Global work is just work now. Your clients are not only hiring talent across borders; they’re transacting with vendors and contractors in multiple currencies as a routine part of how their businesses operate.

As a result, many accounting leaders are asking the same question right now - both for their own firms and for the clients they advise: What’s actually the best way to handle international payments and foreign exchange (FX)?

Part of the issue is that most firms haven’t landed on a clean solution for their own international payments. So you’re figuring it out for yourself at the same time as you’re managing it for clients, and the complexity compounds.

Business owners have normalized the friction. They’re not asking for a better setup because they don’t know one exists. But you’re in a position to see it clearly for both of you — and that’s where the opportunity sits.

First, a distinction:

The terms “international payment” and “foreign exchange (FX) payment” are often used interchangeably, but there’s an important distinction worth making.

International payment is the umbrella term for any money movement across borders, regardless of currency.

Within that, there are two approaches: you can send USD as-is, so the recipient gets dollars; or you can make an FX payment, where the currency is converted at the point of transaction. Your client’s account is debited in USD, but the vendor receives payment in their local currency.

Contractors and vendors almost always prefer local currency, and for good reason. When payments are sent in USD internationally, vendors can be hit with surprise fees or unfavorable exchange rates on their end, meaning they receive less than expected. That creates friction, erodes trust and puts your client in the awkward position of explaining a shortfall they didn’t cause.

FX payments, by converting the currency upfront, remove that uncertainty.

The vendor knows exactly what they’ll receive, and your client has full visibility into the true cost. Most firms, however, aren’t making a deliberate choice between the two - they’re managing whatever setup they’ve accumulated.

Most firms fall into a messy process without meaning to.

A client brings on an overseas contractor, so you find a way to pay them. A supplier wants to be paid locally, so you add a platform for that. Another client is already using something else and wants to stay on it, so you work with that too.

Each decision makes sense in the moment. Over time, they accumulate, and you end up managing international payments across multiple systems, with inconsistent data and no simple way to see the total cost without recalculating it.

The most visible problem with the lack of strategy is fees. When you’re running payments across multiple platforms, you’re absorbing some combination of:

But the harder problem is that you can’t compare across platforms, which means you can’t tell clients what things actually cost, and you can’t budget for it accurately yourself. Here’s an example to demonstrate:

In this example, platform A may look cheapest until you do the math. And nobody’s doing that math every time, which means clients are making payment decisions based on habit, not cost.

The financial hit is only part of it. When payment data lives across multiple platforms, each with different formatting, settlement timing, and exchange rate disclosure, consistency erodes.

That inconsistency doesn’t just create reconciliation work. It:

• Weakens reporting clarity

• Introduces variability into forecasting

• Increases the likelihood of misclassification or incomplete documentation

Over time, fragmented payment processes don’t just cost money. They compromise system integrity, which is the very foundation that advisory confidence depends on.

Evaluate what your setup is really costing you

Whether you’re evaluating your own setup or a client’s, these four metrics tell you if international payments are working or costing more than they should:

1. Total cost per payment: Add up transaction fees, intermediary bank fees, and FX spread markups. If you can’t easily calculate this across platforms, that’s already a problem.

2. Reconciliation hours per month: How much time is spent matching international payments to accounting records? You know manual matching eats hours and takes focus away from higher value work.

3. Payment timing predictability. How much advance notice exists between initiating a payment and when funds actually leave the account? Inconsistency here creates forecasting problems that ripple forward.

4. Cash flow flexibility. Does the current setup allow any control over when funds leave, or does every international payment require immediate outlay? Domestic payments have long offered breathing room between initiation and settlement. FX payments are catching up, and the ability to manage that timing is a lever most clients aren’t using yet.

If any of these are hard to answer, that’s the signal to dig deeper.

Here’s how your international payments could be running

Once firms take a step back and look at the real costs, the next question is inevitable: well, what does a well-structured setup actually look like? The good news is you don’t need to rebuild anything. The capabilities already exist.

Here’s what to look for in the tech:

Everything runs through one platform. Domestic and international, together. That means a consistent audit trail, unified reporting, and no more tab-switching to figure out what a payment actually costs. If you can’t see all your payments in one place, you don’t have a clear picture of your payables - full stop.

Currency conversion happens upfront, not on the vendor’s end. When your client’s vendor is the one absorbing the exchange rate uncertainty, that’s a relationship risk your client may not even know they’re carrying. A better setup converts at the point of transaction, so both sides know exactly what’s moving.

Financing flexibility is built in. This is a real needle mover. At Melio, it’s one of the capabilities we’re most proud of, and consistently one of the most talked about with our clients. International payments can be funded by credit card rather than immediate bank transfer. That means the payment goes out right away, but the cash doesn’t leave your client’s account for up to 45 days. Imagine telling a client: “I can pay your overseas vendor today, but you don’t have to part with the cash for over a month.” For clients managing tight cash flow, that timing can change everything, and it’s the kind of insight that makes clients realize their accountant is thinking about their business, not just their books. Win win.

Clean data, clean books. Every international payment should generate the same clear record: amounts paid, currencies used, exchange rates applied, and settlement dates, and integrate cleanly with your general ledger. If you’re spending hours each month on manual workarounds, that’s a signal the setup isn’t working.

A solution built to scale. The right setup handles five international payments a month the same way it handles fifty, without adding complexity or requiring a new process every time volume grows.

Next time you’re reviewing a client’s payables, ask the question.

How much are they really paying for that overseas wire?

The answer might surprise both of you. The conversations that follow about true cost, cash flow timing and vendor relationships present an advisory opportunity many accountants haven’t tapped yet, because international payments have never been this visible or this manageable before.

The good news is that improving your setup doesn’t mean adding another app to your stack. You get to cut tools rather than accumulate more.

If you’re ready to consolidate your workflow, check out how Melio can help you handle international payments more seamlessly, with you in control.

Many firms are approaching AI as a technology decision when it is really a business model decision. Adding another tool to an outdated operating model rarely creates transformation. It often just adds noise. The firms that will benefit most from AI will be the ones willing to rethink how work gets done, how people are developed, how value is priced and how client relationships grow.

That makes this ADP whitepaper, The Rise of the AI-Enabled Accounting Firm, especially timely. It focuses less on hype and more on the broader shift happening inside the profession right now.

This Shift Is Bigger Than Technology

The whitepaper opens by talking about how AI is accelerating forces that have already been building for years. Those pressures are familiar to every firm leader:

• Rising client expectations

• Persistent capacity constraints

• Consolidation pressure

• Erosion of traditional time-based pricing models

AI did not create these realities. It simply makes them harder to ignore.

That is why this conversation cannot be limited to software demos and prompt tips. Firms are navigating structural change.

The Real Opportunity Isn’t Automation Alone

For years, firms have used technology to improve efficiency. That matters. But efficiency alone has limits. If all AI does is help you complete the same work faster, you may create some short-term capacity. But if you do nothing different with that capacity, the long-term impact is limited.

ADP’s research found that accountants see the greatest revenue opportunities from AI come from improving efficiency and expanding advisory offerings. Those pairings matter. Capacity creation and growth strategy must work together.

The smarter question is not: How much time did AI save us? It is: What higher-value work did that time allow us to do?

Most Firms Are Early — And That’s Okay

One of the more revealing findings in the report is that most firms are still in the early stages of adoption. ADP notes that 88% of firms remain in exploration or early experimentation phases.

That should not create panic. It should create perspective. Many leaders feel behind because the AI conversation moves so quickly. But being early in the journey is normal. What matters now is moving with intention.

The firms that win this phase will not chase every new tool. They will build practical habits, clear policies and real use cases.

Leadership Matters More Than Software

The whitepaper outlines a simple but important truth: firms do not need everyone to be an AI expert. They do need:

• Internal champions

• Managers who know how to integrate AI into workflows

• Staff trained in responsible use

• A culture that encourages learning and experimentation

That is leadership work.

Technology without leadership creates scattered experimentation. Technology with leadership creates progress.

The Human Advantage Gets Bigger, Not Smaller

One of the biggest misconceptions in the market is that AI reduces the importance of people. In reality, it often increases it.

As routine work becomes easier, the differentiators become more visible. Things like judgment, communication, trust, strategic thinking and empathy are capabilities clients remember and reward.

Our skills in analyzing data and helping clients make sense of it are not going away. This is the moment to use AI to become better professionals and better humans.

Start With the Model, Not the Tool

If your firm is evaluating AI right now, begin with bigger questions:

• What work should humans spend less time doing?

• Where do clients need more guidance from us?

• How should we develop our people differently?

• What outcomes are clients truly paying for?

• What kind of firm are we trying to become?

Those answers should shape your technology decisions, not the other way around.

What This Means for Firm Leaders

AI is important. But tools alone will not transform firms. A better operating model will.

The firms that thrive in this AI era will be the ones with the clearest leadership, the strongest curiosity and the most thoughtful blend of technology and human expertise.

AI won’t save outdated firms. But it will accelerate the ones brave enough to change.

Read The Rise of the AI-Enabled Accounting Firm by ADP. It’s a strategic framework for understanding why this moment matters, what forces are driving change and practical steps firms can take to use AI confidently without overextending themselves.

Then, they go right back to work and communicate the same way they always have, regardless of who’s in the room or what the goal is.

It’s not that you’re a bad communicator; it’s that you’re using the same communication style in a bunch of different situations.

Same Person. Wrong Room.

Think about a typical week...

• You’re in a one-on-one with a team member where your job is to listen, support and create space.

• You jump into an internal team meeting where the goal is alignment, decisions and clear ownership.

• You’re on a mixed call with leadership and junior staff, where you need to bridge gaps in context and understanding.

• And then you switch into an advisory conversation with a client, where your role is to translate complexity into something usable and guide them toward action.

