Timesheets are more of a reconstruction… a story told after the fact by busy professionals trying to remember what happened in a day already packed with interruptions, client demands, internal coordination and deep work squeezed into the margins.

And that’s the core problem. Firms are not making decisions on objective operational data; they’re making decisions on incomplete, self-reported data, and then acting as though it’s precise.

The Data Speaks Volumes…of Truth

Leaders are making decisions based on bad data, and the result is that pricing, utilization, staffing and performance conversations are all built on a shaky foundation.

In fact, in the Laurel State of Work Report, about 30% of work time goes unsubmitted, which equates to about three hours per day. On average, professionals work 55 hours but only submit 39.5.

In other words, the average timesheet does not document the full workday. It documents the part someone remembers, enters and decides is worth reporting.

That distinction matters more than most firms want to admit. Timesheets do not measure work; they measure memory, judgment, bias, and sometimes, self-protection. In some cases, timesheets are more about:

• What story do I want to tell today?

• I worked long hours…I’m awesome!

• I worked less hours and accomplished just as much…I’m awesome!

This is not a character flaw, but a structural flaw in the system itself.​

Memory is the Worst Strategy

When a measurement system relies on people recalling fragmented work after the fact, the resulting data will always be distorted. Quick email responses between meetings, brief client calls, ad hoc problem solving, review comments and scattered coordination work are exactly the kinds of activities that get lost. Yet those moments are often what keep projects moving, clients reassured and teams functioning.

Utilization isn’t the problem, visibility is.

Firms have spent years debating billable hours, realization and efficiency as though the underlying data were complete. In actuality, manual approaches capture less than three quarters of real, true work activity. That means many firms are optimizing around a subset of reality and calling it management.

The consequences form a ripple effect:

• If hours are underreported, project profitability is skewed

• If invisible work is ignored, staffing models are wrong

• If relationship-building time is minimized because it’s harder to capture cleanly, firms underweight some of the very work clients value most

At the end of the day, when leaders evaluate people using incomplete records, they may end up rewarding the “neatest” submitter rather than the highest-value contributor.

Getting to the Truth

What makes this moment different is that firms no longer have to accept the fog. The future is one where leaders can move from instinct and lagging reports to visibility-backed decisions.

Instead of waiting weeks or months for manually assembled reports, they can begin to see patterns in real time, like hidden write-offs, mismatched staffing, unreleased time and work happening outside the assumptions built into the traditional firm model.

That shift changes the conversation.

Once firms can see actual work, they can ask better questions:

• Are people underreporting because they are trying to look efficient?

• Are senior people doing work that should be delegated?

• Are fixed-fee engagements quietly absorbing time that never gets surfaced?

• Are operational decisions being made from the wrong baseline altogether?

This is an argument for more honest accountability. Firms can’t improve what they can’t see, and they can’t price accurately, coach effectively or deploy talent well when the data source itself is compromised.

The real opportunity is more than replacing one tracking method with another. It’s to get to a place of managing the business based on reality instead of reconstruction. Once firms accept that timesheets are fiction dressed up as precision, they can start building pricing, performance and client service strategies on something far more valuable: Truth … with a capital T!

The other day, my daughter texted me what I thought was a simple question about retirement planning.

As a tax professional, I did what came naturally: I launched into an explanation. I answered the technical question she asked, explained how Roth IRAs work and felt pretty confident I’d covered it.

She replied with one emoji.

🫠

It’s the one that looks like a melting smiley face.

If you know, you know. And I did not. She said it basically translates to, “My brain has melted.”

It made me laugh, but it also made me stop and think.

I’d answered her question accurately, but I hadn’t answered the question she was really asking.

As accountants, we’re trained to explain how things work. We know the legislation, the thresholds, the rules, and the tax implications. So, when someone asks us a technical question, our instinct is usually to explain the mechanics. But our clients aren’t approaching those conversations the way we are.

To us, retirement planning is a financial product. To them, it’s wrapped up in questions like, Am I already too far behind? Am I doing enough? What if I get this wrong? Will I ever actually be able to require?

Those aren’t technical questions. They’re emotional ones.

And if we answer an emotional question with a technical explanation, we shouldn’t be surprised when the response is a melting smiley face emoji.

Instead of leading with “Here’s how pensions work,” try leading with “You’re not behind just because you’re thinking about this now.”

Instead of listing contribution allowances, start by reassuring them that retirement planning isn’t about making one perfect decision today. It’s about taking the next sensible step.

Instead of explaining every investment option available, ask them what they’re hoping retirement actually looks like. Do they want to stop working completely? Reduce their hours? Travel? Spend more time with family? That conversation tells you far more than jumping straight into the mechanics ever will.

Of course, the technical advice still matters. But people are much more likely to absorb it once you’ve addressed the worry sitting underneath their question.

If we jump straight into explaining the rules, we’ve skipped the most important part of the conversation.

The accounting profession is filled with opportunity. Clients are asking for more guidance. Firms want to grow advisory services. And AI is automating parts of the work that used to take hours, creating more room for higher-value conversations with clients. That’s exciting!

But inside many firms, it’s the same people who keep leading the hardest client conversations. The same managers who keep reviewing the work. The same partners who keep building the relationships that drive growth. Firms can operate like that for a while. Until one day, they can’t.

If this sounds familiar, it’s time to invest in the next generation of professionals who can turn everyday conversations into revenue. Automation is part of the equation, but continuously improving the conversations that create value is the other.

AI Changed the Learning Model

For a long time, accounting developed people through proximity and repetition. You sat near experienced professionals. You listened in on client calls. You absorbed how strong professionals thought, communicated and made decisions. You were also doing the work yourself. Drafting, researching and revising, over and over again. That combination built professional judgment.

It wasn’t a formal leadership program. It simply took time. Your professionals learned the technical work first and built confidence through repetition. Only later were they expected to lead advisory conversations. Unfortunately, we don’t have that runway anymore.

The analysis and research that once filled the early years of a career are increasingly automated. The repetitive tasks are disappearing, and those reps were how professionals learned to recognize patterns, ask better questions and understand what clients actually needed.

So, what do we do now?

We use the tools in front of us. AI can continue to summarize, draft, organize and analyze. In many ways, it can even help speed up foundational knowledge. It gives professionals access to more information and more technical insight in less time.

But faster access to information is not the same as judgment.

Judgment doesn’t improve because someone attends another webinar. It improves one conversation at a time through feedback, reflection and practice. In an AI-first profession, learning has to become continuous instead of occasional.

Because at some point, someone still has to sit across from a worried client and know exactly what to say. Someone still has to interpret the numbers and guide a decision. Someone still has to coach a junior professional through a hard conversation or lead a team through uncertainty.

Those capabilities require human judgment and skill. And as routine work becomes more automated, those human capabilities become more valuable.

That’s why firms are already rethinking how they develop their people. Because if they don’t, they may find themselves with efficient processes and not enough professionals ready to lead the conversations that actually grow the business.

Firms That Grow Will Develop People Differently

Most firms would say they invest in their people. And they do, through annual training events, webinars and the occasional offsite. But that kind of development is disconnected from the actual work. It happens once a year, it isn’t reinforced and there’s rarely a targeted way to measure whether real advisory capability is improving.

The result is a ceiling. Advisory conversations stay concentrated at the partner level. Team members complete the technical work but do not move the conversation forward. Opportunities go unaddressed because the team is not prepared to act on them. Growth becomes dependent on a small group of people. And that just doesn’t scale.

You need to break that pattern. It’s time to build development into the daily flow of work, to create earlier exposure to client conversations and to provide feedback on communication while it is happening. Don’t think of this as annual training. It’s continuous conversation improvement. Every client meeting, pricing discussion, coaching conversation and difficult phone call becomes an opportunity to help professionals get a little better than they were yesterday.

