More of What Matters

Why the industry’s highest AI adopters are measuring regained capacity in value, not volume.

The frost came late that spring, and the winery owner lost his crop. He went straight to his accountant, urgently seeking an answer to one very important question:

What would it cost him to replant the fruit and still make wine that year?

A few years ago, finding the answer would have meant assigning someone to the calculation, digging through the books, and tacking all that extra labor onto the already-cash-strapped client’s bill. But thanks to clean data and the power of AI, Gena Graziano’s firm had an estimate ready in under an hour.

The speed of that turnaround was incredible—almost unbelievable, even to Graziano herself.

But getting the answer fast was only one piece of the puzzle. What really wowed the client was the firm’s ability to take that dollar amount, sit down beside him, and help him figure out exactly where the money would come from and how to allocate it. That’s the part of the AI-driven capacity narrative that often gets missed.

Doing more with the same team is a top priority for firm owners adopting AI. In the recently published State of AI Accounting & Bookkeeping report, 43% of owners selected increased capacity as their number-one goal, more than any other answer and roughly seven times the number of respondents who chose profitability.

But “capacity” can mean very different things depending on where a firm sits on the adoption curve. For those who are still early in their AI journey, it often translates to reclaimed time: a task that once took hours now takes minutes, and the amount of work a single employee can accomplish in a day increases exponentially. But further along the curve, capacity starts to morph from more into different and better.

That’s where it changes what the firm is actually selling, empowering leadership to embrace business models they might have once considered out of reach.

That climb, from time saved to work transformed, is one of the most interesting evolutions in accounting—especially for small and growing firms like Graziano’s. And plenty of AI-forward firms are already seeing the impact of that shift in a big way.

The Drudgery Drawbridge 

When they first dip a toe into the AI pool, most firms start in the same unglamorous place: the drudgery.

And for many, “drudgery” is synonymous with “email.” Darcy Huey, the office manager at MSM Advisors, finds AI particularly helpful in overcoming writer’s block. 

For Huey, AI helps combat this all-too-common “blank page” syndrome, turning ten minutes of staring at a blinking cursor into two.

At VP CPAs, Bri Como unleashed AI on something even more mundane: time tracking. Her firm built a specialized agent that lives in their workspace, so calculating billable time is as easy as sending it a message.

“A lot of our work is billable,” says Como, who is the firm’s manager of operations and systems. “Some of it isn’t, but even those things, when you have hourly employees, we don’t want it to take time to track time.”

With the agent, she simply enters any notes she has on the task she wants to track and bill for, and the agent finds it in the workspace and adds it to the running billable total. That means Como doesn’t have to worry about navigating a separate software, forgetting to start or stop a timer, or keeping a time record for each project. The result: fewer errors and less billable time slipping through the cracks.

Graziano’s first “ah-ha” moment with AI came when a client’s notetaker popped into a virtual meeting one day. “Well, what is that?” she remembers asking. The client described it as a tool that records, transcribes, and summarizes each call automatically, then follows up afterwards with key points and action items. Graziano could hardly believe her eyes. She immediately started using the tool for every call, finally freeing herself from the constant struggle of typing notes while talking.

Quick, easy wins like these provide a perfect gateway to more robust AI usage. They lower the drawbridge to initial adoption and help demystify the technology, all without much effort on the user’s part.

This is crucial considering that the aforementioned AI report also pegged time as the number-one barrier to getting more out of AI, with 41% of respondents selecting that response (approximately double the second-ranked answer).

What’s the biggest barrier to getting more value from AI at your firm?

So, accounting professionals are turning to AI with hopes of putting time back in their schedules, yet they largely struggle to find the time they need to adopt AI in the first place. It’s an interesting conundrum, and certainly one that warrants further exploration.

But based on feedback from multiple survey respondents, the more compelling benefit—and perhaps the more compelling argument for prioritizing AI adoption—lies not in saving more hours, but doing more with the hours you already have.

The Time Savings Fallacy

Taylor Ammons has thought long and hard about this benefit. Her honest conclusion: the time-savings framing doesn’t really fit her experience. Ammons runs operations at Accounting Therapy, a fully remote firm of eight, and when the survey asked what she does with the time AI saves her, she balked.

It’s not that the tools aren’t helpful; they help enormously. It’s that the help doesn’t always result in free minutes on a calendar. Instead, it compresses the time each task requires, enabling Ammons to do a better job with each to-do on her list. Instead of rushing through a slide deck and calling it good enough, for example, she can produce something polished in the same amount of time.

“There’s so much to be done in a small firm that’s trying to grow,” Ammons says.

