AI adoption in finance hits 76%, governance and AI-centric operating models key to future edge: KPMG
Artificial intelligence (AI) has reached an inflection point in finance, with 76% of organisations already using it in financial planning. However, while adoption is outpacing organisations' ability to scale AI across the enterprise, the next comp...

The report highlighted that AI delivers its greatest value in finance by enhancing decision-making rather than reducing transaction costs. However, the biggest challenge is governance.
Noting, 76% of organisations are actively leveraging AI in financial planning, it stressed, "Competitive advantage will increasingly belong to organisations that align their finance operating model around AI -- and can sustain that alignment as AI becomes more capable, more autonomous and more deeply embedded in everyday decision-making."
Furthermore, while many organisations are upskilling their existing workforce, only 28% are reassessing the talent profiles needed for an AI-driven future.
As a result, the gap between training employees to use AI tools and building an integrated human-AI workforce operating model remains unaddressed. Notably, human oversight continues to be a critical part of this transition.
"33% of organisations surveyed are increasing human-in-the-loop oversight as a direct response to AI-related concerns," it said.
In finance, where regulatory scrutiny and professional judgement shape every output, human involvement in AI workflows produces more reliable results and builds the trust required to scale.
The report also found that very few organisations are adopting a total workforce approach. While 38% are upskilling finance and internal audit teams for
AI-enabled processes, only 28% are hiring talent with new skill sets, indicating that most organisations are retraining existing employees rather than redesigning the workforce for an AI-driven future.
Apart from this, data fluency is becoming crucial for deploying AI in finance. "36% of organisations identify improving data quality, integration and system interoperability as their greatest opportunity to extract more value from AI in finance," KPMG said stressing, the real challenge is -- finance teams often not knowing "where to start."
"Data fluency is emerging as the most critical capability need: the ability to assess data quality, interpret outputs and communicate findings in terms the business can act on," it noted.
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