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.

But if the conversation ends with, “Let me think about it,” or “I’ll get back to you,” and then… nothing happens, it’s worth thinking about if the conversation was actually effective.

A strong sales conversation creates enough clarity, trust and direction for someone to make a decision. It requires a different kind of communication than most people realize.

Sales Conversations Aren’t Presentations

There’s a tendency in accounting to treat sales conversations like mini presentations. You explain your services, walk through your process, maybe highlight what makes you different, and hope the other person connects the dots.

But that’s not really how most people make decisions.

A strong sales conversation starts with the other person. You have to make a clear effort to understand what’s actually going on in their world, what they’re dealing with and why they’re even considering a change.

That context shapes everything that comes next. It’s what makes a conversation relevant to your audience.

By the time you start talking about your services, the other person should feel like their problem has been articulated more clearly than they’ve been able to explain it themselves. There’s a sense that you understand not just the surface issue, but what’s underneath it, and that creates a different level of attention.

From there, when you do talk about how you can help, it feels connected. Not like a list of offerings, but like a response to something specific that’s already been established.

How You Speak Can Build Trust

Sales conversations often go sideways when they start to feel scripted or overly polished. The more someone sounds like they’re following a process instead of responding to the moment, the harder it is to build real trust.

The strongest conversations feel grounded. There’s room for nuance, for uncertainty where it exists, and for language that actually matches the situation instead of defaulting to generic explanations.

People can feel the difference immediately.

Engagement Isn’t Optional

The accountant talks. The prospect listens. There are a few polite questions, maybe some nodding, and then the conversation ends without much resistance… or commitment.

A strong sales conversation has more movement than that. There’s a back-and-forth that builds over time, where the other person is actively participating, asking questions and reacting to what’s being said.

You have to pull your listener into the process of thinking through their own situation. If you don’t, the conversation stays theoretical. Theoretical conversations rarely lead to decisions.

Decisions Need Direction

One of the biggest gaps in sales conversations is what happens at the end.

There’s often a soft close, something like “Let me know if you have any questions,” or “I’ll follow up,” which leaves the next step undefined and easy to avoid.

In a strong conversation, the ending feels much more intentional. There’s a shared understanding of what happens next, whether that’s moving forward, gathering more information or deciding that it’s not the right fit.

It doesn’t feel forced, but it also doesn’t leave things open-ended. Because without direction, even interested prospects tend to drift.

Did the Sales Conversation Actually Work?

The most effective sales conversations feel like someone understood the situation, helped make sense of it and offered a path forward that felt relevant and doable.

Most people don’t have a way to see whether their sales conversations actually have this shape. They rely on whether someone said yes or no without understanding what happened inside the conversation itself.

Navi, by XcelLabs, changes that by looking at how the conversation unfolded in real time. It can highlight where you stayed too high-level, where you missed an opportunity to understand the prospect more deeply or where the conversation lost momentum before a clear next step was established.

With an understanding of how you communicated across clarity, authenticity, engagement, action and impact, you know whether the conversation “worked.” But also, how and why it did.

Over time, that makes it much easier to recognize the difference between a conversation that feels good and one that actually leads somewhere.

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.

Totally normal question from an almost-26-year-old.

So, I told her to send me her bank statements. Her response?

“Like… from my jobs?”

No, babe… from your BANK. HELLO? CHASE?!

My entire accounting career flashed before my eyes, and NOT just because I was terrified and confused she’s made it this far living like this. (I mean, come on. How do you not know what a bank statement is? How is that even possible?)

But the longer I sat with it, the more I realized this wasn’t just about her — it was about how differently this generation experiences money, and what that means for how we show up as advisors.

A Completely Different Financial World

My daughter lives in a world where money moves instantly. Why would she know?

She’s never had to balance a checkbook, never had to wait for a check to clear, never had to sit down at the end of the month to reconcile what came in and went out. Her entire financial life happens instantly, invisibly, without friction.

She uses Apple Pay. She Venmos her friends. Money moves in real time, and then it disappears into the background of her life without requiring any deliberate interaction or reflection.

There’s no moment she has to check her bank account in the way we were trained to, no system that requires her to engage with the mechanics of money just to function. The closest she comes is opening a banking app on her phone to see all her transactions in real-time.

So when I asked for a bank statement, I was asking her to step into a system she’s never actually needed to understand.

Money is No Longer Learned Through Friction

Most of us didn’t learn financial literacy because someone sat us down and explained it. We learned it because we had to.

