AI in Finance: how adoption differs across France, North America, and Japan
This fall, finance leaders across France, North America, and Japan met at CCH Tagetik inTouch25 events to compare notes on AI. We surveyed attendees to see where teams stand, what's blocking scale, and what would increase confidence to deploy agentic AI across the Office of the CFO.
Responses: France (Sep 23, 147), North America (Sep 17, 79), Japan (Oct 25, 179). The headline: interest is high everywhere, but priorities and pace differ by region.
Where adoption stands today
Most finance teams are early in adoption, with one region edging ahead on scale.
- North America: 86% are exploring or piloting (53% exploring, 33% piloting). Only 4% are scaling across multiple finance functions.
- Japan: 76% are in early phases; 7% are scaling.
- France: 72% are exploring or piloting, and 18% are scaling across multiple finance functions.
France is moving faster into multi-function deployments. North America and Japan remain focused on targeted tests.
What's blocking scale
One barrier dominates everywhere: internal expertise. Beyond that, roadblocks look different by region.
- Internal expertise gaps: North America 51%, Japan 52%, France 43%.
- Regulatory, security, and ethical concerns: France 48%, North America 29%, Japan 19%.
- Unclear ROI for AI investments: North America 37% vs. Japan 26%.
- Funding constraints: Japan 20%, France 18%, North America 10%.
For governance and risk, many teams reference frameworks such as the NIST AI Risk Management Framework. It's a practical base for policies, controls, and accountability models that finance can adopt quickly. See the NIST AI RMF.
What builds confidence in agentic AI
Confidence drivers reflect how each region thinks about risk, proof, and systems.
- North America: Proven use cases top the list (65%). Governance also matters (41%).
- France: Integration with existing CPM tools is the #1 driver (65%).
- Japan: Clear governance and accountability (44%) and stronger internal AI literacy (36%).
Practical moves for CFOs, by region
- North America: Focus on evidence. Pick 2-3 proven use cases with fast payback (forecast variance analysis, cash flow anomaly detection, close-task automation). Use a standard business case template, stage-gate pilots, and publish results for reuse.
- France: Make integration the plan, not an afterthought. Prioritize tight CPM connectivity, data lineage, and security. Work with IT and your vendor ecosystem (including platforms like CCH Tagetik Intelligent Platform) to standardize models, interfaces, and controls.
- Japan: Budget for literacy and pilots in parallel. Stand up small finance-led AI squads, train for prompt quality and data stewardship, and run contained pilots with clear KPIs. A curated catalog of tools can accelerate fit-for-purpose selection. For a starting point, see AI tools for finance.
Global takeaways for finance teams
- Skill up fast: Pair finance SMEs with data engineers. Build a lightweight enablement program for analysts and controllers.
- Codify governance: Define data access, model risk, approvals, and auditability. Map controls to recognized guidance (e.g., NIST AI RMF).
- Prove ROI early: Tie use cases to cycle-time cuts, forecast accuracy lift, and risk-loss avoidance. Track and publish wins.
- Scale with discipline: Move from explore → pilot → scale with MLOps/GenAI ops, change management, and integration standards.
A shared goal, different paths
Finance leaders agree AI can materially improve speed, accuracy, and decision support. The path differs: France is pushing integration and scale; North America wants proof and payback; Japan is prioritizing governance and capability building.
Wherever you are, focus on the next constraint. If it's expertise, train and pair teams. If it's integration, standardize interfaces and controls. If it's ROI, start with proven use cases and measure relentlessly.
Upcoming: Future Ready CFO
Launching by March 2026, the Future Ready CFO report will feature insights from 1,300 CFO decision-makers across North America, Europe, and Japan. Expect clear signals on technology adoption, operating models, and decision-making in the age of AI.
It will spotlight the shift AI brings to finance leadership-what to invest in, how to organize teams, and which capabilities to prioritize next. Keep an eye out and use it as a benchmark to pressure-test your plan for 2026-2027.
Your membership also unlocks:
