The use of artificial intelligence has long had a sense of inevitability among large organizations. When that future would take hold, however, no one knew for sure. Now, as technologies and capabilities expand, finance leaders report a growing investment and expectation of AI in the coming year.

In other words, that inevitability has arrived. Only those that invest in the technologies effectively will benefit from their impact.

These are some of the findings from KPMG’s “AI in financial reporting and audit: Navigating the new era” survey, which asked 1,800 financial leaders a series of questions regarding companies’ use of AI, and planned investment in the years to come. More than 70% of companies currently use AI in reporting – but 100% expect to incorporate it soon.

Much of this investment focus will shift towards generative AI (GenAI). The survey found that 19% of organizations prioritize the technology today. That’s expected to significantly increase to 58% by next year, while 97% plan to incorporate or pilot GenAI within the next three years. What was holding some organizations back? Respondents to the survey indicated their top concerns include data security and privacy, limited AI skills and talent, gathering relevant and consistent data, and inadequate funding. 

What value do AI leaders experience in the financial reporting space? Imagine you have a talent gap, and the employees you have hired are in the top quartile of financial reporting, but you need more help. The new hires may not have the level of experience you need in reporting. But with gen-AI support, the technology can help ensure they operate at that heightened level. “It drives the biggest benefit in the people who have the least capabilities in many areas,” said Edward Moran, Managing Director of the Audit Innovation Group at KPMG.

How you invest and where you invest in AI matters to realize such a benefit. Here are just a few ways in which organizations can approach generative AI moving forward to ease the transition.

Double Check the Narrative

When analyzing results, it’s not a set-it-and-forget-it matter yet when using any AI tool. Instead, use of the technology requires recognizing that it can create an output – but the output may not match your needs.

For instance, if your team asked AI to distill a 100-page legislation into a one-page synopsis, it will do so. In fact, it may look fantastic on the one-page.

However, there is a human element required that involves a check for accuracy. AI provides a beginning for the analysis. But even with those caveats, the benefits that AI can bring to reporting are tremendous. Of those surveyed who were “AI leaders” in financial reporting, 42% saw enhanced staff skills due to AI assistants, compared to 31% for those in the beginning stages of implementing AI. The ability to predict trends and impacts was 11 percentage points higher for AI leaders, of which 62% reported the benefit. AI leaders also cited a better ability to identify data outliers and anomalies at a 31% rate, compared to 21% for beginners.

The outputs of AI can create narratives about your results, which you and your team have never thought about or realized. This can open your eyes to opportunities and value that the team and reporting brings, beyond what you typically can see with your own eyes.  

The team then must ensure the narrative makes sense for your organization.

The Data STILL Matters

One of the most pressing barriers to increasing investment into AI tools, according to the survey, is gathering relevant and consistent data. Last year, 30% of respondents cited this concern, which rose to 44% in 2024. It’s among one of the highest increases, year-over-year, lagging only to concerns over security.

“These systems run on large volumes of data, so getting good, trustworthy data quickly is key to its success,” said Moran.

It’s not just enough data, but data that has the right provenance or accuracy. For example, data that is stored in PDFs or other difficult to read tools, could pass through the organization, possibly undetected or even altered.

Siloed organizations face more risk in this scenario. AI needs large volumes of data, which is more clustered in siloed organizations that have barriers in place to prevent sharing of information.

“Difficulty accessing trusted, recent and relevant data is very challenging for companies, and I think it would become increasingly challenging as more companies start to adopt GenAI,” added Moran.

Finding the Right Talent

There’s another important AI barrier that saw a significant jump year-over-year in the survey, and that’s the recognition of limited AI skills and talent available to finance teams. This went from 40% citing it as a concern in 2023 to 46% this year. It adds to the overall issue of financial talent in the CFO’s office, a multi-year trend that predates AI.

The difference is that many leaders hope that AI can replace certain talent gaps – but that will not likely solve the concern. Instead, it requires the right infrastructure in place to benefit from AI. The infrastructure includes the talent.

“You could be spending money on AI, but if you don't spend in other important areas, like hiring the right talent, you're not going to get the return you were expecting from your investment,” says Moran.

Without that investment, you may pull the wrong narratives from the AI tool, you might have poor data feeding the system or you could receive solutions, but to the wrong problem. It’s an opportunity for leaders to embrace the technology and find the solutions that will drive results into the future. The survey found that US AI leaders are best equipped to overcome these barriers by taking actions like developing principles for utilizing AI, ensuring that tech leadership is involved in systems integration discussions and piloting AI initiatives to validate ROI, just to name a few.

While barriers exist, with solutions like those in place, they can be mitigated, helping more companies reap the benefits of AI leadership, and thereby expanding the ability of the technology and the results that financial leaders and auditors glean from the data.

It’s a future that AI financial leaders embrace today by understanding the narrative, managing the data and building the right team.

For more information on how auditors and financial leaders incorporate and view AI adoption, download AI in financial reporting and audit: Navigating the new era.