Reimagining the Finance Function

While these encounters are valuable, they tend to heavily focus on technology and individual use cases - automating something that is currently done by humans with enhanced analytics capabilities. How can finance teams enhance their use of AI beyond surface-level automation? What untapped AI opportunities could finance pursue for transformative impact?  

No single perspective can fully address the scope of this question. However, this blog post aims to share a set of observations and perspectives that may serve as meaningful steps in the right direction and spark further dialogue and exploration. 

To create something new, we must first let go of the old  

Too often, organizations find themselves automating tasks or processes that are outdated or unnecessary. While these may have once had a valid purpose, today they often represent legacy inefficiencies. 

Before implementing any AI-enabled solution, it's essential to identify and eliminate these obsolete activities - those that consume time without delivering real value. Streamlining the process first ensures that AI is applied where it matters most. 

Some might argue that AI capabilities are already embedded in platforms, and companies don’t need to develop them independently. While that’s often true, these solutions typically come with licensing cost and there’s no guarantee how those costs will evolve over time. 

Embrace uncertainty as opportunity 

The pace of change in AI has been phenomenal over the past few years. Coupled with major shifts in geopolitics, this has introduced a new level of uncertainty into the business and working environments. But uncertainty doesn’t always have to be a threat. It can be also a catalyst for innovation creating opportunities for new business models that thrive and outperform the old ones.  

This raises an important question: could finance organizations expand their role beyond traditional planning and move toward strategic foresight? What if finance could help organizations see what’s not yet visible and anticipate deep shifts before they fully emerge?  

Could finance truly become a forward-looking business partner, one that guides companies toward their future and embraces a more strategic role? 

Don’t overlook the human side 

Much of the conversation around AI in finance has centered on what the technology can do - its capabilities, efficiencies, and automation potential. Yet the human dimension is often overlooked. AI may transform your company, but without getting the people part right, that transformation may never take root. In fact, it could risk the very foundation of the organization. That’s why the first and most critical point is people: engaging employees early and involving them in shaping AI initiatives is essential to building trust and ensuring adoption. 

One reason this topic receives less attention may be its complexity. AI’s impact on jobs is significant: while some estimates suggest that 10% of roles may become redundant, nearly 100% will be affected in some way. In finance, certain tasks could be fully automated. AI-enabled solutions can now identify automation potential far faster than traditional analyses based on interviews. However, if automation is approached solely from a top-down perspective, there’s a real risk that the implementation won’t deliver the expected benefits. The devil is often in the details.  

There’s also an innovation angle worth exploring. Finance teams often operate with an “expert mindset,” relying on deep domain knowledge and established practices. But the more we know, the less we tend to question. Reimagining finance calls for an “innovator mindset”—one that challenges assumptions and embraces fresh thinking. Interestingly, the most transformative ideas for Finance 2.0 may not come from the finance function itself. As traditional entry-level roles become less common, recent graduates, unburdened by legacy thinking, may be uniquely positioned to envision bold new ways to apply emerging technologies. Their fresh perspective could be exactly what’s needed to shape the future of finance. 

Finally, none of this can succeed without strong leadership and a clear vision. Leaders must articulate not just what AI can do, but why it matters, connecting technological change to strategic goals and cultural values. Visionary leadership helps teams navigate uncertainty, align around purpose, and stay resilient through transformation. In the age of AI, leadership isn’t just about managing change, it’s about inspiring it.