The Hackett Group® Study Shows AI Adoption Rapidly Accelerating Across Core Finance Processes
FP&A, cash disbursements and revenue cycle emerge as the top three priorities for scaling AI, as finance looks to transform performance in 2026
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Current AI adoption levels across finance processes
The study finds that finance workloads are projected to rise 3.2% in 2026, even as head count declines by 2.1% and budgets fall by 1.7%, creating a 5.3% productivity gap. In response, finance leaders plan to increase technology spending by 5.6%, with AI implementation now the fourth-ranked finance priority – up from 16th in 2025.
Against this backdrop, the research shows a decisive shift from AI experimentation to deployment across finance operations. High-volume, transaction-intensive processes are leading the way, delivering fast, measurable impact while laying the groundwork for broader transformation. Specifically, accounts payable is at the forefront, with 33% of organizations already scaling AI solutions, making it the most mature finance process for AI adoption today. Travel and expense management and other high-throughput activities are following closely, reflecting finance leaders’ focus on areas where automation can quickly improve productivity, accuracy, and working capital performance.
AI adoption is also gaining traction in higher-value, judgment-intensive areas of finance. The study finds that 19% of organizations are already scaling AI for planning and forecasting, while another 22% are piloting these use cases. Comparable adoption patterns in business performance reporting and analysis highlight growing trust in AI to augment decision-making in uncertain economic conditions.
“What’s striking is how quickly AI is moving into the core of finance operations,” said
Even traditionally risk-sensitive areas such as treasury, tax and compliance are now entering the AI pipeline. While most organizations remain in the planning stages for these functions, the study points to a clear forward trajectory as agentic AI capabilities advance, and multistep processes can be executed with greater autonomy and control.
Despite this progress, the study highlights that scaling AI successfully will depend as much on people and processes as on technology. Organizational resistance to change is now the top transformation challenge cited by 72% of respondents, while lack of AI talent has emerged as the leading barrier to AI adoption identified by 77% of organizations.
“Technology alone isn’t driving finance transformation,” said
Read the full 2026 Finance Key Issues Study.
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