You will need to build this skillset intentionally to get to stronger client relationships and expanded advisory capacity across the organization. Make sure your professionals are ready to lead when the time comes.

Where Navi Fits

This is exactly what Navi was built for. And it’s worth being clear about what makes it different from every other tool in the stack.

Navi isn’t a workflow tool. It doesn’t automate tasks or speed up compliance work. It grows the professional. Specifically, Navi creates a continuous conversation improvement loop. It analyzes real client conversations, identifies coaching opportunities, highlights strengths, surfaces missed opportunities and helps professionals improve before the next conversation, not six months later during an annual review. That is the kind of skill development that most technology doesn’t touch at all.

With Navi, you and your team members can get specific, timely feedback on real conversations rather than waiting for an annual review. Coaching becomes something the whole organization can access. Skill progression becomes visible, measurable and actionable over time.

None of that replaces the experienced professionals in your firm. Their judgment still matters enormously. Navi just helps you scale what they bring to the table so more people can develop faster.

The Business Decision

Every firm is making a choice right now, whether they realize it or not. They are choosing what kind of organization they want to build in the AI era.

AI can help firms identify opportunities, but opportunity only creates value when someone knows how to have the conversation. That’s why firms need to build systems that continuously improve the conversations that drive revenue, relationships and the people who create both.

In the AI era, people aren’t just part of the strategy. They are the strategy.

We’ll write the email. We’ll summarize the meeting. We’ll spot the opportunity. We’ll draft the proposal. We’ll tell you what to say next.

There’s nothing inherently wrong with that. In fact, lots of firms’ day-to-day tasks can and should be automated. AI tools can save time, reduce repetitive work, and make it easier to spot things that might otherwise be missed.

But we can’t be afraid to pause and ask an important question:

Are these tools actually making accountants better?

AI Should Make Us Better, Not More Dependent

There’s a fundamental difference between helping someone complete a task and helping them build a skill. One creates efficiency in the moment, but the other creates confidence that lasts long after the software is closed.

Take client conversations. Today, AI can analyze meeting transcripts and surface opportunities that were missed during the call.

While we’re focused on other aspects of the conversations, our AI notetaker might flag that a client offhandedly mentioned cashflow issues or that a business owner said they’re thinking about selling in the next few years.

That’s valuable because it helps us identify opportunities for advisory work. But by the end of it, the accountant still can’t recognize those signals in an in-person conversation.

The software has found the opportunity and the person hasn’t learned anything. Next week, they’ll probably miss it again.

Efficiency Isn’t the Same as Capability

Even worse, AI allows people to stop practicing the very skills that created the opportunities AI flagged in the first place.

An accountant might intuitively ask thoughtful follow-up questions that encourage a client to open up, without ever realizing that’s what made the conversation so valuable. If they start relying on AI to spot opportunities instead of staying curious themselves, those conversations may become shallower, and eventually, there may be fewer opportunities for AI to find at all.

The challenge with much of today’s AI landscape is that it focuses on replacing judgment instead of developing it.

What If Every Recommendation Became a Lesson?

Imagine if every recommendation became a lesson instead of simply an answer. Instead of saying, “This client may need bookkeeping support,” the software could explain why that sentence was significant. What words indicated uncertainty? Why is that often a buying signal? What follow-up questions could’ve uncovered more? How could the conversation have naturally progressed from that moment?

Over time, the accountant wouldn’t just have a growing list of opportunities. They’d have a growing understanding of how to identify those opportunities themselves. That’s a very different outcome.

Accounting has never been about perfectly completing a checklist. The value has always come from interpreting what clients are really saying, asking thoughtful questions and knowing when to explore something further. Those are learned skills and they don’t develop when AI just gives you the right answer.

The same principle applies across the profession:

• If AI writers every difficult email, when do we become better communicators?

• If AI decides every next step in a client relationship, when do we become better advisors?

• If AI identifies every commercial opportunity after the meeting has ended, when do we learn to recognize those moments while we’re actually sitting across the table?

Are We Automating Away the Skills We Need?

The most exciting future for AI in accounting isn’t one where software quietly handles more and more of the profession while we become passive operators. It’s one where AI acts like a coach sitting beside us, helping us understand why something matters instead of simply telling us that it matters.

The best technology doesn’t just make today’s work easier. It leaves you more capable tomorrow than you were yesterday.

Mid-year has a way of making firm owners look up. The extension rush is behind you, the inbox has finally thinned out, and for the first time since January you’ve got six months of real data to work with instead of a hunch. The patterns that were invisible back then are obvious now: which clients are slow to pay, which payables keep slipping through the cracks, where your team’s time actually goes versus where you wish it went.

When that moment prompts the harder question: is our infrastructure actually working for us, or have we just gotten used to it? AP is usually where the answer gets uncomfortable. Because the honest answer, in July just like it was in January, is usually: it’s fine.

“Fine” is quietly killing your margins.

It’s the revenue you’re leaving on the table because your services aren’t packaged the way you’d like them to be. It’s the advisory work you can see clearly but that never actually gets off the ground.

It’s also a time thief. It has a way of following you home and setting up shop in the hours you never planned to be working.

When it comes to AP specifically, “fine” can be a genuinely chronic pain. It’s manual, it’s messy, and it’s usually the last thing on the list firms get around to fixing.

Classic “if it ain’t broke, don’t fix it.”

Except not broken and actually serving you are two very different things. Six months into the year is exactly when that gap starts to show.

Teams put up with fragmented apps, or work around a platform that’s outgrown its usefulness, because the pain never quite crosses the line that forces a decision. That tolerance still has a cost, though. It just doesn’t always show up somewhere obvious. By mid-year, you’re staring at half a year of numbers, and it gets a lot easier to see how much it’s actually added up to.

A clunky AP process isn’t only an operational headache. It’s a CAS opportunity sitting on the table, untapped.

For a lot of firms, the right platform is the difference between that opportunity staying theoretical and actually turning into something the firm can deliver in the second half of the year.

A better AP platform opens doors that wouldn’t otherwise exist:

• Packaging AP oversight as its own offering, with real pricing attached

• Advising clients on cash flow and payment timing to manage vendor relationships and head off cash crunches

• Helping clients put business credit cards to strategic use, earning rewards, stretching liquidity, and turning ordinary expenses into a financing tool

• Moving away from hourly billing toward value-based pricing that reflects what’s actually being delivered

So if the mid-year view makes the problem obvious, why aren’t more firm owners switching?

Because “functional” feels like the safe choice. Researching, evaluating, and migrating sounds like a lot of effort when the current setup is getting the job done, even if imperfectly.

There’s the sunk cost of a platform you’ve already paid for, the comfort of sticking with the industry standard, and the pull to accommodate clients who use different platforms because it feels more service-minded. Nobody wants to become the cautionary tale of a rollout that dragged on too long and burned through too much goodwill, especially with half the year already gone.

But when your infrastructure bends to individual client preferences instead of running on firm-wide standards, consistency takes the hit. Service that feels personal because it’s flexible ends up being much harder to deliver well once you try to scale it.

Most of the time, the barrier is perception, not reality.

A few things are worth checking for specifically when you’re evaluating platforms:

• Can you see every client’s payables from one screen, without bouncing between accounts?

• Are approval workflows and role-based permissions configurable per client?

• Does it sync cleanly with the accounting software you already run, without creating a second reconciliation job?

• Does the fee structure get better as your client base grows, instead of working against you?

None of that is an unreasonable ask. Platforms purpose-built for accounting firms, Melio included, treat it as table stakes. Centralized oversight across clients, AI-powered bill capture, direct sync with QuickBooks and Xero, and onboarding support that walks firms through setup rather than leaving them to figure it out solo.