Those are not the same conversations. If you show up the same way in all of them, something is going to break.

Why Accountants Get Trapped Here

The problem is that most of us don’t actually evaluate our communication in a structured way. We leave a call and think, “That went fine,” or “That felt a little off,” without ever breaking it down into what actually happened.

We rarely take the time to ask ourselves questions like:

• Did I clearly state the purpose of the conversation?

• Did I organize my thoughts in a way that made sense?

• Did I ask questions that helped me understand the other person, or did I just move forward with my own agenda?

• Did I define next steps clearly, with ownership and timelines?

• Did the other person leave feeling more confident, more clear and more able to act?

Those are the things that determine whether a conversation is actually effective.

Why This Matters Even More in the AI Era

AI is rapidly making technical answers easier to access. That means the human side of business becomes more valuable, not less.

When you better understand your communication style — your clarity, engagement, impact, authenticity and action — you can understand whether your conversations are actually productive, regardless of the situation. And recognizing of how these traits vary depending on the context you’re in provides a deeper understanding.

Clarity in an advisory conversation might mean breaking down a complex tax strategy into simple parts and checking that your client actually understands it. Clarity in an internal meeting might mean clearly assigning roles, responsibilities and deadlines so nothing falls through the cracks.

Engagement in a one-on-one might mean asking open-ended questions and letting the other person drive most of the conversation, while engagement in a leadership discussion might mean actively pulling in different perspectives and managing tension without shutting anyone down.

It’s the same skill, but with different behavior.

That’s why context matters so much, and why most communication feedback falls short. Generic advice like “be clearer” or “ask better questions” doesn’t actually help if you don’t know where, when and how to apply it.

What works in a client advisory call might not work in a team meeting, and what works in a low-stakes conversation might completely fall apart in a high-tension one.

You Can Address These Pitfalls

Navi, by ExelLabs, grades whether you’re clear and engaging, but it also evaluates you based on how you showed up in a specific conversation. It looks at whether the audience was internal, external or mixed, whether the relationship is new or established, and even whether there’s tension in the room. All of those factors change what “good communication” looks like.

You can become a better communicator, especially when you have a copilot that makes you more aware of the room you’re in and coaches you on how to adjust your approach to match it. You’ll see how you need to deliver information in a way that works for the person sitting across from you within a specific context.

Stop asking: “Am I a good communicator?” and start asking: “Did I communicate the right way for this moment?”

That question changes leaders. It changes client relationships. It changes firms.

Everyone is talking about AI agents, and accounting is no exception. But what is an AI agent in accounting, and what does it mean for the way your firm works? Here’s a plain-language breakdown.

An AI agent in accounting is a software program that executes financial workflows using rules, data inputs, and conditional logic. Unlike general-purpose AI models that generate responses to prompts, AI agents are designed to perform tasks consistently and repeatedly within structured accounting processes.

AI agents are typically used to automate routine activities such as transaction categorization, reconciliations, and exception detection, while operating within constraints defined by accounting professionals.

What an AI Agent is Not

An AI agent is not a replacement for an accountant. It extends the accountant’s capacity, executing what is defined, consistently and at scale. The accountant’s judgment goes into building the agent. What repeats is the execution.

Think of it like a racecar. The car is fast, precise, and built for performance. But you still need an experienced driver behind the wheel. You would not send someone without a license to a racetrack. The same logic applies here. You would not run an AI agent without someone who understands the accounting behind it.

The accountant manages the agent. The agent handles the repetitive work.
The accountant remains responsible for the outcome.

AI Agents vs. ChatGPT and Claude

General AI systems, such as chatbots or large language models like ChatGPT and Claude, are probabilistic. They generate outputs based on patterns in data and may produce different results when given the same input multiple times.

AI agents, by contrast, are deterministic in execution. They follow explicit rules and workflows defined by the accountant. That said, not all AI agents are built the same way. A well-designed accounting agent locks the logic so it runs identically every time. A poorly designed one can still drift. For accounting firms evaluating AI tools, that distinction matters more than almost anything else.

In accounting contexts:

General AI: Answers questions or generates explanations
AI agents: Execute accounting workflows and return results for review

How AI Agents Work in Accounting

Here is an example of how an AI agent can work in accounting. AI agents operate by combining structured data such as the general ledger and bank feeds with predefined instructions. Those instructions determine how the agent processes transactions, identifies discrepancies, and handles exceptions.

The typical workflow looks like this:

1. The accountant defines the workflow and sets the rules.

2. The agent pulls in transaction data and applies those predefined rules.

3. Anything that falls outside those rules is flagged for review.

4. The output is a set of completed tasks and a short list of exceptions.

5. The accountant reviews the results before anything is finalized.

Common Use Cases

A few examples include:

Bank Reconciliation: Match Transactions Without the Manual Work

An AI agent compares bank transactions with ledger entries. If records match, they are marked as reconciled. If discrepancies exist, the agent flags them and may generate suggested adjustments.

Transaction Categorization: Sort at Scale, Review Only What Matters

The agent reviews uncategorized transactions and assigns categories based on historical patterns or predefined rules. Transactions that do not meet criteria are flagged for review.

Exception Detection: Catch Errors Before They Become Problems

Agents identify anomalies such as duplicate transactions, missing entries, or unusual variances. These items are isolated for further investigation.

Role of Human Oversight

In purpose-built accounting agents, human oversight remains central. Accountants define the rules, thresholds, and workflows that guide the agent’s behavior.

Well-designed accounting agents do not make independent judgments or interpret accounting policy on their own. Final decisions, approvals, and adjustments remain the responsibility of the accountant.

The accountant manages the system. The accountant reviews the output. The accountant approves the final result.

This is the model firms should look for when evaluating AI in accounting: execution handled by the system, judgment retained by the accountant.

Impact on Accounting Workflows

The use of AI agents shifts accounting work from manual execution to review and analysis. Routine tasks are automated, allowing accounting professionals to focus on higher-value work such as financial interpretation, advisory services, and client communication.

This approach can improve efficiency, reduce processing time, and help firms handle more work without adding headcount.

For accounting firms, that shift can be significant. Firms using purpose-built AI agents for month-end close report managing 25 to 30 clients with the same team that previously handled 5 to 10.

The shift is not about speed for its own sake. It is about removing the repetitive work so the accountant’s time goes toward review, judgment, and client advisory.

What This Looks Like in Practice: AI Close

One example of this in accounting is AI Close by Puzzle. It is the first agent builder integrated directly with the general ledger, which means the agent and the books live in the same system. No export. No sync. No reconstructed audit trail. The work happens inside the ledger itself, with the audit trail built in.

Step 1: The accountant defines the task

An accountant opens the close checklist and adds a new step, like bank reconciliation. Instead of writing code or configuring a system, they describe the task in plain language, the same way they would explain it to a colleague: pull last month’s bank transactions, match them against the ledger, mark what reconciles, and flag what does not.

Step 2: The system turns that description into an agent

That description becomes the agent. The system translates it into explicit, repeatable steps that can run the same way every time.

Step 3: The agent executes the work

When the close runs, the agent does the work. It pulls the data, applies the logic, and returns a result: matched transactions and a short list of exceptions that need attention.

Step 4: The accountant reviews and approves

The accountant reviews the output, makes any adjustments, and approves it. Nothing posts to the ledger without that sign-off.

Step 5: The same agent runs again next period

The next month, the same agent runs again with the same logic, rules, and output format. The accountant does not need to rebuild it or re-explain it. They review what comes back.

Step 6: Execution repeats, judgment stays with the accountant

This is what makes agents different from a one-time AI query. The work is defined once and runs repeatedly. The accountant’s judgment is built into the setup. What repeats is the execution, not the thinking.

The accountant manages the workflow. The AI executes the task.

That is the real promise of AI agents in accounting: not replacing the accountant, but extending the accountant’s ability to execute with speed, consistency, and control.

AI agents do not change the role of the accountant. They change the shape of the work. Execution becomes faster and more consistent. Judgment, review, and accountability stay where they belong: with the accountant.

AP and AR have always been the unglamorous back-office chore — messy, manual and a total margin killer. Firms can’t ignore it, but they also can’t keep letting it chew up staff capacity, delay month-end and stall advisory work. That’s exactly where AI steps in as the radical sidekick, not a scary disruptor.​

Instead of team members chasing invoices, digging through email for client and vendor questions and re-keying the same data across systems, AI can sit on top of your AP workflows. It can answer questions, surface insights and keep things flowing so your team has time to think more profoundly about the numbers. In other words, AP becomes the first, practical place where AI is deeply helpful, not hype-driven.​

Where do you start? With busywork!

Give AI the busywork

Start by identifying the most time-draining, manual AP tasks in your firm and hand those off to AI first.​ Just think about all that AI can handle for your firm:

• Answer repetitive vendor and client questions like “Did this get paid?” or “What’s the status?” by pulling from synced AP and GL data instead of staff digging through systems.​

• Handle lookups like historical payment patterns, average days to pay or vendor totals so humans aren’t living in spreadsheets.​

• Flag anomalies in bills, possible duplicate invoices or out‑of‑policy payments before they hit the GL.​

• Summarize AP activity for the week or month so accounting professionals can walk into client meetings already armed with talking points.​

When AP is powered by a modern platform that syncs cleanly with the GL, you’re no longer asking team members to dig through and push paper. AI can now do the grunt work so your team can focus on judgment, relationships and strategy.​ AI can serve as your always-on AP assistant, there to answer questions in real time. All you have to do is ask.

It’s also important to note that AI is not something to be feared. There is no steep learning curve or deep knowledge of tech required. It really is just about having conversations. Talking to AI in plain language to get the information you need with speed and efficiency.

