The role of the CFO is undergoing a profound transformation. No longer confined to balancing the books and the monthly close, today's finance leaders are navigating talent shortages, evolving compliance demands and economic unpredictability. In fact,
This shift isn't just about doing more, it's about doing things differently. The stakes are high, and the margin for error is slim. Finance leaders need technology that not only scales with complexity, but can be trusted to operate with precision and purpose. That's where AI comes in, but not just any AI.
Trust is nonnegotiable when it comes to AI in finance. More leaders in the industry need to introduce comprehensive AI commitments designed to ensure solutions are built ethically and without bias. A dedication to safety, transparency and accountability means CFOs can rely on AI tools that empower them to make smarter decisions while upholding the highest standards of integrity.
Purpose-built AI: the foundation for success
Off-the-shelf generative AI tools weren't built for the complexities of accounting. They weren't designed to navigate financial regulations, recognize accounting standards or protect the sensitivity of financial data. The output from basic AI can be unpredictable and will only ever be as good as the person who programmed it, and that's a risk the finance industry simply can't afford.
I think it is imperative to take a different approach: one rooted in domain expertise and built on a foundation of trust. We must train our own LLMs on curated, product-specific datasets including technical documents, configuration materials and support content. This way, these models don't just deliver performance; they reflect a deep understanding of the workflows that finance teams rely on every day.
Because when AI is built with intention and responsibility, it doesn't replace the accountant. It empowers them.
From tools to agents: the next chapter of intelligent finance
We're (rapidly) entering a new phase in the AI lifecycle, one defined by agents. The agentic AI market is still in its early stages, but it's growing fast and projected to rise from
In finance, this means transforming the monthly close, accelerating invoice processing and streamlining reconciliation. Advanced AI solutions and agentic capabilities are already helping finance teams to speed up crucial processes, and as the industry leans into agentic AI, this automation will advance even further, freeing up finance teams to act more strategically and forecast with advanced insights. This effectively elevates the role of the finance team beyond the numbers.
Agents won't replace existing generative AI tools; they'll enhance them. Agentic AI builds on existing capabilities by combining predictive, generative and agentic technologies, meaning it can not only analyze and generate insights but also take autonomous actions to achieve specific goals. It represents a new frontier in software development, a leap beyond conversational AI. And as AI assumes more routine and repetitive tasks, finance teams will be able to gain the time and space back to focus on what truly matters: strategic insights, business advisory and forward-looking planning.
Earning trust with every interaction
Technology can only deliver value if it earns the user's trust, especially in finance. Trust remains a dominant barrier for AI adoption, especially in highly regulated industries like finance. To get over this hurdle we need to provide clear, accessible insights into how AI is developed and how it operates within financial products. At Sage we demonstrate this through our
Autonomous agents represent a fundamental shift in how finance is done. But the benefits of this shift can only be realized if the technology is held to the highest professional and ethical standards.
That's why collaborations with global accountancy professional bodies are becoming increasingly crucial. For example, Sage licenses AICPA content, including training materials and professional literature, to ensure our network of agents are trained to reflect the highest standards of accuracy, ethics and trust. LLMs essentially act as the "brain" that will enable agentic AI to think, plan and execute tasks more autonomously, transforming them from reactive response systems to proactive problem-solving agents. While these initiatives often begin regionally, the implications are global.
Because ultimately AI should enhance human potential, not replace it. It should streamline the complex, simplify the routine and elevate what people can achieve. For finance teams, this means stepping into a new era of confident decision-making, deeper insights and strategic leadership.
Together, we're building that future one trustworthy interaction at a time.