The economics often look different than firms expect, too. Melio doesn’t charge the firm a subscription fee regardless of client volume, and Accountant Partner Program discounts start at 30% and climb to 45% as the client base grows. The cost structure gets better with scale instead of tighter.

CPA Business Advisors switched for exactly this reason. They now manage payments for up to 300 clients and estimate $40,000 in annual savings versus their old bill pay setup. In Bruce Robertson’s words, the firm’s Head of Growth and Development: “The fee structure of Melio is far more beneficial for our needs and client needs than that of the competitors on the market.”

Done right, the switch pays for itself, and the second half of the year is the cheapest time to find out.

Bringing all your AP systems under one roof does more than solve a headache.

When every client sits on one platform with shared visibility and consistent workflows, the work that once felt too scattered to package into a CAS offering finally has real structure behind it.

And as a bonus, your team gets capacity back for advisory work, because senior staff aren’t spending their day bouncing between systems they didn’t choose, doing manual work that resists standardizing or delegating.

That effect ripples across the whole firm. Efficiency, scalability, fee structure, team cohesion: they’re not separate problems with separate fixes. They’re all symptoms of one underlying question. Is the infrastructure you’re running on actually built for the firm you’re trying to become?

Most firm owners already know the answer, especially with six months of evidence behind them now. The hesitation is rarely about diagnosing the problem. It’s about whether fixing it feels worth the cost compared to just living with it for another six months.

For most firms, a switch that pays for itself within 12 to 18 months is worth making. Firms dealing with real limitations tend to hit break-even much sooner than that, often well before year-end.

“Fine” is rarely a neutral state. It’s a default choice to keep absorbing the cost of infrastructure that almost works. The platform you build on shapes what you can charge, how efficiently your team operates, how confidently you can scale, and ultimately the kind of firm you end up building.

Mid-year is as good a time as any to stop treating that decision as background noise.

We imagine leaders discovering a new tool, getting excited about the possibilities, and deciding to bring it into the business.

But really, most technology purchases don’t begin with excitement. They start with a realization like, “I can’t keep doing this forever. There has to be a better way.”

By the time a leader starts seriously evaluating a new tool, they’ve often been living with the underlying problem for months or even years.

Most Technology Decisions Start with Frustration

Good technology simply gives language to define a problem that already exists. A lot of times, leaders don’t fully understand or articulate a problem until they see something that helps them name it.

Maybe you’ve been frustrated because everyone still comes to you for approval, or you’ve noticed that newer employees need more coaching than your managers have time to provide. Maybe you’re growing quickly, but you’re worried about maintaining the same client experience that helped your firm become successful in the first place.

On the surface, those seem like separate challenges, but sometimes they’re all symptoms of the same underlying issue.

• Suddenly, “everyone keeps copying me on emails,” becomes: “we have too much knowledge concentrated in a few people.”

• “Managers are overwhelmed,” turns into: “our development model isn’t scaling.”

• “We’re growing too fast and something feels off,” becomes: “We’re struggling to create consistency as the firm expands.”

Once you can really articulate the problem, a new conversation about solutions begins.

The Right Solution Starts with the Right Problem

The solution itself almost doesn’t matter. The important thing is understanding what problem you’re actually trying to solve.

The firms that get the most value from new tools are the ones that have done the work to become deeply aware of the challenges holding them back.

Technology just gives leaders a new way to see them.

The good news is that you don’t need a sweeping transformation. You just need to start small. Think of it less like flipping a switch and more like onboarding a new client or system.

Running the experiment in 5 steps

A small experiment solves three problems at once:

1. It keeps risk low because you are not changing everything at once

2. It makes learning real because you are working with actual data, actual deadlines and real client expectations

3. It builds trust because your team can see where AI helps and where it requires tighter rules

Starting with one to five clients is the sweet spot for most firms. Even with a small group, you can start to see repeating issues, recurring wins and the beginnings of a playbook you can standardize.

Running this as a proper experiment also means keeping your existing processes intact.

Most firms feel safer running parallel systems for a while, meaning that your legacy GL and workflows stay live while you spin up an AI‑enabled version of the process for the same five clients and compare results side‑by‑side.

Step 1: Choose 1-5 simple clients on purpose

The experiment begins with picking the right clients. You’re not looking for your most complex, dramatic or high‑risk engagements. You want stable, predictable clients where a new workflow can be tested calmly.

Look for clients who are:

• Operationally stable: Those with a consistent business model

• Data‑reliable: Those with reasonably clean books

• Relationship‑strong: Those who trust you and will be comfortable as part of the experiment

Your mindset: You’re not rolling out AI to the whole firm; you’re running a controlled experiment with clients we know well.

Time commitment: Partners/managers: 1–2 hours to select clients, set guardrails and brief the team. Team: 1–2 hours per week in the first month for workflow changes, vendor sessions and debriefs.

Steps 2 and 3: Map the workflow, then give agents specific jobs

Before AI enters the picture, you have to be crystal clear on how the work gets done today. For each of the five clients, map the end‑to‑end flow start to finish. A monthly close might look like this:

• Pull data from bank feeds and accounting system

• Classify transactions

• Reconcile accounts

• Prepare schedules and workpapers

• Review, adjust and finalize reports

As you map, circle the steps that are highly repeatable, rules‑based and time‑consuming. Those are the pieces you want AI agents to draft under strict governance.

From there, you define agents as “digital staff with job descriptions,” not magic bots. Here are a few examples:

• An agent that classifies routine transactions using firm‑approved rules and history

• An agent that drafts reconciliations for specific accounts

• An agent that assembles standard workpapers from multiple data sources

• An agent that flags anomalies or exceptions that do not fit the usual pattern

Tools like Puzzle make this easier by allowing firms to build agents in minutes with plain English. You decide what the agent can do, what it can propose and where it needs human approval.

Mindset to remember: AI should plug into a process you understand. It cannot fix a process you never documented. Agents are here to handle repeatable steps and not to own the engagement.

Time commitment: 1–2 minutes per agent build (often reusable across similar clients) and 30–60 minutes with your tech partner to validate where agents make the most impact. Add 1–2 hours in the first month to refine rules as you see real behavior.

Steps 4 and 5: Review AI like staff work, then scale only what you trust

Once agents are drafting pieces of the work, your experiment is well underway. One rule, however, is a non‑negotiable. AI can prepare the work, but it cannot post, file or be delivered to a client without human review.

Your team should review AI output the same way they would a junior team member’s work:

• Check accuracy and completeness

• Look for patterns in recurring errors

• Compare time spent reviewing now to the time previously spent preparing from scratch

This review step is where trust is built. Teams see exactly where AI is strong, where it needs clearer instructions and where it should not be used at all.

As you gather experience across the five clients, start writing down what you learn: which tasks agents handle well; where predictable mistakes occur; and which prompts, rules or configurations deliver the best results. From there, tighten your setup: clarify boundaries; add rules for common edge cases; and decide which tasks are ideal for agents, which are shared and which stay fully human for now.

By the end of the experiment, you should be able to identify how much time was saved, if quality improved and if your team is ready to expand to more clients.

Mindset to remember: This isn’t about proving AI is perfect. It’s about finding where AI reliably helps and baking that into how you work.

Time commitment: 1–2 hours per month to review metrics and feedback across the five clients, plus a short internal debrief at the end to decide what to standardize and what to try next.

How this moves you up the AI Adoption Ladder

Decisions around AI adoption take time as firms begin with awareness and move toward being an AI-enabled firm, as shown on the AI Adoption Ladder below. The 5‑Client AI experiment sits on the Experimentation rung of the AI Adoption Ladder but nudges you toward Adoption and Integration.