Predict cash crunches before they hit

The real magic happens when AI both answers questions and spots patterns.​ This is the level of power offered in advanced AI-driven AP/AR platforms. For example, Melio’s AI agent, MEL, allows you to ask deeper, analysis-based questions on demand to surface insights faster and with more accuracy.

This means that AI can quickly and reliably:

• Forecast upcoming cash crunches based on open bills, receivables and historical payment behavior.​

• Surface vendors that you can safely slow‑pay, and which ones you should fast‑pay to protect key relationships.​

• Highlight opportunities to use card-based payments or pay-over-time options to smooth out big cash outflows.​

• Turn raw transactions into plain‑language insights that open the door to deeper cash flow advisory.​

This is where AP stops being a cost center and becomes your on‑ramp into ongoing, high‑value cash flow conversations. It’s powered by AI, but delivered by you.​

AP as the gateway to GL modernization

The radical truth is that you don’t modernize the GL by starting in the GL. You start at the edges, like with AP and AR, then build inward.​

When clients live in a simple AP experience instead of inside the accounting software, you protect GL integrity and reduce the clean-up chaos that kills your margins. A modern AP platform that syncs with your accounting system in real time gives you:​

• Cleaner, more consistent data feeding the GL automagically.​

• Fewer client‑created errors, because they’re pressing buttons in a simplified AP environment, not experimenting in the GL.​

• Faster reconciliations and reporting, because AP and GL are working from one source of truth.​

Layer AI on top of that environment and you’ve quietly started your GL evolution without a massive, scary “system overhaul” project. AP becomes the low‑risk sandbox where your team learns to work with AI, and then those same patterns move deeper into GL review, month‑end, and eventually firm‑wide workflows.​

Adopt and leverage your first AI assistant: Start with AP

If AI feels overwhelming (and it likely does), just start small and strategic. Make AP the first place AI shows up as that “always-on” assistant, not an intruder to fear and avoid.

A practical rollout might look like:

• Phase 1: Use AI to answer AP status questions and support staff with simple data lookups. ​

• Phase 2: Turn on AI‑driven alerts for duplicate bills, policy exceptions and potential cash crunches.​

• Phase 3: Connect these insights to advisory, like regular cash flow check‑ins and payment strategy. This can evolve into GL-level pattern spotting, helping companies identify where clients can extend terms, smooth out cash swings or even leverage card-based payments to improve working capital. This turns foundational AP work into higher-value strategic offerings like cash flow advisory.

The goal is to get to a place of comfort with AI. But to do that, it’s time firms stop viewing it as scary and start envisioning what it can do. That includes leveraging a data-driven AP assistant that’s always ready and waiting to process questions and churn out answers. One that will never retire and represents a central knowledge base of all things AP.

It’s time to start building a modern AP environment that protects your GL and your margins. AP is the gateway to the next‑gen firm where AI handles the busywork so your team can finally focus fully on building for the future.

Start where it matters

AI doesn’t need to show up everywhere on day one to make an impact. It just needs to show up where it removes friction, protects margins and gives time back to your team.

AP is the most practical place to start.

When AI handles repetitive questions and manual lookups, your firm gains efficiency, but more importantly, it gains clarity. And from that clarity comes better conversations, stronger advisory, and a smarter path to modernizing the GL without disruption.

The future of accounting isn’t built in massive, risky transformations. It’s built one smart workflow at a time.

Start with AP. Give AI the busywork and let your firm focus on what’s next.

They’re adding new tools, testing automations and sitting through demos that promise to make everything faster and more efficient. And for a moment, it feels like progress.

But then… not much changes. The workflows are still messy. The team is still overwhelmed. The impact feels smaller than expected.

So what’s actually going wrong?

It’s not that AI doesn’t work. It’s that most firms aren’t set up for it to do anything helpful.

AI just amplifies broken systems. And accountants’ systems have been broken for a long time.

AI is only as good as your workflow

There’s a common misconception right now that adding AI will naturally make things more efficient. But AI doesn’t replace your systems, it runs on them.

It pulls from your data, your workflows and your processes. If those things are inconsistent or unclear, AI doesn’t clean them up — it scales them. That’s why some firms see real gains, while others feel like they’re spinning their wheels.

The difference isn’t the tool. It’s the system underneath it.

AI isn’t breaking your firm, it’s revealing it

Most of the time, when AI “fails,” it’s exposing problems that were already there.

Data is scattered across emails, spreadsheets and different tools, with no real source of truth. Workflows vary depending on who’s handling the task, making it hard to create consistency. Leaders don’t always have visibility into where work slows down or breaks, which makes it even harder to improve anything intentionally.

And underneath all of that, many processes were never actually designed. Things just piled on over time.

That kind of environment makes it nearly impossible for AI to do its job well.

Fix the system, not the tool

If firms want to see real impact from AI, the focus has to shift. Not toward more tools, but toward better systems.

That means getting data organized and accessible. Defining how work should flow, even if it’s not perfect yet. Creating visibility into what’s actually happening across the firm, instead of relying on assumptions.

Once that foundation exists, AI becomes powerful. Without it, it’s just another layer of complexity.

So the real question isn’t, “Which tool should we use?”

It’s, “What kind of system are we giving it to work with?”

The work is getting faster. The tools are getting smarter. And yet, somehow, the pressure isn’t going down. If anything, it’s increasing. Because the expectation is no longer just to get the numbers right. It’s to help clients understand what those numbers mean and what to do next. That’s a very different job.

And it’s exactly why I wanted to record a full demo of Navi. It’s not a pitch, but a real, behind-the-scenes look at how we, at XcelLabs, are thinking about the future of this profession and what we’re building to support it.

If you have 20 minutes, I’d encourage you to watch the full walkthrough. But if you don’t, here’s what I want you to take away.

We’ve Been Measuring the Wrong Things

For decades, firms have been built around metrics like billable hours, utilization and realization. Those numbers made sense when accounting was primarily about production like getting work done, getting it out the door and getting paid for it. But that’s not the world we’re operating in anymore.

Today, the real drivers of growth look very different. They show up in the quality of your client conversations. In how clearly you communicate. In the level of trust you build. In your ability to guide decisions, not just report results. The problem is, we’ve never had a way to measure any of that. So firms keep optimizing what they can see, even if it’s no longer what matters most.

Advisory is a Skillset Not a Service Line

We’ve been talking about advisory for years. At this point, it almost feels like table stakes. But most firms are still trying to figure out how to actually deliver it consistently. That’s because advisory requires a different set of skills than most accountants were trained for.

Technical expertise if the foundation, but how you handle a conversation when a client is uncertain is what really matters. It’s how you guide someone hesitant to make a decision. It’s how you simplify something complex without losing its meaning. It’s how you lead.

For a long time, the only way to learn those skills was by proximity. You sat outside a partner’s office. You listened in on calls. You picked it up over time. That doesn’t work anymore is a remote world where things are changing faster than ever.

AI Isn’t Just About Efficiency

Most of the conversation around AI in accounting has been about doing things faster. And yes, that’s part of it, but it’s also the least interesting part. The real opportunity with AI is using it to change how we think.

That’s where this idea of AIQ (Artificial Intelligence Quotient) comes in. It’s the ability to work with AI as a thinking partner. To bring context into it. To challenge it. To use it to sharpen your thinking instead of replacing it.

Two people can use the exact same AI and get completely different results. The difference isn’t the technology. It’s how they show up.

What Navi Is Actually Trying to Solve

When we built Navi, we were trying to solve for the moments where you leave a client call and think, “That could have gone better.” For the times when you hesitate before saying what you really mean. And for the situations where you get pulled into a mental loop, replaying a conversation, second-guessing a decision, wondering what you missed.

Those moments are everywhere in firms. They just haven’t been visible. Navi brings visibility to them.

It takes a real conversation with an actual client and helps you see how you showed up. It’s not judgmental. Rather, it’s grounded in improvement. It highlights where you were clear and where you weren’t. Where you led and where you gave up control. Where you created impact and where there was an opportunity to go further.

And then it lets you do something we’ve never really been able to do before. It lets you ask better questions about your own performance… Why did that conversation stall? Where did I lose alignment? What could I have done differently in that moment?

And because it’s grounded in your actual interaction, the answers are relevant. They’re actionable. They stick.

The Real Value Isn’t the Score

Navi scores how you perform in different areas. It’s useful because it gives you a baseline and shows you progress over time. But that’s not where the real value is. The real value is in what happens after. It’s in the awareness you start to build. The patterns you begin to recognize. The confidence that comes from understanding not just what happened, but why.

Because once you see it, you can change it. And when you change how you show up in conversations, everything else follows. Your client relationships improve. Your team becomes more capable. Your firm starts to operate differently.

This Is About Relevance

At the end of the day, this isn’t really about technology. It’s about relevance.

Compliance work is already being automated. That trend continues to accelerate. So the question becomes: What makes someone choose you?

It’s not just your ability to produce the work. It’s your ability to lead, interpret and guide. It’s how you make someone feel in a conversation. It’s the clarity you bring when things are uncertain. That’s the value. And right now, in most firms, that value lives in a few individuals. A handful of partners. A few strong advisors.

What happens when you can scale that across an entire team?

That’s the opportunity. And it’s also the urgency. Because the future of this profession isn’t 10 years away. It’s the next few.

We don’t need to become something completely different. We already have the foundation. We just need to learn how to use it intentionally, consistently and at scale.

See Navi in Action

If you want to see what all this actually looks like in practice, the full demo above walks through it step by step. But more than anything, I hope it changes how you think about where we’re headed. Because it’s something you can actively shape.

AI-powered tax research is having a moment. It seems like every day there’s another headline about what AI can do for tax workflows, how fast it’s evolving, and why your firm needs to act now.

These headlines aren’t wrong. AI-powered tax research just keeps getting more sophisticated and firms are adopting it at a rapid pace.