We tracked balances so we didn’t overdraft. We paid attention to timing because transactions didn’t clear instantly. We built habits around checking and reconciling because there were consequences if we didn’t.

That friction created awareness, but that system doesn’t exist anymore.

When you remove friction, you also remove the moments where people naturally learn how money actually works.

If I’m being honest, I’m part of the problem too. I’ve always taken care of it for her. I’ve handled the details, answered the questions, made sure everything was fine without ever really pulling back the curtain and showing her how it all works.

If she was my client, it would’ve been different. I would’ve spent more time making sure she actually understood her financial world.

This Is A Shift The Profession Can’t Ignore

The next generation of clients doesn’t experience money the way we do, which means they’re not going to intuitively understand the frameworks we’ve relied on for decades.

If we keep expecting people to understand money the way we were taught, without adjusting how we teach, structure, and communicate it now, we’re going to keep running into the same confusion — not because clients aren’t capable, but because the system we’re asking them to use doesn’t match the way they actually live.

This Is Where Better Advisory Begins

It’s not about explaining what a bank statement is. It’s about recognizing that your clients need someone who can translate their real-life behavior into a system that actually makes sense to them.

That might mean walking them through how their money flows, simplifying what you ask for, or changing how you ask for it. It might mean building processes that don’t rely on them knowing things they were never taught.

We have to slow down enough to meet our clients where they are, instead of expecting them to catch up.

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.

You just got off a call, and the transcript is uploading to Navi. You think, “That was fine… Maybe a 6 out of 10?”

And the score comes back 8.4, and you say to yourself, “Time to delete my Navi account because I’m an advisory god!”

Or worse. It’s only a 3.2, which makes you think, “Ouch. I thought robots were supposed to be friendly.”

Suddenly, you’re not just reviewing a conversation. You’re trying to reconcile two different versions of reality.

Don’t React, Get Curious

Navi’s a tool for you. It’s not judging you. It’s not a manager breathing down your neck, waiting for a reason to replace you.

Take a breath, don’t let a robot get you down. But don’t explain it away either.

The mismatch in scores isn’t a problem; it’s the opportunity.

When your self-assessment and the data don’t align, the goal isn’t to decide who’s right. The goal is to understand why they’re different.

Step 1: Identify the Type of Gap

Before you do anything else, figure out if you rated yourself higher or lower than the data. Those are two completely different growth paths.

If you rated yourself lower, you’re likely dealing with a confidence gap.

If you rated yourself higher, you’re likely dealing with a visibility gap.

Both matter. Neither one means you should toss your laptop out the window and call it a day.

If you rated yourself lower: validate what’s working

This is where most people move too quickly. You assumed you needed to improve, but the data is telling you something else. Time to pat yourself on the back and move on, right?

Nope! You’re doing things well that you’re not noticing. If you don’t know your strengths, how can you play to them?

Instead of brushing past it, ask Navi:

• Where did I show strong clarity in this call?

• What moments landed well with the client?

• What did I do that contributed to this higher score?

This isn’t about boosting your ego. (Although there’s no shame in feeling proud!)

It’s more about pattern recognition. If you don’t understand what’s working, you can’t repeat it.

If you rated yourself higher: find out what you missed

This is the harder outcome, and the more important one. Now you’re looking for what you didn’t see.

Ask Navi:

• Where did I lose the client’s engagement?

• Were there moments where I didn’t answer the question directly?

• Did I clearly define next steps?

• What specifically lowered my score in this dimension?

You’re not looking for a general answer. You’re looking for specific moments.

Growth doesn’t come from “Do better next time.” It comes from, “Right there, that’s the moment where I can make a different choice.”

Step 2: Isolate One Shift

Most people overcorrect. They see the gap and think, “I need to fix everything.”

You don’t!

Pick one dimension, one behavior, one adjustment.

Maybe it’s:

• Asking one more check-in question

• Slowing down your explanation

• Being more direct with next steps

Then, go into your next call looking for that one thing. That’s how you’ll actually be able to build your skills and improve over time.

Step 3: Use Navi Like a Coach, Not a Report Card

If you’re just looking at your score, you’re missing the point. Navi isn’t there to grade you; it’s there to guide you.

Navi’s equipped to answer your questions and help you better understand how you show up in calls. So, treat it like a conversation.

• What would you have done differently in this moment?

• How could I have made this clearer?

• What’s one way I could improve this engagement next time?

