10 AI takeaways for CFOs: What finance professionals need to know

The inaugural AI for CFOs conference, hosted by The Economist in March 2025, brought together global finance and technology leaders to explore the evolving role of AI in finance. From assistants and automation to skills, strategy and scaling, these 10 insights are designed to inform, inspire and support Chartered Accountants — whether you're shaping strategy or just starting your AI journey.

10 key takeaways from AI for CFOs 2025

1. Start with assistants, move to agents when ready

Many finance teams are beginning their AI journey with assistants—tools that summarise, support and streamline such as Microsoft Copilot or OpenAI’s ChatGPT. PPD, a global clinical research organisation, for example, has introduced an AI Academy to help staff confidently use prompts and simulate earnings calls for dress rehearsal challenges. As capability builds, organisations can explore AI agents—autonomous systems that carry out tasks—like JLR’s, a global car manufacturer, solution for rolling up figures from over 60 countries.

Begin with tools that assist. Explore automation once you have the right data, training and trust in place.

2. AI in finance is a business transformation—not just a tech initiative

Successful AI programmes go beyond automation—they reshape how finance teams deliver value. Tech and finance must work side-by-side. Agile approaches suit early development, while secure deployment often needs a more structured rollout.

Bring finance and tech teams together early. Align AI with wider transformation goals.

3. Focus on productivity gains—AI can remove effort, not just speed it up

AI isn't just about streamlining steps—it can help remove them altogether. GSK, a global pharmaceutical company, is developing an AI tool to support investment cases, reducing manual effort and improving insight.

Revisit your finance workflows. What can be simplified or removed with AI support?

4. Empower your people—skills are the difference-maker

Organisations like PPD and NatWest, a UK financial services company, are investing in hands-on learning through AI academies, workshops and gamified tools. This approach is building confidence and capability across finance teams.

Encourage learning and experimentation in a safe environment. Confidence builds with use.

5. Prioritise pilots that scale

Many teams fall into a pattern of endless experimentation. The key is focus. SAP, a global enterprise software company, runs hackathons—but ensures follow-through with implementation plans. Scale matters!

Choose pilots that solve clear business needs and can be scaled responsibly.

6. Keep guardrails in place—trust and accountability matter

AI systems, particularly those involved in financial decision-making, need oversight. Internal tools can  have humans in the loop. Public-facing or customer interactions must require even more scrutiny .

Establish clear accountability and review practices before rolling out AI widely.

7. Rethink the skills and shape of finance teams

AI is prompting finance leaders to ask new questions—about Application Programmable Interfaces (APIs), data lineage, and workflow design. The expectations of a finance professional are evolving accordingly.

Update team capabilities to include digital fluency. Support ongoing development and curiosity.

8. Buy or build? Make the right call for value

If AI gives you competitive advantage, consider building. If it’s standardised, buy! 

Review the market first. Build where it adds strategic value.

9. Use AI where data quality varies

While some finance functions require perfect data, others allow flexibility. Forecasting and optimisation tasks can be managed with 80–90% data completeness.

Match your AI use case to your data quality. Start where AI can deliver value even with imperfect inputs.

10. Make finance data easier to access and understand

Increasingly, finance teams want to ask questions and get answers from their data—without relying on analysts. Tools from firms like JP Morgan, a global financial services company, are enabling more natural interactions.

Adopt tools that allow users to explore financial data in intuitive ways—bringing insight closer to decision-making.

Final thought

AI isn’t replacing finance professionals—it’s reshaping their roles and the value they can bring. These takeaways offer a practical starting point for CAs to explore, question and lead with clarity, confidence, and curiosity to take advantage of the benefits of AI.