At Cofiniti, we recently hosted a Roundtable discussion with a group of seasoned finance leaders to cut through the marketing noise. We wanted to move past the hype and discuss the gritty reality of piloting AI, the genuine security hurdles, and why authenticity and the ‘human touch’ is more important than ever.
Here are the key takeaways from our conversation, coupled with other observations from what we’re hearing in the market.
The most successful finance teams aren’t trying to automate their entire department overnight. Instead, they are finding success in three specific areas:
Perhaps the most lively part of our discussion centred on privacy. Many business leaders have admitted to implementing strict bans on public tools like ChatGPT after discovering employees were uploading documents including sensitive data.
So what’s the consensus now? From our discussions, there seems to be a move away from public AI and towards Secure Ecosystems. Companies are increasingly leveraging tools like Microsoft Copilot or AI features within their existing, secure cloud storage providers. The goal is to keep the data where it already lives, ensuring that corporate intelligence doesn't leak into the public domain.
A recurring theme was that AI is not a shortcut for poor data hygiene. You cannot overlay sophisticated AI on top of messy, inconsistent journal entries and expect magic.
Implementation requires a significant upfront investment in Data Cleaning. AI needs time to learn the business. The more clean, historical data it consumes, the more accurate its anomaly detection becomes. If you aren't willing to do the groundwork on your data quality, your AI project will likely stall.
Despite the fears that surround total automation of roles and departments, the finance leaders we’ve spoken to are unanimous: AI is a Co-Pilot, not an Autopilot.
While AI is brilliant at spotting trends, it lacks context and intuition. An AI might see a spike in utility costs and flag it as an error; a human knows there is a geopolitical crisis affecting energy prices. We still need human judgment to validate AI suggestions and provide the why behind the what.
The AI software market is currently akin to the Wild West. Finance leaders reported significant evaluation fatigue, and are struggling to find transparent comparisons between tools that all promise t he world.
Our collective advice for navigating this:
Finally, we discussed the elephant in theroom: job security. When people hear automation, they often hear redundancy.
Effective change management is therefore critical to successful AI adoption. Leaders must frame AI as an evolution of tools, not a replacement for people. Just as Excel didn't kill the accounting profession, it just evolved it, AI is a new skillset to be mastered. Education is the best antidote to anxiety; when teams see AI as a tool that removes the drudge-work from their day, the fear begins to fade.
The month-end close is evolving, but it’s a journey of incremental gains rather than an overnight revolution. By focusingon data quality, maintaining a ‘human-in-the-loop’ philosophy, and prioritisingsecurity, finance teams can turn AI from a buzzword into a competitiveadvantage.
Are you currently piloting AI in your finance function? We’d love to hear your experiences. To continue the conversation, connect with us today.
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