By Lavi Sharma.
Finance and accounting leaders are increasingly being asked to take on more responsibility for how AI is used in their organizations, and by their clients. According to new research from Genpact, nearly 40% now sponsor or lead AI initiatives. However, the report also found that many are being pushed into this position without the tools they need to succeed, as 62% of respondents cite skills gaps as a significant barrier, with an equal number highlighting regulatory and compliance challenges.
For CPAs, this isn’t just about learning a new tool or workflow. As AI becomes part of financial reporting, forecasting, and decision-making, CPAs are expected to help shape the standards for trust and transparency, and help clients gain real business value from this technology. But with these new responsibilities come new challenges and opportunities. With the right approach, CPAs can help their firms and clients use AI in a way that protects trust while delivering a competitive edge.
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The CPA’s role: Bridging innovation and accountability in AI adoption
Organizations are shifting their focus from “AI that generates” to “AI that executes,” where agentic AI systems decide, act, and learn alongside people. That said, translating AI adoption into measurable financial outcomes is no easy feat. The research found that only 35% of executives say their AI applications are very effective at delivering measurable business value. At the same time, governance isn’t keeping pace with adoption, as nearly all (99%) respondents report not having adequate governance models and structures in place to handle the risks that come with autonomous and agentic AI systems.
For finance leaders, that gap matters because they don’t just ask “Does it work?” They ask, “Can we prove it worked, explain why, and document the risk?”
This is where CPAs come in. By acting as both advisors and guardians, CPAs are uniquely positioned to help businesses translate AI’s potential into measurable results, all while maintaining rigorous oversight and governance. Their deep understanding of accountability, documentation, and risk management enables them to implement responsible AI practices, document decision-making processes, and foster a culture of transparency.
By aligning AI initiatives with well-defined controls and robust governance models, CPAs can help clients avoid “shadow AI” practices and harness new technologies to serve strategic goals without exposing the business to unnecessary risk.
The new skill today’s teams need
For decades, a strong finance team was built on pristine resumes and CPA certifications. Those credentials still matter, but today’s finance professional needs to be just as comfortable with algorithms, data, and storytelling as they are with spreadsheets. However, Genpact’s research shows that while workforce capability gaps are the most frequently cited organizational constraint to AI adoption, only 45% say their organizations offer AI training to all employees.
To help their clients realize the full potential of AI, future-ready CPAs must aim to build:
- Role-based AI fluency: CPAs don’t need to be data scientists, but understanding what AI can and can’t do for clients and knowing how to get reliable, high-quality output is critical
- Smart context navigation: Today, gathering data alone isn’t enough; to drive growth and competitive advantage, professionals need to interpret it within the context of their clients’ business and offer a clear picture to decision-makers
- Adaptability and a desire to learn: With tools and rules changing fast, curiosity and a willingness to learn is a top-tier skill
From compliance cop to strategy architect
As CPAs work to guide their firm and clients through AI adoption, they naturally become a strategy architect, responsible for building a team ready for a blended human-machine world. This is where challenges can turn into real advantages.
CPAs should start by mapping the skills that their team will need in the next two to three years and use this to guide hiring and development. Think of skills as dynamic assets, not just boxes to check on a resume. Next, they must make upskilling a core part of business metrics, tracking how the team adopts new skills and tying that learning to business outcomes. For example, how did upskilling in automation reduce close cycles or error rates for a client?
None of this is possible without effective change management. To get AI right, firms need to get their people comfortable with new technology and processes. By reframing how humans and AI can work together, leaders will be able to build confidence and show that AI adoption is an opportunity for growth.
The human edge in an AI world
Even as AI takes on more tasks, people remain the key differentiator. A CPA’s judgment, intuition, and ethical reasoning are key to helping clients derive real business value from advanced technology. By demonstrating fluency in both finance and AI, accounting professionals become the essential link between data and decision-making. As machines scale their output, CPAs’ role is to safely scale the impact for their clients, turning complex data into clear, strategic advice.
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Lavi Sharma is the global finance and accounting service line leader at Genpact. She is a dynamic and thoughtful leader, passionate about helping CFOs and finance leaders design and execute finance functions that are fit for the future.
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