You’re not talking about AI in theory anymore. You’re using it in live work, with clear guardrails, and learning what’s worth scaling.

I mean the actual experience of being a client, not their opinion of your tax expertise or if they get along with the members of your team that they communicate with the most.

Would they all describe the same communication style? The same responsiveness? The same level of proactive guidance?

Or would it sound like they were working with five different firms?

As firms grow, that’s a question leaders have to consider more and more.

Growth Creates More Versions of Your Firm

When a firm is small, consistency happens naturally. Everyone learns from the same leaders, works alongside the same team members and has a pretty clear understanding of how client relationships should be handled.

Growth changes that.

New managers bring different communication styles. New hires arrive with different experiences and expectations. Acquisitions introduce entirely new ways of serving clients. Before long, people across the organization may be working toward the same goals while approaching them in very different ways.

Some variation is healthy. Different personalities, perspectives and strengths are part of what makes a team effective.

The challenge is figuring out where variation adds value and where it creates confusion.

Clients should be able to trust that they’ll receive the same level of care regardless of who they’re working with.

That kind of consistency comes from creating more shared habits within your team.

Consistency Isn’t Created by a Process Document

A lot of firms assume consistency comes from documenting expectations. “We told people how to communicate.” “We covered that during onboarding.” “We have a written process for that.”

Actual consistency is built through repetition, coaching, observation and reinforcement over time.

That’s why growing firms should regularly ask a few important questions:

• Does every employee know when to escalate a difficult client situation?

• Would every manager coach a team member through the same type of challenge in a similar way?

• Does every client receive the same level of communication?

• Do all of your employees know what great client service actually looks like inside your firm?

If the answer to any of those questions is no, it shows you where growth is creating variation.

Find What Works & Make It Repeatable

You can’t force everyone into the same mold, but you can get more intentional about what matters most in your firm.

What are the behaviors, communication habits and client service standards that define your firm? What do your best managers do that others could learn from? What does a great client interaction actually look like in practice?

Those answers can’t live exclusively inside the heads of your leadership team. They have to be talked about. Modeled. Reinforced. Repeated.

That might mean reviewing client communication together and discussing what worked well. It might mean giving managers more opportunities to share how they handle difficult situations. It might mean creating clearer expectations around responsiveness, escalation or client service.

Most importantly, it means paying attention to the places where your firm is already getting it right.

Every organization has people who consistently build trust, communicate clearly and create great client experiences. The goal isn’t to clone those individuals. It’s to understand what they’re doing and make those behaviors easier for everyone else to learn.

Your Clients Shouldn’t Have to Get Lucky

As your firm grows, you’re going to have more people, more clients and more ways of getting the work done. But growth shouldn’t mean creating more versions of your firm.

The firms that scale successfully will be the ones that figure out what makes their best client relationships work and intentionally teach, coach and reinforce those behaviors across the organization.

Because your clients shouldn’t have to get lucky and work with the right person to have a great experience.

They should know what it means to work with your firm.

AI is getting more capable every day. It can summarize a meeting, flag a risk, analyze a pattern and draft a follow-up before you have finished your coffee. Some accountants look at that and feel nervous. If AI can do all of that, what exactly is left for the professional?

Quite a lot, actually. And it is worth getting specific about what that is.

The firms and professionals who will pull ahead are not the ones who learn to use AI the fastest. They are the ones who understand what clients still need most from a person and use AI to amplify that. When you look honestly at what makes a great accountant, three things come up every time. Judgment. Context. Relationship. AI does not have any of them. But it can make all three stronger.

Judgment: Connecting Facts to Decisions

AI is good at gathering facts. It can pull patterns out of a transcript, flag where a client raised a concern or kept circling back to the same issue and line up options and scenarios. What it cannot do is decide what any of that means for this client, at this moment.

Judgment is the bridge between what we know and what we recommend. Two advisors can look at the same data, the same notes, even the same AI summary, and hold two completely different conversations. The difference is not in the output. It is in how each person reads it, weighs the trade-offs and decides what makes sense for that client.

AI can make that part of your work stronger. It can show you where you spent most of the conversation, where a concern kept resurfacing or where your explanation may not have landed as clearly as you thought. That gives you a better starting point. Then your judgment takes over. You decide what needs to be clarified, what needs to change and what you are willing to stand behind.

That is the part no tool can do for you. It can give you more to work with. It cannot make the call.

Context: Knowing the Story Behind the Numbers

AI sees the conversation in front of it. You see everything that came before and everything at stake after.

You know why the numbers looked the way they did last year and what the client isn’t saying out loud. You know that certain topics are sensitive and which decisions have history behind them. None of that shows up in a summary. But all of it changes what good advice looks like.

AI can tell you what was said. You can tell your client what it means, for them, right now, given everything you know about where they have been and where they are trying to go. And when AI handles the recap efficiently, you have more time and more presence for the part that actually requires you. That is the difference between information-delivery and true advisory.

Relationship: Trust You Have Earned Over Time

You have spent years building client trust. They call you when something feels off. They ask what you would do if this were your business. They lean on you in the hard years and want to celebrate with you in the good ones.

AI cannot recreate that. It has not seen the client through tax seasons, audits, growth and setbacks. It does not remember what you recommended two years ago or how it played out. It cannot say, “We have been here before, and here is what we learned.” It has no skin in the game.

What it can do is help you take better care of the trust that is already there. Tools that capture and analyze conversations can show you where you rushed past something the client cared about or where a call never quite got to a decision. They can help you keep track of promises and follow-ups so fewer things slip through the cracks.

When you bring AI into the trusted advisor relationship, you are still the person they trust. You are simply using better information to show up for them.

AI amplifies the value you already bring to the table.

Your Human Advantage

AI will keep getting better. The real opportunity is to use it in ways that make you stronger and more present for the parts of the work that only you can do.

That is where accounting advisory technology like Navi can help. It makes conversations easier to see after the fact. It shows you where something mattered more than you realized, where a client hesitated or where a decision never quite got nailed down.

Use what you find to show up sharper next time. That is not AI replacing your value. That is AI amplifying it.

The world is constantly changing. There are always new regulations, shifting markets and evolving technologies. It’s exhausting!

Everyone always wants to know what’s next and leadership is expected to provide clarity in the middle of uncertainty. But people don’t actually need leaders to predict the future. It’s more important to be a leader people trust to navigate new experiences alongside them.

We’re living through a period of significant change, and there are two conversations happening at the same time. The first conversation is about strategy, which most professionals have a script for. The second conversation is about fear. And that’s way harder to talk about.

The Conversation Happening in People’s Heads

As leadership teams spend most of their time talking about strategy, most employees spend their time wondering how that big-picture plan will affect them.

People wonder:

• Will my role change?

• Will my skills still matter?

• Am I being prepared for what’s next?

• What does this mean for my future here?

Most people never ask those questions directly. But if organizations fail to address them, they start filling in the blanks themselves.

That’s why communication matters so much during periods of change. People deserve to know that they’re part of the conversation.

You Don’t Need to Have All the Answers

One of the most powerful things a leader can say is: “I don’t know exactly what this will look like yet, but we’re going to figure it out together.”

This kind of honesty creates trust. It gives people confidence that even if the destination isn’t completely clear, they won’t be left behind on the journey.

Ask the Questions No One Else Will

Sometimes, the easiest way to make sure that you’re addressing the questions no one wants to ask is by simply… asking the questions yourself.

Make an effort to create space for your team to approach you with their feedback and concerns. Try to create as many opportunities for conversation as possible. Some people might not feel comfortable raising a concern in a full team meeting, so these topics need to be discussed in one-on-ones too.

Some questions you can ask to get people thinking include:

• What concerns do you have about the changes we’re discussing?