The more specific your questions, the more useful the feedback becomes.

This is What Real Self-Awareness Looks Like

The goal isn’t to be perfectly aligned with your score. It’s just to get closer over time.

You’ll start to understand your patterns, recognize your strengths and see your blind spots before they become habits.

The best advisors aren’t the ones who always perform perfectly. They’re the ones who know how to learn from how they perform.

When you combine your self-awareness with real data, improvement stops being a guessing game and starts becoming a system.

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.

(Don’t worry, you all know I LOVE an event. But we have to think bigger!)

Most of us go to a training or attend a conference to check the CPE box. Then we all go back to work and… nothing really changes.

We’ve normalized a model where learning is episodic and disconnected from our actual work. It’s largely focused on technical updates instead of real skill development.

That model is broken.

Not just because of new technologies and AI. Not just because accountants really should focus more on learning about advisory.

But because of people, specifically, the next generation entering the profession.

Gen Z Isn’t Interested in “Check-the-Box” Development

Gen Z professionals are coming into accounting with a very different expectation: they don’t just want jobs, they want growth.

They understand the profession is changing rapidly and they need to keep up. They’re not counting down the days until they retire from the role they’ve held for 20 years with a long-time boss who still thinks Excel is new-age technology.

They know that they need to differentiate themselves to stay relevant, and that requires skills that have nothing to do with the CPA exam.

Gen Z expects:

• Continuous feedback, not annual reviews

• Development that’s personalized, not one-size-fits-all

• Real skill-building, not just compliance training

• Clarity on how they’re improving over time.

And they’re used to this in every other part of their lives. They grew up with platforms that give instant feedback, track progress and adapt to how they learn.

Then they enter accounting and get… a webinar and a PDF.

The gap is going to become a real problem for firms that are trying to attract and retain talent. The next generation isn’t going to stay in environments where growth feels slow, invisible or disconnected from their day-to-day work.

The Problem with Traditional Professional Development

We’re all used to annual reviews, quarterly trainings and occasional coaching conversations. Even when firms invest in development, it’s often too infrequent to drive real change, too generic to be meaningful and too removed from actual client work.

Most importantly, it lacks feedback loops.

Professionals are expected to improve, but they’re rarely given consistent insight into how they’re actually performing in real situations, especially when it comes to communication, advisory and leadership.

So, growth becomes slow, uneven and largely self-directed.

What Changes With AI Coaching

This is where Navi can start to shift the model in a meaningful way. Instead of treating development as something that happens outside of work, Navi embeds itself into day-to-day responsibilities.

When you upload your client calls and team meetings into Navi, it shows the ways you communicated well and the areas where you still need improvement. You can ask follow-up questions so you can get direct, actionable steps that will help you change your behavior.

Navi introduces the idea of continuous coaching. Instead of receiving feedback once a year, professionals can get consistent feedback based on how they actually communicate and interact with clients.

You don’t have to wait for feedback; you can reflect and adjust in real time. And Navi tracks progress too, so you can actually see how you’re improving over time.

Why This Matters More Than We Think

Most accounting firms have built their development models around technical competence and operational stability. But Gen Z isn’t looking for stability, they’re looking for growth.

Gen Z wants to:

• Become better communicators

• Feel confident leading conversations

• Understand how they’re perceived

• Improve intentionally over time

And they expect their workplace to support that. This is where AI coaching becomes more than a “nice to have.” It becomes a bridge between where the profession is and where the next generation expects it to be.

The Future CPA Firm

The future CPA firm won’t just invest in better technology for client work. It will invest in better systems for developing its people.

Because in a world where technical work is increasingly automated, the differentiator isn’t just what your firm does. It’s how your people think, communicate, and lead.

Those are skills that don’t develop through annual training programs; they come from continuous feedback, reflection and practice.

It’s 11:00 PM on January 28th, and you’re emailing a graphic designer from eight months ago to ask for their W-9. The designer probably won’t respond tonight. The deadline is in three days.

January is a self-inflicted wound. And the honest question is - why do we keep doing it to ourselves?

If this has just been your experience, there’s no need to twist the knife by over-explaining or over-exploring why it happened. You’re probably acutely aware of the cracks in the cycle:

• You pay contractors throughout the year. If you didn’t collect W-9s at the point of first payment, you were chasing it in January.

• If you don’t track payments centrally, you were reconciling across multiple platforms in January.

• If you haven’t built a recurring payment workflow, you were processing all year manually and had a mess to sort out in January.

