AI investments belong on the CFO’s agenda—but decisions about them must be well-thought-out not only from a technological perspective, but above all from a financial one. 💡🏦
As a financial decision-maker, you must clearly assess risk, return, and feasibility. Here is a concise checklist that helps structure decision-making processes and strengthen financial accountability:
1. Strategic Alignment
Assess how the AI project contributes to corporate goals and KPIs.
2. Cost-Benefit Analysis (ROI)
Model scenarios for costs, revenues, NPV, and payback period.
3. Data Readiness
Ensure data availability, quality, and governance.
4. Risk Management & Compliance 🛡️
Assess data protection, bias risks, auditability, and regulatory requirements.
5. Total Cost of Ownership
Include licensing costs, infrastructure, operations, maintenance, and migration expenses.
6. Vendor and Contract Review
Clearly define SLAs, exit clauses, intellectual property rights, and liability issues.
7. Organization & Skills
Plan for internal ownership, skill development, and any necessary outsourcing.
8. Pilot Strategy and Scalability
Stage-Gate approach with clear KPIs for the pilot, evaluation, and rollout.
9. Monitoring & Reporting
Ensure continuous tracking of performance, costs, and benefits.
10. Change Management
Define stakeholder engagement, communication, and incentives for adoption.
A structured, CFO-led evaluation minimizes surprises and increases the likelihood that AI projects will deliver real value. We welcome your feedback or additional insights based on your experience. 💬
#Leadership #AI #Risk Management #Finance