Ask anyone in financial services what dominates the conversation right now, and artificial intelligence comes up almost immediately. For FinTech companies, funds, and financial institutions alike, the future of AI in finance is already here, moving from a talking point at industry conferences to a working part of the financial reporting and audit prep process.
The bigger question firms are wrestling with is no longer whether to use AI in financial reporting. It is how much to trust what it produces, and what that means for the people still responsible for signing off on the numbers.
Reporting Just Got Faster
Across financial services, AI is making routine reporting work much more efficient. Work that once required hours of manual preparation, pulling data, reconciling accounts, building out standard schedules, can now happen in a fraction of the time. Routine reporting that used to eat up a junior team member’s entire week can be largely automated, freeing up capacity for higher-value analysis.
That shift is not confined to any one corner of financial services. Gartner reports that 83% of audit functions are now piloting or actively using AI, with another 12 percent planning to follow within the year. That level of adoption is a signal that AI in audit and reporting workflows has moved well past early experimentation and is becoming standard practice across the industry.
The capability gains go beyond simple automation, too. The ability to analyze large volumes of financial data, spot anomalies, and run scenario-based analysis has grown substantially more powerful than it was even a couple of years ago. Teams that once needed days to stress-test a set of assumptions can now do it in an afternoon.
Speed Without Oversight Is a Risk, Not a Shortcut
Faster is not the same as safer, and that distinction sits at the center of how financial services firms should be thinking about AI-enabled reporting. “The big question becomes, can you trust the output, and how do you review it to make sure it’s right? That’s where the skill and the experience are still very much needed. You still need professionals around you,” said James Lichau, Partner at BPM.
That caution is well-founded. AI tools are only as reliable as the data and prompts behind them, and even strong output still requires a knowledgeable reviewer who can catch an error in judgment, a misapplied assumption, or a nuance the technology missed. Firms that treat AI output as a finished product rather than a well-informed first draft are taking on risk they may not fully recognize until an auditor, regulator, or investor asks a hard question.
Organizations should treat audit readiness as a design principle built in from the start, not a backward-looking checkbox added after the fact. Auditors increasingly expect evidence of what happened, when it happened, and what data supported the outputs relied upon, which means governance and human review need to be built into the workflow itself rather than layered on afterward.
A Trend Playing Out Across Financial Services Firms
The pattern showing up most consistently right now is the widespread use of leading generative AI models to accelerate financial analysis and reporting work. Firms across FinTech, funds, and traditional financial institutions are seeing genuinely strong output from these tools: cleaner first drafts, faster turnarounds, and more sophisticated analysis available to teams that may not have had the bandwidth for it before.
But the value only holds up when someone with real experience is reviewing what comes out the other end. The firms getting ahead are not simply plugging in a tool and hoping for the best. They are building AI automation governance into their process, documenting how AI-assisted work gets checked, and making sure the people responsible for the numbers understand both the strengths and the limitations of the technology they are using.
The Bottom Line
Speed from AI paired with judgment from the people using it is what separates audit-ready financial services firms from the ones scrambling to explain their numbers when the questions get harder. As AI capabilities continue to advance, the firms that invest now in the governance and experience to use it well will be the ones best positioned to earn the confidence of investors, regulators, and clients alike.
How BPM Can Help
BPM serves the financial services industry, helping FinTech companies, funds, and financial institutions build the governance and oversight that responsible AI adoption requires, pairing deep industry knowledge with the technical experience to know when AI output can be trusted and when it needs a second look.
If your firm is exploring how to bring AI into financial reporting and audit prep the right way, reach out to BPM’s Financial Services Group to talk through what that looks like for your business.