And it’s only going to get more complicated. As businesses take on more contractors across borders, international payments enter the mix too.

You wouldn’t let a client run their books this way. You’d build them a process. So why are contractor payments still being run on good intentions and email chains?

Fix the workflow, fix January.

For many firms, the reason it stays unfixed isn’t simple inertia. There’s also tool fatigue.

Many firms have already tried to fix this once or twice, implementing a tool that solved one piece of the problem while leaving the rest untouched. W-9 collection improves, but payments stay scattered. Payments are centralized, but 1099 filing remains manual.

After investing time in partial fixes without solving the whole picture, the appetite to try again is understandably low.

But the reason those earlier fixes didn’t hold is because they weren’t really fixes at all. They were band aids on symptoms rather than a cure for the whole workflow.

The solution is to consolidate contractor management into the same platform where payments already run. When that’s in place:

• W-9 collection is triggered automatically at the point of first payment. The request goes out, reminders follow if a form isn’t returned, and it’s done without anyone having to remember to chase it.

• Every payment is tracked in the same place so contractor spend, payment history and 1099 eligibility are visible throughout the year without reconciling across platforms in January.

• By the time filing comes around, the work is already done. Because everything was captured as it happened, there’s nothing to pull together at the deadline. It was never scattered in the first place.

That’s it. Start the relationship right, keep everything in one place, and January stops being a crisis.

Once the headache is gone, the advisory opportunity opens up.

If you’re managing contractor payments for clients in a fragmented way, you’re doing all the work without any of the data benefits. And for many firms, you’re also not making a margin on it.

When the entire contractor workflow runs through one connected system, that changes. You know which clients are approaching 1099 thresholds before they get there. You can see when contractor spend is creeping up in ways that will affect cash flow, and you can spot compliance exposure before it becomes a problem. These aren’t things clients are tracking themselves, and they’re exactly the kind of insights that shift the conversation from “can you file our 1099s“ to “what else should we be thinking about.“

And even if you’re already doing advisory work, contractor payments can still be a messy, manual headache. The data benefits are just a bonus on top of fixing something that’s been annoying you for years.

This is where the pricing conversation changes too. Contractor management and 1099 compliance, packaged as a defined service with its own fee, is a straightforward conversation with clients who already feel the pain. The outcome is clear, and you’re not trying to convince anyone there’s a problem. Price it separately. Don’t let it get buried inside a bookkeeping retainer where the value disappears.

For firms not yet in this space, contractor management is one of the cleaner entry points into CAS. Defined scope, a problem clients feel acutely, and a natural path toward broader work once the foundation is in place.

The time is now.

The January pain fades fast, and that’s exactly how firms end up back in the same position next year.

Don’t wait. The obvious place to start is with clients already paying contractors regularly. The problem already exists, the value is immediate, and the setup is straightforward.

If you want to see how this workflow comes together in practice, check out how Melio handles contractor payments.

That way, you could be starting 2027 free from the cycle of chasing, with a January that runs itself and a CAS service line that didn’t exist this time last year. Wouldn’t that be something?

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.

But transformation in a profession rarely starts with technology; it starts with human development.

When our team has conversations about where accounting is headed — AI, advisory, client experience — we keep coming back to a framework that has nothing to do with accounting at all: Maslow’s Hierarchy of Needs.

Maslow’s model describes how human growth happens in stages. At the bottom of the pyramid are the basic needs for survival and stability. At the top is self actualization. That’s the idea that people reach their full potential by continually learning, reflecting, and improving.

When you apply Maslow’s hierarchy to the accounting profession, it becomes clear that most firms and most professionals are still operating in the lower levels of the pyramid. The next phase of the profession isn’t just about new tools or new services. It’s about helping accountants move further up the pyramid.

The Base of the Pyramid: Survival in Compliance

The bottom of Maslow’s hierarchy focuses on survival. For humans, that means food, shelter and basic security. In accounting, the equivalent has always been technical competence.

At the beginning of our careers, the focus is on learning the rules. We need to understand the mechanics of the profession, like tax law and audit procedures, well enough to survive in it.

For decades, the profession has built its identity around this level of the pyramid. Passing the CPA exam, mastering complex regulations and producing technically accurate work became the markers of professional success.

And to be clear, this foundation matters. Without technical competence, the rest of the pyramid doesn’t exist.

But surviving the profession and growing within it are two very different things.