• What parts of your job feel most uncertain right now?

• Where do you feel like you need more support?

• What are you hearing from clients that leadership may not be hearing?

People are much more likely to embrace change when they feel like they’re helping shape it. And in many cases, employees already know where the friction exists. They know which processes are broken, which tasks are frustrating, and where valuable knowledge gets trapped inside a handful of people.

The challenge is creating an environment where people feel safe enough to share what they know.

That means building enough trust that people keep bringing you the hard questions, the uncomfortable feedback, and the concerns that haven’t been voiced yet.

What happens to the value of our work when technology changes how we deliver it?

Today, that question is about AI.

The latest catalyst is the IRS’s new guidance on artificial intelligence. Most of the conversation has focused on compliance. It reminds tax professionals that AI doesn't change our professional responsibility. We still own the judgment, the work product and the advice we give.

I couldn’t agree more. But after reading the guidance, I kept coming back to a different thought. I don’t think the biggest issue it raises is compliance. I think it’s pricing.

Accountants have too often asked themselves: “If AI helps us do the work faster, shouldn’t clients pay less?”

Absolutely not! The fact that we’re asking the question reveals the real problem. We’ve been measuring value by the wrong thing.

Time Was Never the Product

No client has ever hired an accountant to spend eight hours preparing a tax return. They hire us because they want confidence. They want someone who understands their business, protects them from risk and helps them make better decisions. Those outcomes are the product. The hours were simply the way we measured the cost of delivering them.

For decades that measurement made sense because expertise and time were closely connected. The more knowledge you developed, the more efficiently you could solve problems. Ironically, the better you became at your job, the harder it became to justify your fees under an hourly model. AI has accelerated that tension.

A task that once took four hours might now take 40 minutes, but:

• Has the client’s outcome changed?

• Has your responsibility changed?

• Has your judgment become less valuable?

Of course not.

Responsibility Never Left the Professional

The IRS makes it abundantly clear that AI may assist with the work, but the professional remains accountable for the final product. You're still responsible for the judgment, the recommendations and protecting your client's interests. That means you're still creating the value.

AI amplifies your expertise, so why do firms feel obligated to apologize for becoming more efficient? We don’t expect surgeons to reduce their fees because robotic technology improves precision. Or architects to charge less because software produces better drawings in less time. We want professionals to embrace better tools that produce better outcomes.

Accounting shouldn’t be any different.

The Question the IRS Doesn’t Answer

One sentence in the guidance really caught my attention. It reminds practitioners that Circular 230 prohibits charging an “unconscionable fee.” Then it goes a step further.

The IRS says that when AI reduces research and drafting time, practitioners should openly pass those efficiencies on to clients and disclose AI-assisted work as appropriate. In other words, if you’re billing by the hour, the clock still matters, even if AI did much of the heavy lifting.

I understand why the IRS took that position. Under an hourly billing model, charging for time that wasn’t actually spent raises legitimate ethical concerns.

But I think that’s exactly the point.

The guidance isn’t exposing a problem with AI. It’s exposing a problem with hourly billing.

The IRS is telling firms how to bill in an hourly world. It's time to stop living in one.

That’s one of the reasons I’ve advocated for value pricing for years. In fact, I wrote Radical Pricing three years ago because I believed then what I still believe today: clients pay for outcomes, not effort. AI has only validated that belief.

With value pricing, clients aren't buying hours. They're buying confidence, professional judgment and better decisions. Whether that answer came from two hours of manual research, 30 minutes with AI assistance or a combination of both shouldn’t be the primary driver of the fee. That makes value pricing more relevant.

The Real Opportunity Isn’t Efficiency

For years, firms have measured AI by how fast it can complete compliance work. Important, but not the end goal. Capacity is.

When AI gives your team hundreds of hours back, you can produce more compliance work. Or you can spend more time identifying planning opportunities, coaching business owners and strengthening the relationships that lead to referrals, retention and advisory work.

You have answers more readily available. Your new bottleneck is now helping clients understand what the answer means and what they should do next.

Maybe AI Isn’t the Disruption After All

I’ve said for years that firms need to stop selling time and start selling expertise. The IRS guidance makes this more important.

Hourly billing assumes effort equals value. AI proves otherwise. Firms that continue selling hours will find themselves trying to explain why greater efficiency should result in lower fees. While the firms that price outcomes, judgment and relationships will see AI as a better way to deliver more value with greater consistency. That’s progress.

The IRS reminded us that AI doesn’t replace professional judgment. I’d take that one step further. If professional judgment is still what clients value — and still what we’re ethically responsible for — then maybe it’s time our pricing reflected that.

Because clients were never buying our time. They were buying our judgment all along.

For a long time, firms assumed that enough experience would eventually turn good accountants into trusted advisors, manages and leaders. A lot of firms are still training accountants for a version of the profession that no longer exists.

Things Have Changed

The profession has changed, and more importantly, the skills that clients actually value have changed. This means that firms need to become more intentional about how people develop than they were in the past.

You can see this change is already happening in real time. Firm leaders are increasingly centering conversations around questions like:

• How do we help younger employees communicate more confidently?

• How do we develop advisory skills earlier in someone’s career?

• How do we help people exercise good judgment when they haven’t seen every situation before?

• How do we create more opportunities for coaching when managers are already stretched thin?

They’re looking for people who can explain complex issues clearly and anticipate problems before they arise. They want to work with professionals who can ask thoughtful questions, build trust and help them make decisions. Those skills need to be developed.

People Drive Growth

Every firm eventually reaches a point where its ability to grow becomes directly connected to its ability to develop people. You can improve workflows. You can invest in technology. You can acquire new clients. But at some point, growth requires more employees who can communicate effectively, build trust with clients, exercise good judgment and take on greater responsibility.

These skills need to be developed. That might mean investing more heavily in coaching. It might mean giving employees more opportunities to practice communication and advisory conversations. It might mean being more intentional about sharing knowledge that currently lives inside the heads of a few experienced leaders.

Whatever the approach, the firms that win the talent battle will likely be the ones that treat development as a strategic priority instead of a byproduct of experience.

Real growth in your firm relies on developing more people who are capable of serving clients.

That’s because AP isn’t just about processing bills anymore. Once you layer in payment timing, credit card strategy, rewards, approvals and cash flow visibility, bill pay becomes one of the most practical advisory channels inside a business. The conversation shifts from “Did this get paid?” to “What’s the smartest way to pay this?”

And clients will pay for that guidance.

Credit card bill pay is an advisory gateway

When clients pay vendors by card through a tool like Melio, every bill becomes a mini cash flow decision point instead of just another ACH.​

You’re no longer just moving money out the door; you’re helping clients:

• Extend effective terms by putting expenses on a card and riding the statement cycle instead of draining cash on the due date.

• Earn rewards on everyday AP spend since points, miles or cash back can be turned into real value instead of getting wasted at “1 cent per point” redemptions.

• Smooth out big hits to the bank account by pairing card-based payments with fast-pay or pay-over-time options to match cash outflows with inflows.

Credit card bill pay turns a “Did it get paid?” question into “What’s the smartest way to pay this?” That’s advisory.​

From button pressing to cash flow coaching

There is power in rewards advisory, where everyday spending is turned into $36K worth of first-class air travel because someone understood how to earn and redeem strategically.​

And that’s the model you want to follow:

• Teach clients which expenses should be on a card versus paid directly (rent vs. inventory vs. ad spend)

• Map payment timing to identify if cash flow benefits for the payor outweigh credit card processing fees, who needs fast pay to protect relationships, and where to use installments to avoid crunches.