Rebecca Isaacs, who runs Isaacs & Associates with a team of ten handling roughly 1,000 clients, describes a similar experience. When she first started using AI as a research tool, she expected to get faster. Instead, she naturally poured the time savings right back into the task at hand.

What she ends up delivering back to clients now comes with “a far greater scope of considerations” than it used to, she explains. So, while the work might have taken roughly the same amount of time, the result is far from the same.

And then there’s Deborah Harris, the CEO of Grow Group (parent company of Grow CFO), whose team is farther up the adoption curve than almost anyone in the entire profession. Harris stopped thinking about the ROI of AI in terms of time savings a long time ago. Hours saved, to her, is a base-camp metric that answers the wrong question.

Instead, Harris—who spent four years building the AI system that now runs alongside her staff—tracks an entirely different metric: revenue per full-time employee. 

“And so, how can I improve the revenue per full-time employee? How can I improve the gross profit per full-time employee?” Harris explains. “And then because a lot of our AI started in the back-end and the administration side of things, how can I improve the operating profit as well? So I measure all of those things.”

If you only ever count the minutes, Harris argues, you will miss the more valuable change happening underneath them. Because the question that separates the firms who are still sitting at the bottom of the mountain from those who are climbing to the top of the peak isn’t, “How much time did AI save you?” Instead, it’s, “What did you do with the space?”

For Harris and Grow Group, the answer is increasing the value of the entire business.

The Meaning of “More”

For many firms, growth means doing more, and more means adding clients and services. And according to Financial Cents’ AI survey data, 52% of professionals agree AI lets their firm do that without adding headcount.

Graziano’s firm is one of them. First Steps Financial has grown revenue 15–20% year-over-year while simultaneously increasing its income per team member—just like Harris and Grow Group—because each person can simply handle more.

But beyond simply ramping up volume, many growth-focused firms are looking toward a second, perhaps even more impactful lever: depth.

Isaacs is bullish on this point. She credits AI for giving her team more capacity to put into the kind of work that actually matters to the clients they have—the kind of work that fosters real relationships.

Now that her team has more time to invest in deep analysis of client books, for example, they are able to catch things they never would have noticed with a rushed pass: an overcharging vendor, an overlooked expense, a foreboding revenue pattern.

She’s using the extra bandwidth to branch into CFO-style work she’d never been able to offer before. This allows her to expand the scope of each engagement, leading not only to more revenue, but also greater client loyalty.

“We’ve done it with a few clients,” Isaacs says of the new model. “We’ve kind of test driven this. I’ve got one client right now—I think his fixed fee is almost $12,000 a month. And we pretty much do soup to nuts on him. We’ve got four people on the account.”

It’s a move enabled by AI, but also one Isaacs is strategically making to help keep the firm viable despite AI. She predicts that AI will soon be able to file basic 1040s in minutes, so why would she put energy into taking on more of them? 

The more complex cases, she says, will remain with human experts—because those clients will still want a real person to interpret, explain, and provide guidance on the numbers.

“If they can do it at home on their computer and in two minutes have their answer, they’re not coming back [to me],” Isaacs says. “So I see what’s gonna happen here. It’s gonna be the complexity that brings people to us, and the need for customer service. Because not everybody wants to get on a computer and just deal with a computer. They want to ask questions, they want to feel secure. We are moving more towards customer service than away from it, in my opinion.”

Relationships, Not Returns

For firms that choose to leverage AI-enabled time savings to serve clients more deeply, work will naturally move from pure production to strategic advice.

Harris built her entire firm on that premise. They don’t do tax returns at all (a very intentional choice), instead focusing solely on fractional CFO work for growing businesses. The Grow team uses AI to, in her words, “use our human capacity in the area where it’s most needed.” 

She’s careful about the language, too: her team refers to AI not as “artificial intelligence,” but “augmented intelligence,” because that vocabulary better aligns with their belief that the machine exists to extend a person’s reach rather than stand in for it.

Ammons has a pretty good idea of how she hopes AI will extend her reach. As a former small-business owner, she’s all-too-familiar with the financial gaps that can make or break a business.

“I lived by my cash flow, and I didn’t know what I was doing,” she says.

Her dream is to bring forward-looking guidance around cash-flow management, projections, and overall strategy to small businesses that could never afford a full-time finance leader.

And she believes the road there is paved with automation. Once her team is free from tedious manual processes, they’ll have more time and space to lean into the advisory work that wasn’t feasible for them to offer before. She’s in the midst of building the foundation to help get them there: task by task, template by template, project by project.

First Steps Financial has always positioned itself as a partner rather than a transaction engine. AI has only underscored that value prop. Proposals and templates that used to eat a whole day now write and send themselves, which means the team can put more hours into client relationships rather than paperwork—and that’s exactly what Graziano wants.

