Case Study
The CFO’s AI Checklist: Six Practical Steps
A practical 6-step checklist from GSK’s VP of Finance detailing how CFOs can responsibly deploy AI, eliminate manual bottlenecks, and achieve measurable ROI. Discover how finance leaders can move past the hype, eliminate manual bottlenecks, and execute a board-ready AI strategy without compromising financial governance.
- Topic
- Business Solutions
- Published
- 22 Jul 2026
Chief Financial Officers face a delicate balancing act. With rising costs, tighter cash flow, and high expectations, finance leaders are challenged to remain guardians of financial control while actively driving business innovation. Yet, 71% of finance teams report being slowed down by outdated, manual workflows.
Implementing Artificial Intelligence is no longer optional; the real challenge lies in deploying it safely, responsibly, and at scale.
Based on insights from Riccardo Calliano, VP of Finance at GSK, this executive checklist outlines six actionable steps to transition your finance function from reactive manual work to strategic, AI-driven value creation.
Key Highlights:
The Workflow Bottleneck: 71% of finance professionals report that outdated manual workflows slow down their daily work.
Double Leadership Role: Modern CFOs are expected to simultaneously serve as guardians of control and drivers of business innovation.
Problem-Driven Strategy: AI adoption must start with defining specific business problems, such as cash flow visibility or forecast accuracy, rather than chasing tech hype.
Data Pre-Requisite: AI efficacy depends directly on data quality, requiring end-to-end audits of key finance processes before automating.
Balanced Execution: Enterprise speed requires upfront guardrails co-developed with IT, cybersecurity, and HR to prevent compliance risks.
Expectation Management: Leaders must proactively address job-loss fears and over-inflated expectations by distinguishing short-term efficiency from long-term value.
Agile Piloting: Organizations should avoid monolithic ERP-style rollouts in favor of rapid, sprint-based pilots co-created with business units.
Platform-Level ROI: AI should be treated as a multi-use platform that yields non-linear, exponential returns over time.
Eliminating "Fake Productivity": Saved operational hours must be deliberately reallocated to strategic tasks to realize true ROI.
Immediate High-Value Targets: Month-end reconciliation and financial reporting are ideal targets for initial, low-risk AI automation pilots.
Cross-Functional Alignment: Successful AI integration requires breaking down silos across finance, IT, and operational teams.