• Use weekly or monthly AP reviews to walk through upcoming bills, card cycles and projected balances so owners can see “runway” instead of just a bank balance​

You’re not just getting bills out the door, but rather you’re coaching clients on how to stretch cash on hand without blowing up vendor trust.​

From cost center to revenue stream is an easy upsell

Once you automate the ugly stuff by applying OCR, inbox routing, approvals and sync, what’s left is high-value conversation time.​

That’s your opening to package AP advisory as its own line item, not a free extra:

• Baseline: AP processing (automation + oversight) at a flat monthly fee

• Upsell: Cash flow and card strategy add-on that includes monthly bill-pay planning, card optimization and points strategy sessions

• Premium: Full-service AP where your team merely presses the button — plus scheduled cash flow check-ins and proactive alerts on upcoming crunches.

This is how you monetize guidance around when and how to pay, not just the keystrokes.​

Be the financial coach

This is where the radical framing comes in. You’re not the person paying bills; you’re the financial coach sitting at the bill pay button with your client.​

In practice, that looks like:

• Positioning AP sessions as “cash strategy huddles,” not check runs. You review open bills, card cycles and cash projections together.​

• Using simple language instead of jargon: “Here’s how we buy you 30 more days of runway” lands better than “We’re optimizing working capital.”​

• Building playbooks by client type, like restaurants, trades or ecommerce, each with specific card and timing strategies you can repeat and scale.​

You become the person who turns bill pay from something they avoid into a weekly conversation they actually look forward to.​

Every bill is a cash flow decision

The traditional view dictates that advisory starts after the books are closed and the reports are pretty. The radical view says advisory starts at the exact moment a client hovers over “pay bill.”​

Every time a bill hits the AP queue, you have a chance to:

• Protect cash by choosing timing and method

• Create value with rewards and financing options.

• Open a deeper conversation about goals, risk and growth.

When you design AP so clients never touch the GL but always have a smart, guided bill pay environment, you’ve built a live advisory channel right where money leaves the business.​

Advisory doesn’t start with a fancy dashboard or a big consulting project. In a radical AP firm, advisory starts at the bill pay button. And that single click is where you modernize, monetize and protect your sanity.

This idea came to me after meeting Ryan Reynolds at AICPA ENGAGE. If you’ve ever been to ENGAGE, you know it’s one of the best places in the profession to hear new ideas, challenge old assumptions and think differently about what’s next. Which, now that I think about it, is a very Deadpool mindset.

While everyone else is following the script, he’s constantly looking around and asking: “Wait… Why are we doing this?”

Everybody in the movie thinks they’re operating inside reality, but Deadpool realizes the rules are all made up.

His real superpower is refusing to accept the world exactly as it is presented. He’d make a terrible tax preparer, but he’s an excellent innovator.

When Familiar Starts Looking Necessary

A lot of accounting “rules” aren’t actual regulations. They’re habits. Someone created them, and we can improve them.

Most firms don’t realize when they’ve started following a script. When you’re living inside a business every day, everything feels normal.

The client onboarding process is normal. Of course, your weekly meeting always feels the same. That’s why it’s called “weekly.” The ten-step approval chain is how it’s always been done. Why wouldn’t we ask Jim every question that comes up? He’s been around for decades.

Nobody wakes up one morning and decides to build an overly complicated process. You just inherit today’s reality from yesterday’s decisions. After a while, it’s hard to tell the difference between something that’s necessary and something that’s simply familiar.

The Best Improvements Happen Outside the System

That’s why I think Deadpool is such a surprisingly good mascot for innovation.

He’s not constantly breaking the rules because he loves chaos. He’s constantly asking whether the rules actually make sense.

That’s a skill a lot of firms need right now. The biggest opportunities for improvement rarely come from working harder inside the system. They come from stepping outside the system long enough to examine it.

The firms building what’s next are willing to look at a process everyone accepts and ask a question nobody else is asking.

Questions Worth Asking

So, channel your inner Deadpool. Step outside your business for five minutes and ask:

• Why do we still do this manually?

• If I were a client, would I enjoy this experience?

• Why does onboarding take so long?

• Why does every email need partner review?

• Why do difficult conversations always get escalated to the same person?

• If we were building this process from scratch today, would it look the same?

• What would break if I disappeared for two weeks?

• Are we solving 2026 problems with 1996 thinking?

The accounting profession needs more people willing to challenge assumptions. The future belongs to the people willing to ask: “What if there’s a better way?”

Yet underneath the hype, most firms aren’t racing ahead. They’re parked in the same place — curious about AI, but not confident enough to let it near work they sign, let alone build a new operating model around it.

Your caution is not the problem to be “fixed.” It’s the professional instinct you need to design around so AI becomes an advantage, not a liability.

Accountability, not technology, is the real barrier

From the outside, it’s easy for tech folks to shrug and say, “The tools are ready; firms just need to get on board.” But inside firms, the questions are different:

• “If an AI system drafts this work and something is wrong, am I still signing?”

• “If the agent misclassifies, miscalculates or misses an edge case, who is actually on the hook?”

• “If AI touches the books, can I still stand behind the engagement the same way?”

In accounting, you don’t get to blame the system. You sign the work, so you own the result regardless of which platform prepared it. That simple fact changes the entire AI conversation.

AI can’t be treated like a trendy gadget or a lab toy. It has to show up as an extension of your professional judgment. As something you’ll monitor, test and govern with the same rigor you apply to any other part of the engagement.

The real risk is AI without oversight

Uncontrolled AI is at the heart of concerns. The issue isn’t that a system can draft a reconciliation, propose a journal entry or categorize transactions. The danger is when those actions happen quietly in the background with no boundaries, no audit trail and no clear review step.

When automations post directly to the GL or push information to clients without human oversight, you quietly drift from “AI‑assisted work” to “AI‑substituted work.” And that’s exactly the scenario that triggers every concern about accountability.

The safer — and smarter — way to think about AI is simple:

• AI prepares the work

• Accountants review, challenge and approve

• Nothing posts or goes out the door without human sign‑off

Puzzle is a good example of an AI-native accounting platform intentionally leaning into this “AI prepares, humans approve” model. Instead of hiding AI in the background, Puzzle brings AI agents to the front of the experience so firms can see exactly what each agent is doing, where it stopped and what requires human review.

When you design your AI for accountants, you get the speed without sacrificing control.

Shifting the mindset from autonomous to AI-led

A lot of AI marketing is built around speed, not accountability. You’ve seen the claims of a fully automated close or hands‑free reconciliations. But for a profession that signs its work, that’s a red flag, not a selling point.

Many tools fall short for firms because they treat governance and controls as an afterthought instead of a core requirement. By contrast, tools that resonate with accountants lead with governed automation accountant-approved workflows, offering clear checkpoints for review and approval.

Considering all of this, it’s truly a mindset shift that needs to occur first — one from autonomous automation to accountant-approved AI. The first takes humans out of the loop, while the latter keeps accountants not only in the loop, but in control.

The AI Adoption Ladder

Adopting AI is not an overnight decision. Successful firms progress at a steady, intentional pace. Consider each rung of the Adoption Ladder:

Intentional adoption is key

AI is real and it’s here. However, firms should not adopt it without an intentional strategy in place.

That strategy starts with setting an important goal: AI does not remove accountants from the process, but rather it changes what they spend their time on. When AI prepares work faster and more consistently, accountants can stay focused on what only they can do, like review, interpret, advise and sign.

Okay, fine, not every email. But enough of them to notice? Do you feel like you’re constantly reviewing responses, tweaking wording, double-checking tone and stepping in before something goes out the door?

If you’re leading a growing firm, I have a feeling you know exactly what I’m talking about.

It’s not a bad thing! At first.

