How Firm AI tackles the biggest challenges accounting and consulting firms face today

Tom koehler

Enrollment in four-year accounting programs is up 8.9%. This is the third straight year of growth, but today’s freshmen won’t be hiring-ready until the early 2030s. So firms still have to manage the talent gap creatively.

Firm AI addresses the talent shortage three ways.

First, as alluded to previously, it hands routine work that consumes a large share of professionals’ non-billable time to agentic AI coworkers — work like completing timesheets, intake forms, conflicts questionnaires, and status compilations.

Second, it supports and accelerates practitioners’ judgment — about which clients to accept, which estimates to challenge, and when to walk away — with playbooks that are executed consistently by AI coworkers that flag exceptions for review. So when someone retires, the expertise and institutional knowledge stays.

Third, it reshapes roles, so there are fewer preparers and more reviewers. Operations staff spends less time on data entry and more time on judgment, which makes better use of scarce talent, and provides a more attractive entry point for the next generation.

Quality holds because the model assumes fewer people, not more trust in the machine. Consequential decisions stay with professionals, every AI action is logged and auditable, and the review bar remains high.

Tom koehler

To understand where private equity is headed, it helps to look at where it’s been.

Private equity’s first wave of investment in professional firms was driven by multiple arbitrage: Buy small practices, aggregate them, then sell the combined entity at a premium. With many firms now consolidated, that opportunity is maturing, and the question shifts from how many firms a sponsor can buy to where organic growth will come from next.

Private equity firms sit on both sides of the table, as buyers and sellers. In professional services, the priorities are the same either way: margins that survive fee deflation, capacity that doesn’t depend on hires who don’t exist, and controls that satisfy firmwide governance.

Agentic AI is becoming central to all these things. But it also introduces risk: An ungoverned agent inside a portfolio company is a regulatory finding waiting to be written, and a discount at exit.

It’s becoming more obvious that the next wave of deals will be priced on operational excellence in addition to financials. Firms that can prove they run governed AI — not just claim it — will command a premium.

This is where Firm AI comes in. It supplies the governance needed to use AI responsibly by logging every AI action and enforcing independence, conflicts, and entity boundaries across core systems. And it adds capacity without adding headcount, so growth stops being constrained by the labor market, and unit costs rise more slowly than revenue. So when it’s time to exit, the buyer’s due diligence will confirm a strong valuation.

Tom koehler

When every firm’s professionals use the same horizontal tools, the productivity those tools deliver stops being a differentiator.

The Big Four make this point at enterprise scale: McKinsey has 20,000 AI agents supporting its work, EY plans to have 100,000 agents by 2028, KPMG has committed to billions of dollars in AI spend, and Deloitte uses Zora AI™ to augment its workforce.

However, every market leader has two advantages that their competitors simply can’t buy.

The first is the firm’s “memory”: every engagement delivered, deal passed, fee held or broken, and conflict cleared or escalated — plus the reasoning behind each decision.

The second is the unwritten judgment and methods of the firm’s practitioners, which inform every decision and continually enrich the firm’s memory. For a century, this passed within the firm by apprenticeship, then left with the practitioner at retirement or lateral exit.

The Firm AI playbooks I mentioned earlier are the first vehicles for permanently codifying a firm’s judgment and methods. Each time a playbook runs, the AI remembers what decisions were made and how, so it gets smarter. Firms that use these playbooks to execute common tasks, such as screening inbound opportunities or conducting conflicts searches, create an ever-growing, proprietary record of their memory and judgment that no model vendor can supply.

In a market where intellectual property and productivity are table stakes, these playbooks empower firms to scale the unique expertise and ways of working that make them stand out from their competitors.

Tom koehler

Most enterprise buyers now say they want pricing that’s tied to results: 2026 IBM research notes that 83% of consulting firm leaders favor this approach. AI adds to that pressure: When it compresses a 40-hour analysis into a fraction of the time, clients won’t pay for 40 hours.

KPMG’s own auditor made that case in February, when it negotiated down its own audit fee on the grounds that AI had made the work cheaper to perform.

The billable hour isn’t being abolished, but as this example illustrates, it is being audited.

In January 2026, McKinsey’s Global Managing Partner, Bob Sternfels, said on the record in Harvard Business Review that “about a third” of revenue comes from underwriting outcomes. He shared that McKinsey’s own analysis found outcome-fee revenue to be more volatile than hourly billing revenue, and that its partner compensation model wasn’t built to absorb the added volatility.

That’s not an argument against the model; it’s an argument for running it on real-time economics. But most firms don’t have that. Instead, they discover engagement profitability at closeout, which under a fixed fee means discovering the loss after it’s too late to fix it.

In my conversations at top consulting firms, price committees are already asking for fee benchmarks and win-loss history, so the fixed fee is set from evidence rather than optimism. Firm AI facilitates this by providing firms with the real-time data that alternative-fee arrangements require, along with pricing recommendations built from comparable engagements.

Passive time capture, also possible with Firm AI, will become essential, because it will allow firms to see the work as it happens, track profitability, and staff accurately even when hourly billing is no longer the norm.

Last but not least, there are a few things lead partners will always ask for: engagement intelligence, margin alerts, and proactive, real-time visibility into scope creep. Firm AI can provide those too.

The hard part of alternative fees has never been the pricing; it’s been the lack of an operating model providing connected, real-time intelligence. And that’s what Firm AI makes possible.