What happened
KPMG surveyed 1,013 senior finance leaders across 20 countries and 13 sectors on AI deployment and governance in finance functions. Active AI use in finance has more than doubled since 2024 (from 30% to 75%), with nearly 71% reporting AI meets or exceeds ROI expectations. Strongest returns appear in decision-making quality, forecast accuracy, and responsiveness. However, 36% cite data quality as both their biggest barrier and opportunity. Critically, 93% of US companies plan to deploy or scale AI in finance within 18 months, with half already planning multi-agent AI system orchestration. The assurance readiness gap emerges as a key differentiator: organizations with robust assurance frameworks will outperform peers.
Why it matters
Finance is becoming a primary domain for enterprise AI scaling and multi-agent system deployment. Board and executive teams need to understand that ROI is real but contingent on data quality and assurance readiness—not just AI adoption rates. This report quantifies where finance leaders are winning (decision engines, not cost-cutting) and where governance gaps remain (workforce readiness, system interoperability).
Action needed
Audit your finance function's data integration and assurance frameworks now. Brief the CFO and board on the assurance readiness gap, and commission a three-month scoping project on multi-agent AI governance before scaling orchestrated systems.