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AI in Finance 2026: the report card

The second year of our research. Every survey finding has been tested against interview evidence, and in several places the interviews qualify the survey materially.

How the cohort scored on seven dimensions of AI maturity

We scored each interview from 0 to 5 on seven dimensions, with 3 as the operational threshold: the point at which a practice is embedded and depended upon rather than trialled. The cohort averaged 2.98, clearing the threshold on five dimensions and falling short on two.

Its strengths lie in talent, culture and strategic vision, while its weaknesses are the data foundation and, most clearly, the discipline to state the return that an AI investment is expected to deliver.

Method: a survey of Finance leaders of multinational companies, compared with 2025, and structured interviews with senior Finance leaders across several sectors. Interview subjects are identified by sector only.

Talent and culture3.59
Strategic vision3.50
Deployment breadth3.14
Finance use cases3.09
Governance3.09
Data foundation2.55
ROI discipline1.91
Operational threshold 3.0 
At or above thresholdBelow threshold

What changed in a year

Survey results for 2026 against 2025. The marker shows last year's figure.

Progress so far

56%

report moderate, sustained use of AI in Finance.

42% in 2025. Nobody now reports full integration.

People and change

80%

expect traditional FP&A analyst roles to be substantially automated.

42% in 2025.

Overcoming challenges

53%

cite an unclear return as a barrier, the largest movement in the survey.

6.5% in 2025.

Overcoming challenges

67%

cite data quality and integration as a barrier.

35% in 2025.

People and change

87%

name business storytelling as a priority skill for Finance teams.

81% in 2025.

Overcoming challenges

47%

are very confident about AI in Finance, in the same year that every barrier rose.

19% in 2025.

The skills that matter most are the ones teams lack

Asia Pacific Finance leaders rated each skill for its importance to the business and for their team's current capacity. The widest gaps sit in communication: simplifying complex ideas, tailoring the message, and creating buy-in.

As AI takes on data gathering and first-pass analysis, the value Finance adds moves to explaining what the numbers mean and what the business should do next.

Importance to the businessCurrent team capacity
Understands business operations
Can discuss value drivers
Simplifies complex ideas
Clearly articulates views
Challenges unethical behaviour
Challenges business assumptions
Sets business-aligned goals
Tailors communication style
Creates buy-in

Scale shown from 2 to 5. Source: Global CFO Network, the Finance skills agenda, 2026.

Mark your own report card

Grade your function on the six questions that separated the leaders from the rest. Ask colleagues to do the same and compare: the differences within one organisation are more instructive than the grades.

Your answers stay in your browser and are not sent to us.

DecisionIs AI an expectation in your function, with a consequence attached?
ReturnDo you specify the return and the accountable owner before approval?
CostHave you priced the cost of operating AI at scale?
DataAre you deploying without waiting for a perfect data foundation?
GovernanceDoes your governance enable deployment rather than delay it?
CapabilityHave you rebuilt the apprenticeship through which junior staff acquire judgement?

Bring the findings to your leadership team

Members receive the full report, all thirteen findings, and a walk-through for their Finance leadership team in person or online.