Research from Blue J’s own Outlook Report had similar findings:

• 54% of respondents reported using some form of AI to do tax research

• 86% of respondents agreed that AI-powered tax research creates an advantage for firms

• 735% YoY increase in tax questions asked on Blue J from July 2024 and July 2025

Despite all this positive momentum, plenty of tax professionals still feel stuck. With multiple vendors all making the same promises of speed, accuracy, and security, it’s a wonder any of us ever move past the evaluation stage. After subjecting yourself to a blur of vendor demos and seemingly interchangeable feature lists, sticking with your current tech stack can start to feel like the easiest option.

Why Information Overload Leads to Inaction

No matter how much we might like to think of ourselves as rational, human beings are prone to cognitive biases. When you’re overwhelmed—possibly from all those demos and feature lists—defaulting to one of these biases is an easy way to cut thinking costs. Most of the time, the reason you hold off on choosing a new tool has nothing to do with the tool itself. And everything to do with the process of choosing one.

Status Quo Bias

When faced with uncertainty, we tend to stick with what we already know—even if it’s slower or less efficient. In psychology, this phenomenon is called the status quo bias. While leaning on this cognitive bias can free up space for other mental tasks, it can also lead to missed opportunities.

Accounting has a well-known acronym related to this bias: SALY, or Same As Last Year. It may be rooted in a desire to drive consistency, but defaulting to SALY can also drive stagnancy. When you don’t take the time to reevaluate your tech stack, all the issues caused by that tech can compound year over year.

Luckily, the behavioral science experts at The Decision Lab have some advice on how to disrupt this bias:

• Increase awareness: This requires weighing your options, giving equal consideration to each.

• Create space to consider: In a busy firm, it’s easy to put off making a decision until a block of free time magically appears in your calendar (spoiler: it will never happen). To get past this, book blocks of uninterrupted thinking time in your calendar and look to expert-vetted evaluation questions to make the best use of that time.

Loss Aversion

Humans don’t weigh gains and losses evenly. A potential loss feels more painful than the joy associated with an equivalent gain. This cognitive bias is called loss aversion, and makes us want to hang on tight to what’s known and familiar—including legacy tax research solutions.

When you’re evaluating AI-powered tax research tools, the promise of saving hours on research doesn’t feel nearly as impactful as the perceived risk of losing credibility or wasting spend.

But once again, the experts at The Decision Lab have a few strategies for fighting back against this bias:

• Frame wisely: Pay attention to the benefits you want to achieve, not just the risks you want to avoid. For a benefits-focused framework for evaluating AI-powered tax research, look through this buying guide.

• Use perspective: Take a step back and pressure-test potential decisions. Consider what would be the worst realistic outcome if you moved forward. This helps put the fear in perspective and makes it easier to decide whether the risk is real or just perceived.

Even after reading this blog, these cognitive biases will almost certainly creep in as you’re evaluating AI-powered tax research solutions. After all, you’re only human. But that doesn’t make decision paralysis any less dangerous.

With so many firms having made the move, staying where you are means getting left behind.

The good news is there’s still time to catch up. With the right comparison tools, you can finally move past the evaluation stage and find the AI-powered tax research solution that works for you.

Top 7 Factors to Evaluate in AI-Powered Tools

When you’re evaluating solutions that all sound similar, focus your questions on the things that actually change outcomes:

1. Answer quality: You need answers you can trust, validate, and stand behind—not just answers that show up fast.

2. Content: Answer quality depends on content quality. Look for deep, authoritative tax source coverage, curated by people who understand the subject.

3. User experience: If a tool isn’t easy to use, it’s just going to collect dust. Widespread adoption demands a workflow that feels intuitive from day one.

4. Price and value: Look past the per seat license price. What matters more is the value you get per active user—based on real adoption rates.

5. Security: Make sure the platform is built to handle sensitive tax work safely, with clear standards and safeguards.

6. Speed of execution: Choose a vendor with a proven track record of ongoing product improvement, so your solution stays current and gets more valuable over time.

7. Post-purchase experience: Implementation is only the start. Ongoing support and reliability are what keep your tax research tool useful long-term.

Want to deep-dive into each of these categories? Download your copy of the AI-Powered Tax Research Solutions Buying Guide.

So Long, SALY

You’ve read the headlines, you’ve watched the demos, and you’ve even memorized the feature lists. But all that information only made you feel more stuck.

Now, you finally have a tool that can get you past the evaluation stage. Armed with a buying guide, you’re ready to cut through the “claim clutter”, to focus on the features, capabilities, and support that really matter. So you can stop watching from the sidelines and see just what this headline-making technology can do for your firm.

We suck up a lot of air talking about creating better workflows and using new technology.

And that’s the problem!

(Okay, fine, I’ll give you points for doing better than the vast majority of professionals who still swear by doing it the same as last year, but you’re not off the hook.)

Technical excellence and efficiency are low-hanging fruit. Of course, customers expect it, but it’s not the part of your business that provides actual value to your clients.

Your clients want to work with someone who can help them understand the big picture of their finances. Anyone (even computers) can spit out an accurate tax return, but it takes someone special to take the time to strategize about their goals and answer the financial questions that keep them up at night.

How Do We Make Accountants Better Advisors?

It starts with self awareness.

Most professionals have no real way to understand how they communicate. It’s really hard to self-reflect and figure out how often you interrupt people, whether or not you use a lot of jargon, if you tend to guide clients or simply react.

This creates a massive blind spot because you can’t improve what you can’t see.

Historically, the kind of feedback you need to improve has been limited. Coaching is expensive and sporadic. Feedback is inconsistent. Your colleagues are busy with their own assignments. Most professionals are left to figure it out on their own.

Navi changes that.

The AI Mirror

Tools like Navi aren’t just trying to automate tasks. They’re starting to act as something else entirely: a mirror.

When you upload client conversations and team meetings into Navi, it reflects your behavior back to you. It can pinpoint:

• How you spoke

• How you structured a conversation

• Where you created clarity or confusion

• Where you missed opportunities to lead

It shows your invisible habits! And once you see them, you can improve them.

With continuous, personalized feedback, accounting professionals can intentionally develop the advisory skills that make them irreplaceable.

If the last 20 years of accounting technology were about building more efficient firms, the next phase is about building more self-aware professionals. Not just faster technicians, but better communicators, stronger advisors and more intentional leaders.

That doesn’t happen with more software alone. It happens when professionals finally start to see themselves clearly and decide to grow.

But by the time the report is finished, the business problem has usually already happened. The payment is late, cash flow is tight or there’s an operational bottleneck. And explaining the past, while important, isn’t what clients actually want from us anymore. They want help staying ahead of problems.

That shift is why we’re entering the end of month-end thinking.

Modern Advisory is About Visibility

Your real opportunity comes from gaining visibility into what’s happening inside a business in real time. Because once you can see patterns as they emerge, your role changes completely. Instead of showing up to meetings saying, “Here’s what happened last month.” You can say, “Here’s what I’m seeing right now and here’s what we should do about it.”

That’s advisory. That’s leadership. And that’s where accountants become truly valuable business partners.

Getting to that level of insight has historically required a lot of manual work. You have to pull reports, dig through dashboards and even ask staff to investigate transactions. All so you and piece together what the numbers might mean. By the time the answer surfaced, the moment for proactive action had often passed.

Enter the Era of AI Agents

We’re beginning to see AI agents embedded directly inside accounting workflows. Right inside the tools you use, allowing you to ask questions about financial activity and instantly surface insights.

→ Instead of running reports, you simply ask the system a question.

→ Instead of digging through dashboards, the platform finds the signal for you.

→ Instead of reacting to problems weeks later, you can see the pattern as it starts to form.

This agent is not replacing you. Actually, your role is being elevated! Because the value you provide does not involve collecting data. It comes from your ability to interpret it and advise on what to do next. AI removes the friction between those two steps.

The Real Advisory Opportunity

When accountants gain faster access to information, something powerful happens. The conversations with clients change. You stop being the person who explains financial history and become the person who helps protect the future of the business.

You start asking better questions:

• Why are these bills starting to creep overdue?

• Why is vendor spend increasing in this category?

• Did growth outpace the systems the company put in place?

• Are there operational pressure points forming?

Those questions open the door to conversations that matter. This is where advisory really lives. And it’s also where you can build stronger client relationships and command higher-value engagements. All because you are thinking about their business alongside them.

From Historian to Strategist

For years, I’ve talked about accountants moving into advisory roles. Luckily, AI agents accelerate that shift. They allow accountants to move:

From processor → protector
From report generator → insight leader
From bookkeeper → business advisor

This is what’s possible when technology frees you from the friction of gathering information. When you can access insights instantly, you spend less time hunting for answers and more time having meaningful conversations with clients. And that’s the work that actually matters.

A Quick Example

In the video above, I walk through an example of this shift using Mel, a new AI agent inside Melio’s AR and AP workflow. Instead of running reports or digging through dashboards, I simply ask questions about what’s happening in the system, and the platform surfaces the answers instantly.

It’s a small glimpse of what accounting looks like when visibility replaces month-end reporting. Take a look. It’s where accounting is heading!

The Firms That Lead the AI Era

Success does not come with the more technology you have. Rather, you have to use technology to become a better advisor. Embrace the tools that give you faster insight, clearer visibility and the ability to ask better questions about what’s happening inside your clients’ businesses. This lets you deliver better intelligence, faster insight and more proactive leadership.

And that’s exactly the kind of work Radical CPAs are built for.

From the outside, it looks like accounting is moving fast. But when I talk to firms, the reality often feels very different.

Partners are talking about AI but aren’t quite sure where to start. Innovation committees are evaluating tools but struggling to move from discussion to action. Staff are curious, and in many cases already experimenting, even if they aren’t officially “allowed.”

