2026 KPMG Global AI in Finance Report

The question is no longer whether organizations use AI, but how effectively they translate it into business value. While active AI usage has more than doubled over the past two years, only 23% of organizations report outcomes that exceed expectations, indicating that success depends on more than implementation alone. Leading organizations are distinguishing themselves by applying AI to high-value decision-making processes, establishing robust governance frameworks, measuring impact rigorously, and equipping their workforce with the skills needed to act on AI-driven insights. Together, these capabilities create what can be described as a Decision Advantage.

As finance functions continue to evolve, AI is becoming a core decision-support engine. In this environment, trust — enabled through effective AI governance, controls, and oversight — is emerging as a critical source of competitive advantage.

Four AI in finance priorities for finance leaders in 2026

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Reframe AI around value, not tasks

Direct AI investment toward the areas where it is producing the strongest returns: planning, forecasting, risk assessment and commercial analysis. Prioritize use cases where human judgement is central to the outcome.

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Build measurement into execution

Move beyond tracking KPIs to building the assurance readiness infrastructure that makes measurement actionable. The performance dividend from measurement is real, but it compounds when paired with the controls to act on what the data reveals.

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Treat governance and controls as the ticket to play

Invest in governance, audit trails and evidence capture alongside AI deployment. Organizations with stronger controls are scaling faster and seeing significantly better outcomes. The inverse is equally true: without them, organizations face disruption, regulatory delay, and erosion of stakeholder confidence. Controls enable confidence, and confidence enables scale.

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Shape the total workforce, not just the training

Upskilling is necessary but insufficient. Finance functions need people who can operate at the intersection of organizational intelligence, finance expertise and data fluency, with the ethical judgment, critical thinking and risk management to govern decisions made faster than ever. CFOs should consider how the shape and composition of the workforce will change over the next few years, and put a proper workforce plan in place, refreshed every six to nine months.

These four priorities are interconnected

Decision-oriented AI produces stronger results when supported by robust controls.
Controls are more effective when measurement is embedded.
Measurement only scales when the workforce has the capability to interpret, challenge and act on what AI produces.
That reinforcing cycle drives sustained performance.
Organizations building it are capturing the advantage.

In the Caucasus and Central Asia region, we are also seeing that organizations are increasingly evaluating AI not by the number of automated routine tasks, but by its ability to improve the quality of decision-making. The finance functions that are pulling ahead in our region are those that have moved beyond viewing technology solely as a cost lever and are instead using it as a decision engine for strategic planning and risk management. Ultimately, it is the maturity of how these capabilities are governed and orchestrated that drives sustainable business value from AI.