The Problem Isn't the CC

A lot of founders built their firms on strong relationships and high-touch communication. They care deeply about client experience. They know how they want the firm represented. They know how to handle difficult conversations, explain complicated issues clearly and make clients feel taken care of.

So naturally, people keep coming to them. They don’t want to get it wrong and screw up an important client relationship.

At first, it probably even feels good. It means your team trusts you. It means people care about getting things right.

But when your firm starts growing… More clients come in and more employees are hired… And they’re ALL. SENDING. EMAILS.

Suddenly, you’re an editor, a coach, a relationship manager and an emotional support system for half the organization. As if keeping the firm’s lights on wasn’t enough.

It’s exhausting!

Founder Burnout Often Looks Like Responsibility

We don’t talk enough about the emotional labor of that kind of leadership dependency.

From the outside, growth looks exciting. There’s more revenue, more momentum. You have a bigger team and bigger opportunities.

But internally, growth can start to feel like being emotionally responsible for more and more people until it gets to a point where you can barely step away for a bathroom break.

It might seem harmless, but think about it. You’re reviewing client communication late at night. You’re mentally carrying difficult conversations. You’re desperately trying to maintain consistency across a team that’s getting larger and more complex every year.

You can improve workflows and hire managers, but that dependency doesn’t always disappear.

I think this is where a lot of founder burnout quietly starts. It’s not easy to be the person everyone relies on for reassurance, judgment and communication support.

Especially in accounting firms, where so much of the business depends on trust.

We all know that clients don’t just remember whether the work was technically correct. They remember responsiveness, clarity, tone, confidence and how interactions made them feel.

For founders, that creates an invisible pressure to personally protect the quality of every client relationship.

At Some Point, Trust Has to Scale

But eventually, growth forces you to realize that you can’t personally hold every relationship, review every interaction and coach every employee forever.

At some point, scaling a firm becomes less about workflows and more about trust.

• Can your managers lead without constant oversight?

• Can employees communicate confidently on their own?

• Can other people carry the culture and client experience consistently?

And if they can’t, then the question becomes: What do they actually need in order to get there?

• More coaching?

• Clearer communication standards?

• More opportunities to practice difficult conversations?

• More confidence?

• More support from managers who already feel overwhelmed themselves?

Eventually, founder dependency stops being a “people keep CC’ing me” problem and starts becoming a signal that something deeper inside the organization needs attention.

At a certain point, leaders have to stop asking: “How do I keep up with all of this?”

And start asking: “What would need to change for my team to succeed without needing me involved in every step?”

Many founders spend years proving they’re the smartest person in the room. Scaling requires something much harder. Creating a room full of people who no longer need to ask for your approval.

That’s not losing control. That’s leadership working!

It happens every busy season. And for a lot of tax professionals, that cleanup process takes up far more time and mental energy than it should. The return itself is often fairly straightforward. It’s the reconstruction that drains you.

The firms gaining leverage right now are finding a faster path from those bank statements to usable numbers. That means less time buried in cleanup and more time for the work that actually grows the practice. Here’s how they’re doing it.

Why Cleanup Has Gotten Harder

The challenge today goes beyond bookkeeping habits. Small business finances are simply more fragmented than they used to be. A decade ago, most clients had a checking account and a credit card. Today, revenue might flow through Stripe, PayPal, Shopify, Square and Venmo. Expenses run through several cards, subscriptions, apps and payment platforms. Even a client with a few hundred thousand dollars in revenue can generate a surprising amount of transaction activity across a surprising number of sources.

That means you’re not just getting one bank statement anymore. You’re getting a stack of them, plus credit card exports, plus whatever else they managed to pull together before the deadline. Someone still has to work through all of it, figure out what’s income, what’s an owner’s draw, what’s a transfer and what belongs in each expense category. And all of that happens before the return even starts.

This is the bottleneck. And it’s exactly where there’s an opportunity to work differently.

What a Better Workflow Looks Like

The firms handling this best are not eliminating the cleanup process entirely. They’re just getting through it faster.

Instead of starting from zero and manually coding everything line by line, they’re finding ways to organize the activity quickly and generate a first-pass P&L so they can get into the actual accounting and tax work sooner.

That changes how busy season feels. Instead of spending hours building the first draft, your team can spend more time reviewing the numbers, correcting exceptions and advising clients.

That’s a much better use of talent than manually sorting transactions all day.

Where AI Can Help

This is exactly where AI can help. A lot of cleanup work is repetitive. The same transaction patterns tend to show up over and over again. That’s exactly the kind of pattern-recognition work AI is built for.

That becomes especially useful when you’re dealing with:

• Clients who only provide bank statements

• Catch-up bookkeeping tied to a return deadline

• Quarterly estimate work requiring current numbers

• Smaller clients who don’t have monthly bookkeeping support

• Last-minute engagements where there’s no time to start from zero

So, what does a faster cleanup process actually look like?

Platforms like Adam by Tyms are designed to help firms shorten the path from bank statements to a usable starting point for tax prep. You upload bank statements or transaction exports and it generates a draft P&L in minutes. Firms can also manage multiple clients and team workflows from a centralized dashboard, making it easier to scale this process across engagements.

Instead of manually building the books from scratch, you can start with organized numbers and focus your time on the actual accounting and tax work. There will always be transactions that need your eyes for a second look. But even reducing part of the reconstruction process can create meaningful time savings during busy season.

Curious? See Adam in action here.

The Opportunity for Firms

What would you do with more capacity during busy season?

For smaller firms and lean teams, reducing even part of the cleanup process can make a real difference. Less time spent organizing transactions means more room to take on additional work and fewer situations where a relatively simple return turns into hours of unpaid cleanup.

It also changes how experienced professionals spend their time. Instead of sorting transactions and cleaning up books all day, they can spend more time reviewing issues, answering client questions and helping businesses think ahead before filing deadlines hit.

And honestly, that’s where a lot of firms want to go. More planning conversations. More advisory work. More opportunities to strengthen the client relationship instead of simply organizing records.

Try It for Yourself

If cleanup work is eating into too much of your busy season, Adam by Tyms is worth a look. It’s a new solution that is still evolving, and it’s designed for exactly the kind of reconstruction work tax professionals already deal with every year. And generating a quick P&L is just one part of what the platform can do.

Schedule a demo to see how firms are using Adam to reduce cleanup work and move from bank statements to usable numbers faster.

Thanks to my XcelLabs sponsor

Adam by Tyms is a complete practice management software and AI bookkeeping platform for accounting firms — white-labeled under your brand, with your pricing, your clients and your margin. Learn more about how you can get smarter numbers with effortless control.

People are constantly saying things like:

• I asked ChatGPT…

• My AI assistant reminded me…

• Claude helped me think through…

• It’s like having a tutor…

• I talk to it when I’m anxious…

• It’s my brainstorming partner…

Culturally, people are treating AI differently from other technologies that have come before it.

I’ve never heard anyone say, “Excel helped me process my feelings,” or “QuickBooks gave me confidence before a difficult meeting.”

When people evaluate an AI tool, they’re starting to compare it to coaches, mentors and administrative assistants. No one’s comparing the robot that answers all their questions to tax software or traditional productivity tools.

That’s a completely new kind of conversation.

From Automation to Development

For years, most accounting tech conversations focused on operations. But lately, some of the most interesting use cases seem to be moving away from pure efficiency and toward something much more human.

Firm leaders are talking more about communication quality, employee development and consistency across teams.

Some firms are starting to think about AI as something that can support human development inside the firm itself.

The firms most seriously exploring these tools often aren’t just asking: “What can this automate?”

They’re asking:

• Can this help our people learn faster?

• Can this help newer staff communicate more confidently?

• Can this support managers who are already overwhelmed?

• Can this create more consistent coaching experiences across the firm?