So we’re in this strange place where AI is everywhere in the conversation, but adoption inside firms still feels slow. I don’t actually think accountants are ignoring AI. The profession is behaving exactly the way it always has when new technology arrives.

Accountants Are Usually Late to the Party

Historically, accountants haven’t been at the front of technology adoption curves. They tend to move once tools are proven, stable and compliant.

We saw this with digital workpapers, cloud accounting, client portals and e-signatures. In each case, the technology was widely used in other industries long before it became standard practice inside firms.

There are good reasons for that. Accountants operate in an environment defined by regulation, confidentiality and professional liability. The cost of getting technology wrong can be much higher for a firm than it is for many other businesses. So the profession tends to watch carefully before jumping in.

AI is following that same pattern, but this time the speed is very different. AI appears to be evolving monthly or weekly. And clients are already experimenting with it in their own businesses.

That creates a tension we have to address: The instinct to wait for certainty in a world that is moving very quickly.

The Innovation Traffic Jam

Even when firm leadership agrees AI is important, adoption often stalls once the conversation moves from strategy to execution. Inside many firms, AI initiatives run into what I think of as an innovation traffic jam.

Leadership says the firm should explore AI. IT wants to evaluate security and compliance risks. Innovation committees start reviewing vendors. Meanwhile, the people who are most curious about the technology — the staff — aren’t always sure if and how they’re allowed to use it.

So they do what curious professionals always do. They try it anyway. They test prompts. Draft emails. Summarize documents. Explore what the tools can do. But because that experimentation is happening informally, the firm doesn’t really benefit from it. The learning stays isolated instead of becoming part of how the team works.

Tools Aren’t the Real Problem

At the same time firms are trying to figure out AI, they’re also dealing with an overwhelming number of options that are coming at them quickly. For firm leaders trying to make responsible technology decisions, this can create decision paralysis. So many firms default to waiting. But the irony is that the most important learning about AI doesn’t usually come from purchasing a new platform. It comes from experimenting.

When firms begin discussing AI, they usually start with what tools they should buy. But it’s probably the wrong place to start because the real shift with AI is behavioral.

Most people still treat AI like Google. They ask a question, read the answer and stop. But AI works much better as a conversation partner.

• You provide context

• You refine the question

• You challenge the output

In many ways, it works more like interacting with a junior team member than using a search engine. This is where the idea of AIQ, your Artificial Intelligence Quotient, becomes important. It’s your ability to think with AI rather than simply using it as a quick-answer tool. The real benefit of AI is having your people learn how to work alongside it.

The Firms Making Progress

The firms experimenting with AI are permitting their teams to try things, share with one another and explore where AI helps and where it doesn’t. The focus is on building familiarity with AI.

Small discoveries start to accumulate. Someone finds a better way to draft client communications. Someone else uses AI to summarize research or meeting notes. Over time, those experiments begin to change how work gets done.

Interestingly, smaller firms sometimes move faster here. With fewer layers of approval, new ideas can spread quickly across a team. But firms of any size can create the same momentum by simply making space to learn.

Where the Value Shifts

Our business model has been built around time. Hours worked. Time sheets. Billable time. But what happens when work that once took hours can be completed in minutes?

The connection between time and value becomes harder to justify. That’s why value-based pricing and subscriptions are getting more attention. As AI handles more of the grunt work, the value clients place on interpretation, insight and guidance increases. AI is changing where an accountant’s value sits.

We need to change the conversation around AI away from what might be lost to what we gain. Accountants have always spent enormous amounts of time collecting data, organizing it and preparing reports. AI may finally give you time to think. That’s not something we’ve had a lot of time for. In that sense, AI will amplify what accountants can do for their clients.

But the real question is whether the profession is ready to move from talking about AI… to learning how to work with it. It’s time to increase adoption and change the value discussion.

“AI-first” is everywhere right now. Sometimes it means we want to modernize. Sometimes it means we do not want to get left behind. Sometimes it means we bought a tool and now we need to use it.

Regardless, we need a starting point that fits inside a real week. Big change rarely comes from one sweeping initiative or an expensive tool. It comes from small, intentional moments of curiosity, courage and connection that happen over and over again.

Here’s one way to start. Pick one business problem you can feel right now, then run one AI-supported experiment to address it. The next three micro-moments show what that can look like in practice.

Micro-Moment #1: Make One Invisible Conversation Visible

Most firms have been doing advisory work for years without calling it advisory. It shows up in quick questions and short calls. The value is real, even if it never gets captured.

When those moments pass without any record, it becomes harder to learn from them. We miss patterns. We miss training opportunities. We miss follow-up that could strengthen a client relationship. And it gets tougher to connect that work to scope and pricing.

Start small. Choose one recurring meeting or one type of call. If it fits your firm’s policies, professional standards and client consent, try an AI note-taker or a recording. It can capture the substance without making someone multitask through the conversation.

Then review the notes with accounting advisory tech, like Navi. Look for themes and repeat questions. Pull out commitments and next steps. Notice where you gave real guidance that never made it into a deliverable.

Once you look at a few conversations this way, it becomes easier to see the advisory you already provide. And when you can see it, you can train from it, follow up on it and price it with more confidence.

Micro-Moment #2: Use AI for Self‑Development, Not Just Tasks

Once conversations are visible, they become a mirror. A lot of professional development still runs on annual reviews and occasional training. Meanwhile, we spend hours every week in meetings where we could be learning in real time.

A small, meaningful experiment is to have one manager pick one skill to improve. Keep it narrow. Clearer openings in meetings. Better transitions between topics. Closing with firm next steps.

Then use feedback from accounting advisory tech on a handful of calls to support that one change. Share a few transcripts or summaries. Ask the tool to focus on that single dimension. What worked? Where did the conversation drift? Were the next steps specific and owned by someone?

It’s not to “score” a person. It is to reduce guesswork. Growth moves from “How did we do this year?” to “What did we learn this week?”

Micro-Moment #3: Level-Up Coaching and Advisory

Picture a tax manager who has lived in compliance. They review returns, answer technical questions and keep deadlines moving. Advisory conversations and anything that feels like “selling” can feel awkward.

Now the firm wants that manager to take a compliance-heavy topic and turn it into a value-forward conversation. The partner does not have an hour to script it. The manager does not want to walk in cold.

This is a great place for accounting advisory tech support. The manager can rehearse how to explain the opportunity in plain language, anticipate likely questions and draft a follow-up email that recaps the value and next steps.

We are not rewriting the firm’s strategy. We are upgrading one conversation. The manager shows up with more confidence, and the firm gets a repeatable way to help good people step toward advisory without months of partner coaching.

How Micro-Moments Add Up

None of these examples looks like a transformation on its own. That is the point.

Macro change is the sum of many small, specific experiments. One team captures and learns from calls that used to disappear. One manager improves how they run conversations with real feedback instead of gut feel.

Over time, those micro moments change what the firm treats as real work. They shape what gets coached and rewarded. They influence how services get packaged, scoped and priced.

Try One Micro-Moment in Your Firm

It starts with one step. This month, name one business problem you can feel right now. Design one AI-supported experiment around it. Debrief honestly. What improved? What did not? What surprised you? Then run the next one.

If you want more support getting started, Think AI-First and accounting advisory tech tools like Navi can help with the design and debrief. The goal is to keep learning, one micro-moment at a time

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AI is getting smarter every day. It sorts information. It outlines the first draft. It catches patterns that used to take hours of human time. With all of that happening in the background, a new question sits right in front of us.

Where do people add value now?

That is the real turning point. Not the technology itself. The way we lead. Because once the repetitive work gets handled, people have room to think in a new way. They have space to test ideas, explore problems and bring something original to the table. Some leaders make that possible. Some leaders shut it down without realizing it. Let’s talk about the difference.

A New Kind of Leadership Is Emerging

For most people, agentic is a new word. It simply means having the ability to take action without waiting for direction.

Agentic AI follows the same idea. You give it a place to start and it keeps going. It can automatically be programmed to sketch out a multi-step plan or flag something worth a second look. It’s not here to replace your thinking. It just helps you get to the strategic part faster, the part clients actually value.

Agentic leadership builds on that. These types of leaders make it easier for someone to use their judgment, take initiative and spend more time on work that needs a human mind instead of a checklist.

Here’s a great real-world example. CEO Satya Nadella encouraged Microsoft to move from “know-it-alls” to “learn-it-alls.” That mindset made curiosity normal. It made it okay to ask questions, try things and learn out loud. AI fits right into this kind of environment because the tools change quickly. When learning is part of the culture, people can grow with the technology instead of falling behind it.

That’s why this moment matters. AI expands what people can do. Agentic leaders create the conditions for people to actually use that freedom.

Agentic Leaders Invite People to Think with AI

This is where you feel the difference. Agentic leaders want you to use AI as a thinking tool. You try something with AI and see what comes back. You compare a few options. You walk into a meeting with ideas that have already been through a round of stress-testing.

Agentic leaders care about the quality of your insight, not the minutes you spent getting there. If AI cleared the path, great. What matters is what you did with it. They want you experimenting. They want you learning. They want you growing into work that calls for judgment, not repetition.

With a leader like this, you feel free to explore without worrying that you “cheated” by using AI. You are trusted to make sense of the output and turn it into something valuable.

Agentic Leaders Open Space for Higher Value

Now here’s where things get interesting. Once AI handles the basics, people finally get a little breathing room. And that space is where the real work starts. That’s when you can slow down enough to ask a better question, notice something a client didn’t see or follow an idea you never had the capacity to explore.

Agentic leaders want more of that. They want people spending their time on the kind of thinking that leads to advisory work. And when people actually have the room to do it, you see new services and better solutions for clients. None of that happens when leaders keep the focus on old processes and billable minutes.

