By Saum Mathur.
Come 2026, your firm will no longer view revenue from billable hours as the most important performance metric. Instead, you’ll focus on a new metric as your North Star: revenue per employee.
This shift is inevitable. In a market where CPA firms are being acquired at a breakneck speed, many firms face pressure to increase valuations by optimizing for efficiency and profitability. Build an effective path forward by setting your sights on revenue per employee and integrating AI technology that helps you improve it.
How Revenue Per Employee Drives Different Behaviors
Take the traditional hourly billing–based revenue model. This model often incentivizes behavior that’s the opposite of value-driven. When the client can afford it, there’s an incentive to charge more hours for work that could be completed more efficiently. This has been the norm in consulting companies and accounting firms for decades.
The revenue per employee model takes a different approach. It incentivizes your management team to adopt strategies that grow revenues faster than headcount costs, or potentially with lower headcount altogether. This shift enables you to consider new services that deliver higher value to clients.
For example, if your firm does compliance work, you would now be able to enter the advisory market, and even cross-sell these services to existing clients. In turn, clients would begin perceiving your firm as a strategic partner rather than just a commodity provider. You would then be able to charge higher prices for work delivered at similar headcount costs as compliance projects.
When your firm prioritizes revenue per employee, you’ll also focus on price optimization. Compliance services are commoditized and price-sensitive. However, clients show less sensitivity to price increases in advisory services, so pricing is only limited by their budget and the perceived value your firm provides.
How to Improve Your Firm’s Revenue per Employee
Small to midsize firms struggle with two main challenges: attracting talent and clients while operating efficiently. Both factors constrain revenue growth. First, identify your firm’s efficiency bottlenecks—typically the manual effort required for accounting, tax and advisory work. Rather than adding more people, implement AI to multiply your team’s output.
Instead of relying on legacy systems, adopt the newest AI-powered platforms that handle time-consuming operational tasks. Look for features like AI-based pricing models, dynamically created custom workflows and AI agents that handle project management and client communications. Also take full advantage of AI features that tax and accounting software vendors are building into existing products.
Approach this transformation using a three-part framework:
1. Automate Existing Core Workflows
Start by implementing tax and accounting software with built-in AI capabilities in order to automate significant parts of your existing accounting and tax workflows. Look for AI products that can automate transaction booking, verify whether data for completing taxes is available and accurate, and then automate tax preparation itself.
The most advanced AI systems can create tax strategies for clients automatically.
This foundational step significantly reduces manual effort, allowing your firm to take on more clients without increasing headcount. More importantly, it frees up your existing team’s time for higher value work.
2. Break Free from Templated, Cookie-Cutter Processes
Most firms use practice management solutions that automate workflows and facilitate client interactions. But here’s the growth-killing problem: legacy systems require a lot of effort to set up workflows and templates, so once they’re established, your firm ends up taking on only the projects that fit the cookie-cutter workflows you’ve already designed.
This limitation often keeps compliance firms trapped doing compliance work. The rigid, one-size-fits-all nature of traditional workflows makes diversification into advisory services difficult, given each advisory project requires customized approaches that don’t fit standardized processes. The opportunity cost is significant: high-growth firms are 49% more likely to emphasize advisory services, according to the 2025 Future Ready Accountant report.
Modern platforms solve this constraint by using AI to create statements of work that truly reflect each client’s context and pain points, then build tailored workflows in a matter of seconds. This flexibility eliminates the growth constraints that force firms to turn away profitable advisory opportunities just because they don’t fit existing processes.
3. Scale Advisory Services with AI Assistants
Another transformative advancement is the emergence of advisory assistants. These AI products perform strategy and roadmapping work based on a client’s specific financial and industry context and data.
Then, your team can focus on interpreting these insights and implementing them as high-value advisory work that clients pay premium rates for. These agents significantly accelerate advisory work, which lowers the barrier to entry for compliance firms that want to expand their offerings.
The Critical Distinction: Productivity Multipliers vs. Cost Savers
As you evaluate AI tools, look for ones that act as productivity multipliers rather than simple cost savers. The difference between the two is whether the AI uses your data and your client’s data and context. If it does, it’s a productivity multiplier.
Cost-saving AI is still valuable to speed up generic tasks, like basic data entry, standard calculations or routine document generation, with limited context awareness. Productivity-multiplying AI, on the other hand, uses your data and client’s unique context to offer insights, customized recommendations and tailored solutions. In turn, it helps your team deliver higher value advisory services more efficiently, which directly supports your shift toward optimizing revenue per employee.
What’s at Stake
AICPA’s CAS Benchmark Survey found that firms that generate significant revenue from advisory services earn more than 30% higher monthly recurring revenue. But those who stick with the legacy billable hour model risk getting left behind—or worse, going extinct.
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Saum Mathur is Chief Operating Officer at Paro, where he drives efficient growth by integrating AI with operations through intelligent automation. A 25-year AI veteran, he has led enterprise-wide business intelligence strategy, data services and analytics platforms across global operations at Hewlett-Packard, Groupon and CA Technologies. At Paro, Saum advocates for the strategic use of AI to help finance and accounting professionals transition from traditional compliance work to higher-value advisory services.
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