AI Is Revealing Human Challenges

Industry leaders are starting to think more intentionally about how people learn, communicate and build confidence inside modern accounting firms.

Once firms start thinking about AI through a more human lens, it naturally leads to bigger questions about how teams learn, communicate and develop. It makes you think more critically about where your team is struggling and what they need help with.

And honestly, that’s valuable whether the answer to these problems ends up being AI or not.

Once you identify the gaps, the solution might be AI, or it might not be. But viewing technology through that lens forces firms to think more intentionally about what their people actually need to succeed.

The “ugly” stuff is all that repetitive, manual, error-prone work that no one wants to do but everyone ends up doing anyway: keying bills, chasing down backup in email, fixing client mistakes in the GL and re-entering the same data across multiple systems. But what if you could automate this layer and wrap it in smart approvals and permissions?

You can, and when you do, you’ll experience the Holy Grail of efficiency and control.​

What we’re talking about here is the “efficiency + trust = higher margins” play. You’re not just speeding things up; you’re also building an AP/AR environment that flows on its own, protects the GL and gives both your team and your clients confidence that nothing is slipping through the cracks.

And it all starts with automating the front end…

Automate the front end: OCR, inbox-forwarding and sync

The first job of automation is to stop humans from being data entry bots. Instead of staff or clients keying every vendor bill, you route documents into a single AP hub, like Melio’s, using tools like email forwarding, drag-and-drop uploads and direct connections to vendor portals. OCR reads the invoices, extracts the key fields and pre-populates bills so your team is reviewing, not re-keying. That alone eliminates a big chunk of the “we’re too busy to do advisory” bottleneck.​

Next, let integrations do the rest. Two-way syncing with systems like QuickBooks or Xero keeps payables and receivables flowing automagically between your AP platform and the GL. No more double work, copy-paste or hoping someone remembered to update both systems. When a client creates an invoice or pays a bill in the AP tool, those changes appear in the accounting software in real time, keeping the GL current without inviting the client into the GL itself.​

The net effect:

• Fewer manual touches and less time on low-value tasks

• Fewer client-created errors, because they’re pressing buttons in a simplified AP view, not experimenting in the GL

• Faster month-end, because you’re not hunting for missing transactions or reconciling between out-of-sync systems

The goal (and ultimate win) is turning AP/AR into a clean, digital pipeline that feeds the GL instead of constantly clogging it.

Add control: Approvals, roles and audit trails

Automation without control is just faster chaos. Modern AP platforms let you define approval workflows that mirror how decisions really get made in your clients’ businesses. You can set thresholds (who approves under $5k vs. over $5k), route certain vendors for extra scrutiny and build multi-step approvals for sensitive payments. Instead of random “Does this look okay?” emails, everything moves through a consistent, trackable path.​

Role-based permissions then keep the right people in the right lanes. Owners can approve, managers can review, staff can prepare bills, and your firm can oversee the entire workflow without giving anyone a free pass to override the GL. Clients still “press the button” where appropriate, but only inside the guardrails you design.​

Audit trails tie it all together. Every approval, change, rejection and payment is logged. So when a vendor calls about a payment, or a client questions a bill three months later, you’re not digging through inboxes. You can see exactly who did what and when.​

That structure does three things at once:

• Protects against fraud and out-of-policy spending

• Builds confidence for owners and controllers who need oversight but don’t want to micromanage

• Gives your firm cover when something goes sideways because the history is transparent and documented.

This is how you earn trust while still staying out of day-to-day chaos.

Turn efficiency + control into margin

Once the ugly stuff is automated and controlled, the economics of AP/AR change.

Your team isn’t stuck in the weeds cleaning up client errors in the GL or chasing down missing bills. They’re monitoring flows, handling exceptions and using the time they get back for higher-value conversations around cash flow, payment strategy, credit card usage and pay-over-time options. And that’s where advisory lives.​

On top of that, predictable workflows make it easier to package and price AP/AR as a standardized service instead of one-off, “it depends” clean-up work. You can build recurring offerings where:

• OCR, inbox-forwarding and syncing are baked into your baseline AP/AR process

• Approval workflows and permissions are part of onboarding, not an afterthought

• Oversight, not data entry, becomes the core of what clients are paying for.

You’re no longer undercharging for messy, manual work that kills morale and margins. You’re charging appropriately for a system that keeps money moving, protects the books and gives clients peace of mind.

Stop doing, start owning

The radical move here isn’t just adopting tech. It’s deciding you’re done being the human safety net for broken AP/AR.

Automating the ugly stuff means you stop burning margins on manual entry, rework and chasing client errors and start owning the AP/AR environment as a controlled, automated high-trust channel. You become the architect of how money and data move, not the person stuck cleaning up what happened after the fact.​

This is where efficiency and control finally meet. And once you’ve got both, AP/AR stops being a chore you tolerate and becomes an engine you can scale.

A lot of firms spent years untangling messy systems, moving to the cloud, implementing new technology and trying to modernize the way work actually gets done.

That’s really important work, and it’s definitely where I’d recommend any firm start first. (You’ve heard me say it time and time again, tech doesn’t fix broken processes.)

But what if you’ve done all of that? (If you’re reading this, I’m guessing that you’ve at least tried.)

Maybe you took it seriously, and you feel pretty good about where your firm is at now. It took a while to notice real results, I’m sure. But maybe, you’re finally starting to look around and realize there’s less manual work to do, your processes move along pretty quickly, and everyone seems a little less frazzled.

You’re not alone! I’ve noticed a lot of firms that seem to be entering a different stage of growth, and I think they’re some of the most interesting case studies in the industry right now.

I’m talking about firms that already invested heavily in technology and improved a lot of their workflows. The operational side of the business is in a much better place than it was five or 10 years ago.

Because of that, they’re starting to notice a different kind of problem. (There’s always something, isn’t there?)

The New Bottleneck Isn't Technology

The new problem has to do with people.

Some of the most forward-thinking firm leaders aren’t spending all their time talking about automation anymore. Instead, common topics include things like: communication quality, younger staff development, coaching, client relationships and consistency across teams.

I think that means some firms have gotten far enough along in their technology journey to realize that smoother systems don’t automatically solve human challenges.

In a weird way, better technology almost makes those challenges more noticeable.

Once the day-to-day operations get less chaotic, leadership gaps become harder to ignore.

You start noticing that managers are overloaded and younger staff need more coaching than anyone has time to provide. You see how communication can vary wildly from person to person. Even with better systems, the firm still relies heavily on a few experienced people to keep things running smoothly.

Technology Scales Faster Than Mentorship

Growth is happening faster. Managers are stretched thinner. Professionals often get fewer opportunities to absorb communication skills and advisory instincts just by being around experienced people all day.

At the exact same time, clients are expecting more human connection than ever.

They want responsiveness. They want strategic thinking. They want confidence. They want advisors who can communicate clearly and build trust.

That creates an interesting tension inside modern firms. Scaling technology is one thing, but scaling people is way messier.

ESPECIALLY when growth starts accelerating.

The Real Challenge is Scaling Humans

The firms furthest along in their technology journey aren’t asking which software to buy next. They’re asking questions like:

• How do we help people grow faster?

• How do we maintain quality as the firm scales?

• How do we support managers who are overwhelmed?

• How do we create more confident communicators and advisors?

Maybe this is the next phase of growth for the accounting profession. The first era was about digitizing work. The second era was about automating work. The next era may be about accelerating human development. Because once technology stops being the bottleneck, people become the competitive advantage.

Welcome to the Post-Tech Firm

The future is not about having the most technology. It’s about using that technology to develop better leaders, better advisors and better humans.

That’s not a technology strategy. That’s a people strategy. And I think that’s where the real future of accounting begins.