So, how can we build toward this? You don’t need a sweeping transformation. Try weaving small habits into the day that make AI part of how people think.

Ask your team what tiny frustration they have with workflow and let AI be part of exploring an answer. Add one AI prompt or reflection question to your next project just to see what it turns up. Open a meeting by sharing something AI got wrong or something it revealed, and what you learned from it.

Those small moves add up. They show people it’s okay to try things. And that’s the point. Agency grows through practice, not pressure.

It’s Happening Now

AI is already taking over the routine parts of work. It handles the sorting, the drafting, the checking and the organizing. So, the value moves to what people can interpret and advise on. The insight behind the data. It is a different kind of contribution, and it relies more on judgment than efficiency.

Agentic leaders see this happening in real time. They lean into it. They create safety to try things and learn as they go. They celebrate curiosity because the tools keep evolving. And they treat thinking as part of the job because that is where people can add the most value.

Discover You AIQ

This new era is not about replacing people. It is about freeing them to do high-level advisory work. The leaders who start now will help their teams develop the expertise that clients are craving. They will build teams that use AI as a partner, not a shortcut.

And if you are curious where your own organization stands right now, the AIQ Assessment is a helpful place to begin. It takes a few minutes and gives you insights into your readiness for agentic AI, your cultural strengths and the habits that will help your team grow from here.

AI is not a passing trend or stealer of jobs. Quite the opposite. It’s the not-so-secret sauce to help amplify efficiency. To reduce the stressors that come with time-draining, manual tasks. To elevate a firm and its people.

Even so, accountants continue to struggle with trust where AI is concerned. Is the data secure? Is data integrity ensured? How much do we really know about this AI character?
While these are valid questions, accountants cannot put AI off any longer. It’s time to cut through the noise and get to what AI really means, its value and best practices that will help elevate the accountant role.

What Does AI Really Mean?

It’s important to start with a solid understanding of AI, and the easiest way to do that is to highlight what it is not.

It’s not ChatGPT. Or Copilot. Or Gemini.

It’s not a standalone feature inside a spreadsheet or platform.

It’s also not new.

AI has been around for years, working in the background to elevate workflow efficiency. Think about invoice scanning and OCR. That’s AI at work. Any platform that supports predictive analytics is also AI at work. The difference today is that AI has moved to the forefront. It’s more visible and more “human” than ever before.

And these are all good things! It means that AI is progressively evolving to make our jobs easier. It not only removes manual, repetitive tasks that suck up valuable time, but also supports CFO and teams with predictive analysis, forecasting and a reliable brainstorming partner.

AI should be thought of as a tool that elevates humans, not eliminates them. It’s here to compliment the work of CFOs and team members. However, before that can happen, firms must move past the noise and apprehension and really dig in.

Rest assured that the real wins will go to those who get curious and find new and better ways to work with AI as a dedicated partner, not an afterthought.

Start With Clean Data

AI can’t work miracles. If you start by feeding it garbage, you’ll get garbage back.

CFOs often cling to the fear that: “AI can’t be trusted to deliver accurate results.” To be clear, this is not an AI-only issue; it’s a data issue. If you don’t start with clean data, how can you expect AI to do its job?

Accountants are no strangers to chasing down the latest Excel version or cleaning up numbers that changed three meetings ago. You can’t be expected to output accurate forecasting based on outdated and/or bad data, and neither can AI. It requires current, structured, reliable data from the start…just like humans do.

Also consider how much more AI can do in terms of predictions and insights when you add clean unstructured data into the mix. AI takes emails, PDFs and meeting transcripts, analyzes each communication and provides suggestions for improvement. This combined with clean structured data offers a world of possibilities to better support clients and ensure accurate financials.

Lose the App Chaos with Unified Systems

Your AI strategy must also include a unified technology ecosystem. Too many organizations deal with “app overload” where disparate solutions are used across departments and roles. This makes connecting the dots organization wide virtually impossible while also causing more headaches and late nights than necessary.

CFOs need to adopt a “great re-bundling” mindset. This means ditching dozens of apps and moving data into a single, centralized space. For example, there are platforms that exist to aggregate data for better forecasting, easier cash flow planning and less data-wrangling drama.

It’s about getting to a place where all your data lives in the same zip code, offering instant access and accurate output. This supports CFOs in not just staying on top of work but getting in front of it.

AI is Already Delivering

Whether you realize it or not, AI is already doing a fair amount of work. It’s flagging weird transactions, recommending invoice codes and automating annoyingly repetitive tasks. So let’s give it the credit it deserves, while also understanding that there’s so much more it can do for you.

Advisory is the big ticket. As automation takes over busywork, it frees finance pros to focus on advisory work like solving bigger challenges and offering bolder solutions. Firms are starting to offer services around “data readiness” and even auditing AI systems themselves. (And please, if you’re still billing by the hour, maybe it’s time to think about outcome-based pricing. AI changes how you deliver, so why not change how you charge?)

AI has the power to serve as your dedicated co-pilot, supporting you with recommendations based on the data you feed into it. It doesn’t replace your judgment and expertise, but it will challenge your thinking, help you poke holes in your strategy and bring up things you never considered.

The crucial thing to remember is that you can’t expect AI to be perfect. It’s like training a new hire. Use professional skepticism, check its work and lean into its support.

Success Means Being a Safe, Responsible and Human

Bringing AI into your work isn’t just another tech rollout. It requires a strategy, complete with goals, good governance and a culture that values learning and experimentation.

It’s best to start small. Pick a business problem, try out an AI tool and see where it takes you. Don’t expect one class or webinar to make you an expert. Being hands-on, iterating and, yes, making mistakes is how everyone gets better. Training is critical but so is creating a space where people feel safe to ask “dumb” questions and suggest new ideas.

If you’re ready to get on the AI train and do it right, start with a few tips:

• Don’t boil the ocean. Begin with one real business problem and use AI to tackle it.

• Get your data in order. A little time spent cleaning now saves a lot of AI headaches later.

• Involve the whole team. Be transparent about what’s changing and set clear policies about what’s cool (and what’s not) with data.

• Encourage curiosity and play. The more you interact with AI the more trust builds.

• Always check AI’s work. You have to do this before sharing or acting on its advice. Like humans, it’s not perfect.

AI isn’t something to fear. It should be explored, tested and strategically implemented. It’s also something that can elevate your role beyond comprehension. So, get curious, experiment and see where fully embracing AI can take you.

Impact is the part of the conversation that sticks. It’s what your client learned, but it’s also what they felt. It’s that question you answered that had been weighing on them before the call. It’s the confidence they gained surrounding their next steps. The moment they thought, “Okay… I can actually do this!”

You don’t have to be overly inspirational to make an impact. You just need to be real, helpful and tuned into what really matters to your client in that moment. When you make an impact, your client isn’t just nodding along with the plan you laid out. They actually believe in it and they feel capable and supported in moving forward.

In the past, we only measured impact by looking backward — what happened after the call. Did the client follow through? Did they email you back? Did they take action? That kind of feedback is useful, but it’s limited. Navi helps you see how impact is created in the moment, so you’re not just reacting to results. You’re learning how to shape them as they’re happening.

That’s always our goal as financial advisors. And that’s why Impact is one of the categories that Navi analyzes and scores when you upload your conversations.

Impact lives in the afterglow

The call might be over, but its impact is what remains. It’s the lingering energy, the takeaway line, the gut feeling your client is left with.

Sometimes it’s a phrase you said that landed well because you took their unique personality into account. Maybe it’s the way you delivered your message in a steady, confident and caring way. Sometimes it’s not any specific moment at all, but instead the cumulative experience of building a trusting relationship over time.

Impact really just means that you’re tying what you’re saying to what the other person needs to hear.

You can’t control how someone feels, but you can influence it.

When your presence, intention and language resonate with someone, you can change how they feel.

And Navi can help! It helps you understand how your words and delivery actually land.

When Navi scores for Impact, it’s looking at:

• Did you say something that was clearly memorable or meaningful?

• Did your tone and delivery convey confidence, support or clarity?

• Did the conversation shift the client’s thinking, energy or next move?

Navi also looks for signs that impact may have been missing, like if the call ended flat, the solution felt generic or the energy dropped off at a key moment.

This kind of personalized feedback can help you notice what works so that you can do more of that on purpose.

Why this matters more than ever

Your clients don’t just want numbers. They want support. They want a clear path forward. They want someone to help them make sense of the chaos and give them some clear next steps that don’t feel scary.

So before your next call, ask yourself:

• What do I want them to feel when we hang up?

• What do I want them to take with them?

• What was the point of this call?

Because even if they forget 80% of the details (and they probably will), they’ll remember how the conversation made them feel.

Chaos always creates opportunity, but only if we’re willing to step into the advisory role our clients need.

This year’s tax landscape isn’t “business as usual.” Between new deductions, temporary provisions, confusing reporting requirements and inconsistent IRS guidance, small businesses and employees are overwhelmed. And when people are overwhelmed, they go to Google, TikTok or their POS provider, not their accountant.

That’s the risk. And also the opportunity. Because, as this panel made crystal clear, OBBBA isn’t really about compliance. It’s about conversation.

Here are seven takeaways from the session that took place as part of ADP’s Accountant Summit:

1. Complexity Has Become Client-Facing

Amy, ADP’s senior director of government affairs, laid out the biggest headline items:

• A new overtime deduction, but only for the premium portion and only under FLSA definitions

• A return to full domestic R&D expensing

• A new deduction for voluntary, customarily tipped occupations, capped and income-limited

However, most clients think these deductions are much simpler than they actually are.

As Amy put it:

“It’s not as straightforward as employers and employees think it is.”

