The AI business case for the finance team: costs, ROI and a 90-day pilot

Global reference

• Scope: CFOs, finance directors and transformation leads
• Topic: Building and testing the case for AI in finance
• Evidence: Gartner survey of 204 finance leaders, March 2026

Why a business case matters

Gartner found 66% of finance teams using AI report efficiency gains, but 63% said implementation was slower than expected in 2025. Its advice: measure realised value, not the number of tools.

Costs to include

• Licences and usage charges, which can rise with volume.
• Integration with the ERP, bank and data sources.
• Data clean-up, often the biggest hidden cost.
• Staff time for testing, training and review.
• Governance: security review, legal review and audit.

Benefits to measure

• Hours saved per process per month.
• Days taken off the close.
• Error rates and rework.
• Working capital: faster collections, fewer duplicate payments.
• Better decisions, measured through forecast error or time to answer.

A 90-day pilot plan

• Days 1 to 15: choose one process, record a baseline and agree success measures.
• Days 16 to 30: set up the tool, connect data and agree controls with internal audit.
• Days 31 to 75: run in parallel with the current process and log every exception.
• Days 76 to 90: compare results with the baseline and decide to scale, change or stop.

Red flags

• No baseline, so no proof.
• Vendor demos instead of your own data.
• No named owner after go-live.

What to do now

• Pick a pilot where volume is high and judgement is low.
• Put the stop decision in the plan from day one.
• Report results in money and hours, not features.

Our take

A small, measured win beats a big, vague programme. Use the first pilot to build the method, then repeat it.