AI Maturity

AI maturity is how far an organization has progressed in embedding artificial intelligence into its processes, data, people, governance, and decision-making. Organizations usually assess it with a staged maturity model. Early stages involve ad hoc experiments and isolated pilots, while advanced stages have AI embedded across functions and built into how decisions get made.

In business planning and FP&A, AI maturity often follows a clear progression. Teams move from manual, spreadsheet-based planning to AI-assisted planning, where machine learning supports forecasts and variance analysis. The most mature teams use agentic AI to monitor performance and propose actions within defined controls.

Each stage depends on reliable data. Without finance data governance, such as clear data ownership and consistent definitions, AI outputs are hard to trust or audit. That's why a finance team's AI maturity rarely gets ahead of its data maturity.