AI is everywhere in the headlines. And it’s officially entered the boardroom, bringing fresh pressure and high expectations for accounting firm leaders. This pressure often shows up in the form of questions like:

• “What’s our AI strategy?”
• “Are we leveraging AI enough?”
• “What’s our risk if we don’t act now?”

But the real opportunity lies not in answering these questions with sweeping innovation plans or vague declarations. Instead, it starts with one fundamental shift in mindset: moving from a technology-first to a business-first approach. 

Approach 1: Technology-first

“AI must be used - we should be using it.”

This mindset starts with technology and searches for problems it might solve. 

Compare this to the “let’s build a website” mentality from the early internet era, where companies rushed to go digital without a plan for what those sites were meant to accomplish. It’s driven by FOMO, competition, and the desire to appear innovative.

In practice, the technology-first approach often leads to:

• Broad but shallow pilots
• Low adoption from employees
• Solutions looking for problems
• A lot of motion, with little measurable impact
  
  

Approach 2: Business-first

“How do we accelerate the prep time required to produce engagement letters?”

The business-first  approach begins with specific business challenges where AI is just one possible solution. It’s rooted in operational pain points, measurable outcomes, and a clear understanding of what’s at stake.

When firms take a business-first approach, they:

• Identify the biggest friction points
• Select the right tool for the job (AI or not)
• Measure success in terms of business impact
• Get stronger adoption because value is obvious
• Prioritize efforts that drive tangible results

Back to the early internet era. Many companies rushed to build websites simply to say they had one, and lacked a clear purpose. Amazon took a different approach. They identified a specific business challenge: how to dramatically expand access to books and make it easier for people to buy them. 

The internet wasn’t the goal, it was the tool. That clarity of purpose became the foundation for Amazon’s broader strategy, which ultimately helped them become one of the most successful and transformative companies in the world.

Firms should view AI the same way. Not as a checkbox, but as a lever.

The impact difference

When AI implementations originate from clear business needs, the results speak for themselves. These initiatives are more successful, while also being more sustainable, scalable, and meaningful to the people doing the work.

• They solve real problems employees face daily - AI becomes a tool for relieving bottlenecks, not creating new ones. Teams are more likely to adopt solutions that genuinely make their jobs easier.
• Success metrics are defined from day one - Projects start with a clear understanding of what “better” looks like whether that’s reducing turnaround time, increasing billing accuracy, or improving client responsiveness.
• ROI is tied to operational improvements - It’s not about how impressive the tech is, it’s about how effectively it accelerates core processes and contributes to firm performance.
• Teams understand the “why,” not just the “how” - With a business-first approach, employees are brought into a solution versus being handed another tool. This drives engagement and long-term adoption.
• Resources are focused on high-impact use cases - Instead of spreading efforts thin across trendy experiments, firms can invest in a few meaningful areas with high return potential and scale what works.

Practical applications of AI for accounting firms

To bring this to life, here are real-world examples of how accounting firms are applying AI with a business-first mindset. Each use case is tied to a specific operational challenge and delivers clear, measurable value.

• Faster client onboarding
• More accurate billing
• Enhanced knowledge extraction
• Improved audit efficiency
• Reduced administrative overhead
• Streamlined financial processes
• Proactive workflow management

Success with AI starts here

The most successful AI implementations don’t start with “What AI should we adopt?” or a 5-year roadmap. They start with a simple, focused question: What specific operational challenges are costing us the most in time, quality, or client satisfaction? From there, firms can evaluate whether AI is the right tool to solve those challenges and measure success based on tangible improvements in the metrics that matter most.

That’s how hype becomes impact. One problem, one solution, one win at a time.