Report
Finance is changing - here's how to stay ahead
Finance teams are experimenting with AI, but most lack the formal training to use it effectively. Close the gap between adoption and capability with a practical roadmap for building AI literacy and preparing your team for autonomous systems.
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Why it matters
As AI evolves toward powerful agentic systems, finance teams need structure – including formal training, clear incentives, and a blend of technical and human skills to manage these systems responsibly.
AI adoption is accelerating faster than the talent needed to deploy it.
What's inside...
- Understand the AI landscape: Learn the practical differences between ML, generative AI, LLMs, and agentic systems – and when each matters for finance workflows like forecasting, variance analysis, and scenario planning.
- Master prompting for agentic AI: Discover how to frame clear, recurring missions that let AI agents handle multi-step tasks automatically while you focus on interpretation and strategy.
- Identify critical skills for your team: Get a concrete breakdown of the hard skills (data transformation, predictive analytics, prompt engineering) and soft skills (business partnering, ethics, collaboration) that separate high-performing AI-enabled finance teams from the rest.
- Build a sustainable upskilling program: Follow five research-backed principles to make training strategic, embed it across all leadership levels, and create an ecosystem that turns individual learning into team-wide capabilities.