Finance Technology: The Tools-First Model for CFO Decision Support

1. Shift staffing models toward digital product development. Transition from hiring more business partners to building digital product teams with roles like AI product managers and knowledge engineers.

2. Adopt a product-oriented mindset. Prioritize usability, continuous feedback and iterative improvement to ensure tools deliver value and drive adoption. Focus on user experience, intuitive interfaces and ongoing training for business users.

3. Choose accessible finance technology for tool development. Select finance technology, such as agentic coding tools and low/no-code solutions, that staff can easily use to accelerate tool-building capabilities for decision support.

• Decision support is delivered primarily through AI-powered, finance-built tools.

• Business leaders can independently model scenarios and receive recommendations through finance-built tools.

• Natural language interfaces make sophisticated analysis accessible to business decision makers.

• Real-time feedback helps finance teams continuously improve tools.

• Digital product teams manage tool development, adoption and improvement.

• Context engineering ensures tools reflect unique organizational needs.

• Reliance on IT for tool development is minimized to avoid bottlenecks.

1. Work with IT to create a digital sandbox for finance tool-building exploration.

2. Retrain finance business partners to focus on teaching and need-sensing.

3. Begin storing organizational context (e.g., meeting transcripts, emails) for future AI use.

4. Pilot a tool where decision support demand is high and analysis is repeatable.

5. Select agentic coding or low/no-code platforms aligned with team skills.

6. Measure tool performance and user adoption continuously.

7. Gather user feedback to drive iterative improvements.

8. Expand tool deployment as adoption and effectiveness grow.

AI has ushered in the biggest transformation to finance since the digital spreadsheet, requiring CFOs to act as catalysts for fundamental change by leading the shift from legacy systems and mindsets to an agile, AI‑powered finance function. That vision marks the starting point of a broader journey CFOs must navigate to fully deliver on the mission‑critical priority of leading the shift to AI-first finance. 

The steps in that journey include:

• Redesigning finance teams, roles and ways of working to maximize AI’s benefits. This includes shifting responsibilities, updating talent profiles and evolving workflows so the function captures transformational — not just fractional — productivity gains.

• Reviewing validated finance AI use cases and applying best practices for identifying, prioritizing and piloting new opportunities. CFOs should also assess emerging vendors that can support evolving finance needs as use case complexity grows.

• Assessing digital and technical capabilities required for successful finance AI implementation. That means deploying emerging best-practice solutions to build both the systems and the people capabilities needed to accelerate adoption and scale value.

• Creating a finance AI roadmap that builds value-added capabilities while delivering measurable ROI. CFOs should ensure the roadmap explicitly ties automation, efficiency and potential headcount displacement to clear financial outcomes.

• Learning how to approach build‑versus‑buy decisions for finance AI solutions. Understanding where vendor capabilities lead or lag CFO expectations helps determine which capabilities are best sourced externally and which should be developed in‑house.

For more on how Gartner helps drive success on this and other mission-critical priorities for CFOs, speak to us today.