AI use in finance to hit 75% by 2026, boosting decision-making

AI is increasingly a decision-making engine, not just a cost-cutter, a KPMG report finds. Active AI use in finance has more than doubled, with 75% of organisations leveraging it for planning, reporting, and analysis, seeing improved decisions.

Artificial intelligence is increasingly emerging as a decision-making engine rather than merely a tool for cutting costs, with organisations reporting the strongest gains in areas such as forecasting, decision-making and responsiveness, according to a KPMG report.

Rapid Adoption and Impact on Decision-Making

The report, based on a survey of 1,013 senior finance leaders across 20 countries and 13 sectors, said active AI use across finance has more than doubled in two years, rising from 30 per cent in 2024 to 75 per cent in 2026. More than three-fourths of organisations are leveraging AI in financial planning, reporting and commercial analysis, while 71 per cent said AI is meeting or exceeding return-on-investment expectations.

The report found that AI's biggest impact is concentrated in judgment-heavy activities. About 70 per cent of organisations reported improvements in decision-making quality, while 71 per cent saw faster decision-making and 64 per cent reported better forecasting accuracy.

Agentic AI Shows Stronger Performance

Agentic AI deployments showed an even stronger performance advantage, with organisations at the orchestrating and multi-agent stages outperforming those still in early planning by 32 percentage points on average, and by nearly 40 points on forecast accuracy and ROI.

Governance and Data Quality Emerge as Key Challenges

However, KPMG said adoption alone does not guarantee value. Governance, controls and assurance readiness are emerging as key differentiators. Organisations capable of producing AI-related audit evidence efficiently reported three to six times the rate of significant improvement compared with those that were not assurance-ready. Yet only 42 per cent of organisations were found to be strongly assurance-ready for AI-enabled finance processes.

Data quality remains another major constraint. Thirty-six per cent of organisations identified improving data quality, integration and system interoperability as their greatest opportunity to extract more value from AI.

The Path Forward: Workforce, Investment, and Governance

On the workforce front, 38 per cent are upskilling existing finance teams, while only 28 per cent are hiring for different skill sets.

KPMG concluded that finance leaders need to direct AI investment towards planning, forecasting, risk assessment and commercial analysis, while embedding governance, measurement and human oversight into deployment.

The report said the competitive advantage will increasingly lie not in whether organisations use AI, but in how effectively they operationalise it to improve decision-making and performance. (ANI)

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