And she’s right. The media messaging (“no tax on tips!”) is dramatically oversimplified. If accountants aren’t the ones explaining the nuance, the internet will — and we all know how that goes.

2. Advisory Begins Where Misconceptions Live

Kelly, the Tax Girl herself, brought up the most important truth of the entire panel:

“People think they understand these deductions, but many of them don’t.”

She pointed out:

• Many employers think they can “raise” overtime rates to double time to maximize deductions. They can’t.

• Many businesses think they can reclassify staff into newly “tippable” jobs. They can’t.

• Some employees believe they’re now guaranteed a refund. They aren’t.

Kelly also highlighted that business decisions made for temporary deductions can create long-term compliance problems. And that’s exactly where accountants need to step in. Not just to say “no,” but to say: “Let’s figure out what you can do that makes sense for your business over the next five years, not just the next five months.”

That’s advisory.

3. IRS Guidance is Loosely Written, and Clients Will Need a Translator

One of the biggest surprises? IRS guidance for 2026 planning is… generous. Draft instructions openly use phrases like “Do your best.” That should terrify taxpayers and motivate accountants. Loose rules lead to inconsistent reporting, misclassification and algorithmic mismatch.

And as I shared in the session:

“The IRS will have more data than ever before. And once they have it, they’re going to use it.”

This is the year to help clients:

• Reconcile POS systems with payroll

• Ensure reported tips match historical patterns

• Avoid red-flag fluctuations that algorithms will immediately catch

• Document internal processes

• Understand the trade-off between paycheck withholding and year-end refund expectations

The firms that help clients think proactively and not act defensively will win.

4. Tips, Service Charges & Industry Confusion are an Advisory On-Ramp

Amy outlined how the IRS will define qualified tips, including:

• Cash

• Card-charged tips

• Voluntary tip-sharing arrangements

But not:

• Mandatory service charges

• Large-party auto-gratuity

• Fees imposed by the restaurant

Then, Kelly raised the point almost no one is talking about: service-heavy industries like country clubs, spas and salons may need to fundamentally rethink their pricing model to remain competitive in the labor market.

That’s not a tax return conversation. That’s a strategy conversation.

This is exactly where firms can stretch into true advisory without needing a consulting department or hiring a strategist. You already know the POS systems, the payroll feed, the industry dynamics and the credit calculations. You’re the only one with that complete 360° view.

5. OBBBA Turns Credits into a Gateway Drug for Advisory

I said this during the panel, and I’ll repeat it here:

This bill is a stair-step into advisory for firms that have always stayed “compliance-only.”

Take restaurant credits:

• You can project expected tips

• You can calculate potential credits

• You can compare reported vs. expected tips

• You can prepare clients for audit exposure

• You can create training for staff on reporting best practices

• You can charge for this because it’s real, tangible value

This is how advisory starts — with something you’re already doing, enhanced. Not a pitch deck. Not a new department. Not a brand-new offering. Just a deeper level of service rooted in the work you already know.

6. The Profession Is Changing and Advisory is No Longer Optional

Dan asked a great question during the session: Are firms actually ready for this shift?

My answer on stage is the same answer I’ll give here: They don’t have a choice.

AI is swallowing the grunt work. Automation is collapsing the old billing model. Clients expect explanations, not just deliverables.

And OBBBA (like PPP before it) is creating pressure that moves firms toward communication, interpretation and strategic clarity. That’s the future of the profession. And it’s where accountants will create the most trust, differentiation and revenue in the next three to five years.

7. So What Should Firms Do Right Now?

→ Talk to every client in tipped or overtime-heavy industries

Restaurants, salons, clubs, hospitality, delivery, event staffing.

→ Reconcile POS + payroll before Q2

This alone will prevent 90% of IRS mismatch notices.

→ Create quick education for clients’ employees

A 1-page “What This Means for Your Paycheck” wins enormous goodwill.

→ Offer a 2026 planning call

It doesn’t have to be complex. It just has to start the conversation.

→ Price advisory separately from compliance

Even a small planning fee differentiates value and sets expectations.

Complexity Creates Connection

This bill is more than a compliance change. It’s an invitation for CPAs to step closer to clients, to become clearer communicators, to lead through uncertainty and to bring human judgment back into a world drowning in information overload.

During tax season, clients need more than deliverables. They need your leadership. That’s where advisory lives. And that’s where the future of the profession is heading.

In the accounting world, it might seem like certainty is what clients want most. Precision. A spotless, professional presence that never breaks the script.

But what I’ve learned is that what they often want more than anything is a real human being on the other side of the conversation.

They want to know that you’re with them. They don’t want you to solve all their problems for them; they want you to walk alongside them and use your expertise to help them navigate whatever arises.

That’s authenticity, and it is one of the dimensions that Navi scores on. Navi is a conversation intelligence tool built specifically for accountants. It analyzes your client calls and gives you personalized feedback across five key dimensions that make-or-break trust: authenticity, clarity, engagement, action and impact.

You can have all the right answers, but if you show up like four spreadsheets in a trench coat, the client isn’t going to open up, and you won’t get anywhere.

Authenticity means being honest

Authenticity doesn’t mean turning a client call into a therapy session. It doesn’t even mean saying everything you’re thinking. (Trust me, if I did that, I’d have lost my platform a decade ago!)

It just means letting go of the idea that you need to sound a certain way for others to take you seriously.

Authenticity can look like a lot of things. It’s different for everyone. It could mean admitting when you’re not sure about something, explaining a concept the way you’d tell it to your mom, or pivoting to share a quick story from your own experience to help something land.

It’s as simple as laughing when something’s funny, pausing when something’s heavy or adjusting your language to meet your client where they are emotionally.

These moments might seem small, but they create the kind of safety where all honest, productive advisory conversations start.

Drop the act!

Our world overhypes polish, perfection and professionalism. It’s easy to feel like you have to be “on” all the time. Especially in client conversations, where high fees and high stakes are involved, there’s a lot of pressure to sound confident, competent and in control even when you’re not 100% sure about something.

But clients can feel the difference between a conversation and a performance. When they sense something’s off, like you’re maybe saying what you’re “supposed to” say instead of what you actually mean, they mimic that behavior and start holding back.

Being authentic breaks that cycle and invites your client to drop their act, too.

How do you know if you’re being authentic?

It’s hard to measure authenticity on your own. We all like to believe we’re being ourselves, but sometimes we slip into autopilot and start sugarcoating without even realizing.

That’s where Navi comes in.

When Navi grades a call on authenticity, it’s not just a vibe check. It’s looking for very specific cues. Did your tone feel natural and competent with what you were saying? Did you share anything personal or honest that added value to the conversation? Did you avoid sales-y language? Did you answer questions directly, even when the answer was, “I don’t know”?

If authenticity felt low, Navi doesn’t just hand you a low score. It shows you where it broke down. Maybe your tone didn’t match the emotional weight of the moment, or you dodged a question without realizing it. For me, Navi noticed I’m constantly saying, “That’s a great question,” instead of answering.

These moments matter, and Navi can help you notice them and make real changes to shift your communication style.

Being real builds relationships

Clients don’t need the perfect accountant. They need an advisor whom they can trust.

So, next time you’re in a client conversation, ask yourself: Am I saying what I think I should say or what I actually mean? Am I trying to sound “professional” or am I trying to connect?

Being real is what sticks, what builds trust, and what makes you memorable.

AI is changing accounting. Right now, most people treat it like an intern. It can clean up a report, draft an email or summarize what you don’t have time to read. That is helpful, but it’s also limited.

The bigger opportunity is using AI as a thought partner. Imagine asking it to suggest a few strategies you may have overlooked or to point out a question that could deepen your next client conversation. That is a very different role than a digital intern.

This new skill is called AIQ. It is your ability to think with AI, not just automate tasks. And it is becoming one of the most important abilities for business leaders today.

What Is AIQ

AIQ stands for Artificial Intelligence Quotient. Think of it as your ability to work with AI in a way that levels up your thinking. It is not about writing code or becoming a data scientist. It is about knowing how to use AI in real, day-to-day accounting work.

Research from MIT shows that people who learn to collaborate with AI improve both speed and accuracy. For example, an accountant might use AI to scan thousands of transactions for unusual patterns, then apply their own judgment to interpret the results. A marketing leader might ask AI for a campaign outline, then refine it with human creativity. In each case, AI is doing the heavy lift, but people are steering the outcome. That is AIQ in action.

What if the real breakthrough with AI is not in tasks, but in thinking?

Why It Matters

Moving from tasks to thinking is what raises the stakes for firms. In other words, AIQ matters because it changes how value is delivered.

Compliance work will always be part of the profession, but clients are asking for more. They want advisors who can interpret data, anticipate risks and point to opportunities. Leaders who build AIQ can deliver that depth in real time, when decisions are being made.

And the need could not be more urgent. Deadlines are shorter. New rules keep coming. And client expectations keep climbing. They want faster answers, sharper insights and guidance that looks ahead.

AIQ helps turn those demands into opportunities. Picture an accountant preparing for a client meeting. Instead of digging through articles, they ask AI to pull the latest industry news so they can focus on strategy and advisory conversations. That frees up time for the work clients value most.

The same applies at the leadership level. A managing partner might ask AI to model the impact of a regulatory change on different service lines, then use that analysis to guide strategic planning. Or a leader could use AI to rehearse client conversations, testing how a new idea might land and refining the message before stepping into the room. These are the moments when AI stops being an assistant and starts being a thought partner.

It also matters for talent. Staff who learn to use AI as a thought partner are not just finishing tasks more quickly. They are building the skills to think, analyze and advise. That growth keeps people engaged and helps firms hold on to the next generation of leaders.

Think back to when spreadsheets first showed up. At first, they were a niche tool for specialists. Over time, they became a baseline skill every professional needed. The same happened with pivot tables. What once felt advanced is now essential. AIQ is on that same path.

