The AI Adoption Gap in Finance and How to Close It
The AI adoption gap in finance is rapidly becoming a defining competitive fault line between organizations. While early adopters are using AI to automate repetitive tasks, improve accuracy, and unlock real-time insights, many finance teams are still stuck in manual, spreadsheet-heavy workflows. This session tackles why that gap exists and, more importantly, how finance leaders can close it—turning AI from a vague buzzword into a practical toolkit for better controls, sharper forecasting, and more strategic partnership with the business.
In this masterclass, finance leaders explore why AI is rapidly transforming the function yet remains underused in many teams, leaving a widening competitive gap between early adopters and cautious followers. The discussion emphasizes that finance is rich in repetitive, rule-based work—AP, spend management, and contract review—that is ripe for automation, freeing professionals to focus on analysis, partnering with the business, and strategic decision‑making.
Pauline Babel, Chief Financial Officer at Spendesk, joins Kevin Appleby, COO and Podcast Host at GrowCFO, to share a practical, experience-based roadmap for AI adoption in finance. Drawing on real deployments—from automating invoice processing and spend categorization to piloting AI in FP&A and discount approvals—Pauline explains how to start small, build trust, set strong governance, and scale AI usage across the team while maintaining rigorous standards for data privacy, accuracy, and human oversight.
Highlights:
- Why the AI adoption gap is emerging in finance and how it’s reshaping competitive advantage
- Practical starting points for AI in finance, including AP, spend management, and contract review
- How Pauline’s team at Spendesk uses enterprise-grade AI platforms (like Dust) to balance innovation with data privacy and governance
- A step‑by‑step roadmap for scaling AI usage—from first pilots to broad adoption and measurable ROI
- Real examples of AI augmenting FP&A work, discount approvals, and productivity across the finance team—not replacing finance professionals
- Key metrics and practices for tracking AI adoption, time savings, accuracy, and business value in the finance function
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