Dive Brief:
- AI use in financial services is growing, with three-quarters of leaders reporting that they are using the technology this year, compared with less than one-third in 2024, according to KPMG’s Q3 AI Finance report. KPMG polled more than 1,000 senior finance leaders in 20 countries for the results.
- At least 71% of respondents reported it at least meeting ROI, only 23% say AI is exceeding their expectations. In many cases, adoption of AI is moving faster than organizations’ ability to translate it to enterprisewide performance at scale, a problem that persists across industries, the report found.
- The technology is being used in financial planning, reporting and commercial analysis, according to the report.
Dive Insight:
As businesses reshape financial operations around AI use — in pursuit of better decision-making and more accurate forecasts, tech leaders are tasked with ensuring their people and workflows are primed to use the technology, or risk losing out on its advantages. Skills gaps, not the technology itself, are usually the barrier to success.
KPMG data from this spring showed that for nearly all finance leaders, data security, privacy and risk were the top factors affecting their AI strategy this year. In the Q3 report released last week, finance leaders had four top priorities: reframing AI around value, not tasks, prioritizing AI governance, building measurement of AI into execution and shaping their workforce, not just training.
While technical skills are critical, CIOs must foster human-centric skills to advance AI in their organizations, a PwC report from April found. Those skills included coaching, agility, judgment and empathy.
AI is excelling for finance teams that use it for judgement-heavy tasks, KPMG found, less so in cost-saving areas. Organizations that deploy agentic AI reported stronger performance around forecast accuracy and ROI, and organizations with stronger governance report significantly better outcomes — in some cases three to six times better than their peers.
Data and talent were listed among the top barriers to AI for financial services two years ago, and those problems persist, said Nikki McAllen, global head of finance advisory of KPMG Australia, in the report.
“Functions that will likely pull ahead are the ones that recognize these as distinct problems requiring distinct responses,” McAllen said. “Data quality is not a technology fix. Workforce capability is not a training plan.”
Successful financial teams build the conditions AI requires, such as governance, measurement and workforce abilities.
“Trust, embedded in how performance gets built, is what separates the organizations capturing value from the rest,” McAllen said.