Stability and Security: Building the Modern Firm

The second layer of Maslow’s hierarchy is safety and stability. Once basic survival needs are met, humans begin seeking structure, predictability and security.

In accounting firms, this stage shows up in the systems and processes we build to support the work.

This is where the profession has spent the last 20 years. We invested heavily in technology designed to create operational stability:

• cloud accounting platforms

• workflow systems

• document management

• automated tax preparation

These tools made firms more efficient and more scalable. They helped create predictable processes and stable operations.

But while these systems solved many operational problems, they didn’t fundamentally change the role of the accountant. They just made the existing role more efficient.

Maslow would say that’s exactly what we should expect at this stage. When people reach stability, they begin asking a new question:

What comes next?

Belonging: Relationships with Clients

The third level of Maslow’s hierarchy is belonging. Humans naturally seek connection, community and relationships.

In accounting, this stage shows up in our relationships with clients and colleagues.

Many firms talk about being “trusted partners” or “strategic advisors,” but relationships in the profession have often been transactional. Clients bring information, the firm processes it and deliverables go out the door.

Advisory services began to change that dynamic. Instead of simply producing reports, accountants began participating in conversations about strategy, risk, and decision-making.

But advisory work introduces a new challenge. Technical expertise alone is no longer enough. The value shifts toward how professionals communicate and engage with clients, which is less tangible but incredibly important.

Esteem: Becoming a Trusted Advisor

The fourth level of Maslow’s hierarchy is esteem. At this stage, individuals seek respect, confidence and a sense of mastery.

In the accounting profession, this is where the idea of the trusted advisor truly lives.

A trusted advisor does more than deliver accurate work. They guide conversations, help clients understand complex issues and build confidence through clarity and insight.

But most accountants were never trained for this part of the job. This creates a gap in the profession. Firms say they want advisors, but the development systems inside most organizations still focus on technical output rather than interpersonal growth.

Moving up this level of Maslow’s pyramid requires something new in self-awareness.

Professionals need to understand how they show up in conversations, how clients perceive their communication style and how they can improve the way they guide discussions.

That kind of growth requires feedback, reflection and practice.

The Top of the Pyramid: Self-Actualization

At the very top of Maslow’s hierarchy is self-actualization. It’s the process of realizing one’s full potential.

This is where professionals stop thinking only about tasks and begin focusing on continuous personal growth.

In a profession built on lifelong learning, you might assume accountants spend a lot of time here. But in reality, self-actualization requires the ability to see ourselves clearly.

We all have blind spots in how we communicate. We think we are being clear when we actually sound confusing. We believe we are guiding conversations when we are simply reacting to them.

This is why reflection is such a powerful tool for professional development. When people receive insight into how they think, speak and interact with others, they gain the opportunity to grow intentionally.

This is where the newest generation of AI tools may play a role in the profession.

Instead of focusing only on automation or efficiency, tools like Navi are exploring how AI can act as a kind of mirror for professionals. How AI can help them reflect on their communication patterns and identify opportunities for improvement.

The Next Evolution of the CPA

The next generation of tools won’t just make accountants faster. They’ll help accountants become better advisors.

The future CPA won’t just be a technical expert supported by powerful software. They will be a professional who understands how to communicate, guide clients, and continuously improve how they show up in their work.

And if Maslow’s hierarchy teaches us anything, it’s that real professional growth doesn’t happen at the bottom of the pyramid. It happens at the top.

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.

We were mostly talking about how to survive tax season without losing our sanity. The biggest technology debate (for what felt like forever) was about whether firms should move their bookkeeping software off desktop computers and into the cloud.

AI wasn’t on the radar. And honestly, neither was aging. What young professional is ever thinking that much about menopause?

The idea that one day, your experience might make you feel out of place in a fast-moving industry simply doesn’t cross your mind until you’re my age.

I didn’t expect AI to become part of my leadership story, and I definitely didn’t expect menopause to be a part of it. But somehow, both of these forces — one technological, one deeply human — ended up reshaping how I think about leadership, experience and the strange moment we’re living through in the industry right now.

The Career Pivot I Didn’t See Coming

A few years ago, I sold the accounting firm I had spent decades building. Like most founders who finally reach that moment, I assumed it meant I had closed an important chapter of my career. I thought I would take what I had learned and step into something new with a little more control and a little less chaos.

Instead, I walked straight into the most disruptive leadership transition of my life.

I joined two high-velocity tech startups, led by founders young enough to be my kids and operating inside a culture that moves fast.