And the good news is you can start building your AIQ now.

Building Blocks of AIQ

AIQ is not fixed. You can build it step by step. Start small. Use AI to summarize a document, draft meeting notes or highlight trends in data. Let the technology take the first pass. Then apply your own judgment to finish the work.

Encourage teams to experiment and share what they learn. Make time to ask, “What did AI get right? Where did it fall short?” Those small conversations build trust and skill. Over time, people learn to ask better questions, stress test answers and compare results. That is how AIQ gets its start.

As skills grow, the next step is to use AI for exploration. Ask it to surface blind spots, compare options or point out connections you may not have noticed. Prompts like these stretch thinking and train teams to see AI as part of the decision-making process, not just a shortcut.

Try It for Yourself

Your AIQ will shape how you lead in an AI-powered world. It is not about becoming an expert in every tool. It is about learning how to think with them. Because AI can do more than lighten the load. In the right hands, it can change the game.

Curious where you stand? Take our quick AIQ self-assessment and see how your skills stack up.

We don’t just watch the games. We have season tickets, there’s an autographed Dick Butkus painting over the fireplace, and yes, he wears his Bears jersey proudly even though we live just a short drive from Green Bay now.

Me? I’m… adjacent. I was thrilled to watch the Bears beat the Packers last week, but seeing them lose this weekend brought me back to reality. What surprised me most, wasn’t another Bears loss, but how much more I enjoyed watching the game because of analytics.

Seeing the “Why”

The broadcast kept explaining the “why” behind the action. Go for it or punt. Manage the clock or pick up the pace. Every decision came with the mathematical reasoning behind it, and for the first time, I wasn’t just watching the game unfold. I was actually understanding it.

Since we watched the game on Prime, the broadcast leaned heavily into AWS-style analysis. My husband, who has decades of football stats living rent-free in his brain would say things like, “Statistically, they should go for it here.”

I’d laugh and reply, “Analytics!”

It became a game between us that made me feel more connected to him and to these games he’s always put on the TV for as long as I’ve known him.

With the analytics in mind, I could follow the logic and not just the emotion. I wasn’t just reacting to big plays based on how intensely he was yelling at the screen. I was engaged in the strategy.

And that’s exactly what AI-X is all about!

Seeing Things More Clearly

In our world of accounting advisory and firm leadership, we’re often told that AI or analytics will change everything. But too often it’s presented as a replacement: something cold and impersonal meant to take over.

In reality, when it’s done right, it doesn’t replace human experience. It helps us understand it.

That’s what Navi was designed to do. It’s built to help firms see the field more clearly. To take all that institutional knowledge (the gut instinct, the client nuance, years of experience, etc.) and make it visible. More shareable. Useful in real time.

The same way the broadcast brought me into the game, Navi brings your team into the decision-making process. It uses data to provide context, and it makes logic feel obvious.

Seeing the Whole Picture

When people can see the full picture, the whole team plays better.

The insights aren’t siloed in one expert’s head. The strategy is out in the open and it guides better choices.

That’s what changed the game for me these past two weeks, watching the Bears’ historic Super Bowl run. And that’s what will change the game for firms that embrace AI-X.

Whether it’s the fourth down at Soldier Field or your next big client decision, the right data at the right time makes everyone smarter, more confident and more engaged.

Analytics might just be my new favorite part of football. Go Bears!

Of all the benefits that come from using AI for tax research, saving time is probably the most obvious. But when arriving at answers takes minutes instead of hours, some firms are left wondering what that means for their billings.

It’s a fair question, though the wrong one to focus on. Accelerating your tax research doesn’t shrink revenue potential. It’s quite the opposite—provided you have the right billing method and the right strategy to redeploy your time.

In this article, we’ll cover what it takes to make this shift, including:

• What the data says about AI efficiency

• Competitive advantages of AI-powered tax research

• The mismatch between hourly billing and how AI delivers value

• Exploring new ways to bill for your work

• Ideas for turning efficiency into opportunity

• A real-life example from accounting firm Larson Gross Advisors

The Data Behind AI Efficiency

By now, most of us have seen or experienced just how fast organizations’ use of AI is accelerating. And this trend extends into tax, where over half of the tax practitioners surveyed for Blue J’s AI Tax Research Solution Outlook Report reported using some form of AI for tax research.

For practitioners accustomed to legacy tax research tools, switching to AI-powered research can be transformative. Traditional tax research tools often require you to spend hours crafting complex Boolean searches and mining through the sources to stitch together a comprehensive answer. With AI-powered tools, like Blue J, you simply ask tax questions conversationally and receive cohesive, source-backed answers in seconds.

Here’s what Blue J’s user data tells us about the efficiency gains of AI-powered tax research:

• 93% of tax practitioners surveyed say Blue J saves them time.

• 2.94 hours/week saved, according to tax practitioners surveyed.

• 75% reduction in research time.

But these efficiency improvements aren’t just from research. 18.8% of respondents to a Blue J user survey say drafting is their primary use for the application, so faster drafting (and faster client response times) is also a major contributing factor.

A Mismatch Between Hourly Billing and AI-Driven Value

AI-driven efficiency adds up quickly, though that can sometimes seem like a double-edged sword. For firms that bill by the hour, every minute saved might also feel like money lost. But productivity and profitability don’t need to be at odds. With the right billing method, your firm can get the best of both.

Time has long been the way tax practitioners determine how much to charge for their work. The longer the task takes, the more billable hours. AI redefines this link between time spent and value delivered. Because the right tax answer is just as valuable whether it takes 10 hours or 10 minutes to produce.

When you’re working with AI, your billing needs to reflect that value—not the time it took to get there.

Exploring New Ways to Charge Clients

The 2024 CPA.com & AICPA PCPS Client Advisory Services (CAS) benchmark survey revealed that firms are already increasingly moving away from pure time and materials billing. Depending on your tax practice and your clients, some alternative billing methods may be a better fit than others. To help you start thinking beyond the billable hour, here are a few options to consider:

Fixed-fee pricing charges a flat fee for pre-defined services, paid on a monthly, quarterly, or annual basis.

• This allows for predictable revenue, assuming you keep scope creep and client complexity at bay.

• It also rewards efficiency, as the faster you deliver, the higher your margins.

Subscription model billing has clients pay a recurring fee at pre-defined intervals (often monthly or quarterly) for ongoing access to a bundle of expert services.

• This approach builds steady cash flow and leaves room to integrate advisory services as part of ongoing work.

• The subscription model requires clear scope and boundaries to prevent over-servicing clients.

Value-based pricing lets firms charge based on the outcome or benefit rather than time spent.

• This approach rewards your firm’s unique expertise, creativity, and judgment.

• Success hinges on a strong framework, frequent client communication, and trust in the fee.

Turning Efficiency Into Opportunity

Aside from adapting your billing for AI, you’ll also need to adapt your work. Firms reclaiming hours previously spent on research and drafting can repurpose that extra bandwidth for offerings further up the value chain. This consultative, relationship-driven work can then be billed at a premium because it relies on judgment, foresight, and highly personalized strategies—all of which require professional expertise and experience.

Pursue more complex advisory and strategic planning

What exactly those advisory and strategic services look like is going to depend a lot on your clients. For some, it might mean taking on a few simple tax strategy planning sessions. For others, it could mean assessing cross-border tax implications, modeling alternative business structures, or even more complex challenges.

What’s the impact? Clients are willing to pay more for strategic services because the work directly influences key business outcomes.

Accounting Today reports in its 2025 Year Ahead survey that firms expect to spend more time on advisory services. However, they also report that there are “elements of friction holding them back.” Time saved through AI-powered tax research could help to eliminate this friction.

Strengthen client relationships

Beyond providing higher-value services, you can also make your existing services feel more premium. Time saved on tax research can be reinvested into higher-touch client service, including quarterly check-ins, mid-year tax planning sessions, and even short educational updates that position your firm as a proactive advisor.

What’s the impact? These moments build trust and differentiate your firm from competitors who are still operating transactionally. They also create natural openings for advisory upsells and cross-service opportunities.

Develop talent and deepen expertise

Busy firms can struggle to find time for staff mentoring and professional growth. When AI efficiency removes the constant time pressure, senior staff have more room to coach junior practitioners and invest in advanced training. AI can also play a direct role in educating juniors, helping them to gain an overall understanding of new tax topics, as well as how to verify tax answers.

What’s the impact? Investing in firm talent leads to stronger recruitment, better retention, faster skill development, and a team that can handle higher-value strategic work.

Seeing the Change in Action at Larson Gross Advisors

The firms that act on these opportunities are already seeing results. Take Larson Gross Advisors for example. This Washington State-based accounting firm replaced its difficult to use (and highly underused) legacy tax research tool with Blue J in hopes of making research easier and improving adoption across the firm. The results are impressive:

• 71% of users are active weekly.

• Each user asks an average of 3.5 questions a day.

• Staff now save about two hours per week while producing faster, clearer, and more client-ready deliverables.

Rather than treating those hours as lost time, the firm has redirected them into strategic advisory work. Staff are now helping clients think through important decisions, model scenarios and tax treatments, and analyze the larger impact of their choices. As Partner and Tax Practice Leader, Tanya Silves, puts it, “We’re there to do life with them.” The shift has also prompted a move toward value-based pricing, which better reflects the speed and quality of their work.

Build a More Profitable Future With AI

When it comes to using AI for tax research, accountants are optimistic. Among those surveyed for Blue J’s Outlook Report, 86.6% agree that AI-powered tax research provides a competitive edge. As for what that competitive advantage looks like, time savings took a top three spot, with 83% seeing this as a key benefit of AI.

The firms set to thrive in the AI era will be those who see this efficiency not as a threat to their revenue, but as the foundation.