“I don’t really even do any of those things at all anymore,” she says of the administrative grind. “They’re all automated.”

And whenever a client needs numbers to make a decision—the winery owner, for example—the firm can now produce them fast enough to help the client reach a timely, fully informed conclusion.

The View from the Top

The next natural question, then, is how the payoff of deeper client relationships actually shows up. The answer largely depends on where you are in your journey.

Near the bottom of the adoption curve, returns are less obvious. Como, for example, is optimistic about the future impact of AI in her firm, but she doesn’t yet have concrete ROI figures to share.

“I think we’re still too early to definitively say,” she says matter-of-factly.

Higher up the curve, the data-backed picture starts coming into focus. Harris, for example, has some of the most definitive numbers of all: as mentioned above, the Grow team has seen a 20% lift in gross profit on the CFO side of the business and roughly 10% on the bookkeeping side (measured by revenue per full-time employee).

The situation in both firms is consistent with the AI survey data. Only one in five firms can point to clear, measurable ROI from AI, while about half describe the benefits as promising but hard to quantify.

Has your firm seen a clear return on its AI investment?

And in line with both Como’s and Harris’s experience, the results gap closes as adoption deepens: firms running AI across the whole organization are more than 15 times likelier to report measurable ROI compared to firms where only a few people dabble.

Skills for Success

For a long time, accounting work was largely seen as a calculation and compliance job. It was equations and formulas and spreadsheets and tax forms. But with AI, that center of gravity is shifting—sliding away from pure number-crunching and evolving into something more like coaching. More and more accounting professionals are finding themselves advising, interpreting, and supporting their clients through major financial decisions. And that means the skills necessary to thrive in the role are evolving as well.

Ammons has watched this happen on her own team. The higher-value services her firm wants to offer depend less on technical execution and more on confidence in front of a client, and not everyone will want or succeed in that kind of role.

More than that, not everyone will be equipped to succeed in that role. And with less technical work for newer professionals to learn on, there are even fewer opportunities to develop the depth of knowledge and skill necessary to act as a confident advisor. Isaacs worries about this stunting the career growth of the next generation.

While she sees the tools as major accelerators for seasoned professionals who already have a solid foundation of knowledge and experience (and who inherently know what “good” looks like), she’s also not ignoring what this could mean a decade or more down the road.

If AI does the entry-level passes that used to teach newbies the basics, where do the basics get taught?

“You can’t use a calculator in grade school,” Ammons says, arguing that young students earn the right to automate addition and subtraction by first understanding how to do it manually.

Similarly, she wants her team to grasp the back-end of every automated process before they lean too heavily on AI, because when a client asks why the money moved the way it did, for example, “they need to be able to talk the client through that.”

Huey is witnessing the educational impact of AI on the front lines. In addition to her day job as an office manager, she is currently in school for accounting. While she is disciplined about not overusing AI, she still worries that it’s affecting her learning.

“The more I rely on AI, the less I’ll retain,” she says.

That’s why, while she leverages AI for research, she forces herself to generate her own ideas first, wary of what leaning too hard on the tech will cost her later. But many accounting leaders wonder if that approach is the exception rather than the rule.

Harris has taken matters into her own hands, in a way, saying that part of her responsibility as a firm leader is putting her employees on the path to a long, sustainable career.

The first thing she tells a new hire:

The way she sees it, the day-to-day tasks that make up an accounting role will certainly change with AI. But the need for someone who truly, deeply understands the numbers—enough to catch the machine when it’s confidently wrong—will never go away.

All of which brings the climb back to where it started: a frost, a winery, and a number calculated in half an hour.

The Ascent

The speed of that calculation wasn’t the true ROI of First Steps Financial’s investment in AI.

The ROI came after the firm handed the number to the client, when the team sat with a shaken business owner, working out how to rebuild what the weather had taken. That conversation—and all the care, empathy, and reassurance that came with it—is something AI could never handle. And the way Graziano sees it, that is precisely what the firm’s regained capacity is for.

Getting your firm to that stage, though, means putting sustained effort into the climb. At the bottom of the AI adoption curve, AI gives a firm its time back, and reclaimed time is a real gift.

But time is only the first step in a long journey. Only the firms that press forward will discover the full value of this technology: its ability to change the work from simply producing the numbers to interpreting them, from filing the return to advising the person behind it, from serving whoever walks through the door to going deep with the clients worth the dive. And somewhere near the summit of that curve, the ROI becomes unequivocally apparent: in service quality, in relationships, and yes, in revenue.

In its highest expression, capacity isn’t about how much a firm can get done, but what they have the room to do. AI might give back the hours, but how a firm uses them is still a gloriously human choice.