Suddenly, the rules were completely different. Speed was everything, hustle was currency and wisdom was negotiable.

The Part No One Talks About

At the same time all of this was happening professionally, my body was going through its own transformation. My role was changing, my industry was changing, my energy was changing. And sometimes, usually late at night, I wondered if I was becoming irrelevant.

Which when you think about it, is kind of ironic. I can probably hustle harder now than I ever could before. My kids are grown. My network is expansive. After decades of building businesses, making mistakes, recovering and building again, I have a level of clarity I never could’ve had when I was younger.

I know exactly what not to waste time on. That kind of clarity is its own form of speed, but the startup world doesn’t always see it that way.

A Conversation with AI

Then, one night, something unexpected happened.

I found myself talking ChatGPT, not asking questions so much as thinking out loud, trying to make sense of the patterns I was seeing and the tension I was feeling between experience and speed.

And something clicked.

The thing I had quietly worried might make me obsolete was actually the most valuable thing I had. Because in an AI-driven world, the real advantage isn’t speed. Machines already win that game.

The real advantage is judgement.

It’s pattern recognition built over decades. It’s knowing when something looks innovative but is actually the same problem wearing new clothes. It’s understanding when technology might be accelerating the wrong decision simply because it can.

That realization changed how I think about leadership.

It’s also why I care so deeply about the work we’re doing with Navi. AI doesn’t just need engineers. It needs leaders who understand context, consequence and human decision-making. Leaders who have seen cycles repeat and know that the fastest answer isn’t always the right one.

Experience is the Real Advantage

It’s National Women’s Month, and the theme this year is “Leading the Change: Women Shaping a Sustainable Future.”

But real change doesn’t always come from moving the fastest. Sometimes it comes from the leader who can pause and say, “I’ve seen this before.”

Because in an AI-driven world, experience isn’t outdated. It’s a strategic advantage.

“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

.

If that answer’s never, you’re not alone. But if we’re serious about building advisory-driven firms, that has to change.

In most firms, advisory conversations happen in real time, and once the meeting ends, they disappear into memory. Normally, no one goes back to actually examine how the conversation unfolded.

It’s a missed opportunity!

If accountants want to remain indispensable, we cannot compete on information alone. We compete on our interpretation, strategic advice and the quality of our conversations.

Advisory is the future of the profession, and we need to start treating it like a skill that deserves reflection and refinement.

Go Look For The Blind Spots

You have blind spots, and so does everyone else.

None of us can experience our own communication the way others do. Of course, what you said felt clear to you… Afterall, you’re the one who said it.

You may think you translated a complex tax strategy into something digestible and meaningful. But until you review the conversation, you’re relying on instinct instead of evidence.

Blind spots show up in subtle ways. You might:

• Over-explain the technical details and under-explain the business impact

• Ask questions without actually creating space for them

• Assume the client agrees with you when they’re just being polite

• Default to jargon instead of using everyday language

• Interrupt because you’re trying to be efficient

• Answer the question asked, but ignore the real concern behind it

These things are almost impossible to process on your own, especially in the moment. That’s why Navi changes the game.

Navi Makes Advisory Performance Visible and Trainable

Navi allows you to upload transcripts of client conversations and it analyzes them across six advisory metrics:

• clarity

• authenticity

• engagement

• action

• impact

• growth

Instead of relying on how a meeting felt, you receive feedback tied directly to what was actually said.

You can see whether you clearly connected technical recommendations to business outcomes. You can hear where you defaulted to explanation instead of strategy. You can notice where you rushed to fill silence.

Even more powerful, Navi allows you to complete a self-assessment before reviewing the analysis. You rate how you think the meeting went, then compare it to the feedback.

That comparison is where growth happens because the gap between perception and performance is where the blind spots live.

When you start to notice your own patterns, you can shift communication from something that “just happens” to a real skill that you can intentionally improve upon.

Technical Accuracy Is the Baseline, Not the Differentiator

Most CPAs are exceptionally well-trained in technical accuracy. We’re taught to research, verify, document and defend. But advisory requires something more.

Advisory is about translating complexity into language that both your adult children and elderly parents could understand. Clients don’t want to understand tax law; they want to hear about what it means for them.

When you review your own conversations, you begin to hear the difference between delivering information and providing actual insight.

Then, advisory stops being an instinct some people “just have,” and becomes a skill that you and your entire firm can deliberately strengthen over time.