The AI Adoption Gap in Finance and How to Close It скачать в хорошем качестве

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 remain stuck in manual, spreadsheet-heavy workflows. This session explores why that gap exists and, more importantly, how finance leaders can close it. The goal is to turn AI from a vague buzzword into a practical toolkit for stronger controls, sharper forecasting, and more strategic partnership with the business. In this masterclass, finance leaders examine why AI is rapidly transforming the finance function yet remains underused across many teams. This has created a widening competitive gap between early adopters and cautious followers. The discussion highlights that finance is rich in repetitive, rule-based work such as accounts payable, spend management, and contract review. These areas are well suited for automation and allow finance professionals to focus more on analysis, business partnering, 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-world deployments, including automating invoice processing and spend categorization and piloting AI in FP&A and discount approvals, Pauline explains how to start small, build trust, establish 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 is reshaping competitive advantage Practical starting points for AI in finance, including accounts payable, spend management, and contract review How Pauline’s team at Spendesk uses enterprise-grade AI platforms such as Dust to balance innovation with data privacy and governance A step by step roadmap for scaling AI usage from initial pilots to broad adoption and measurable ROI Real examples of AI augmenting FP&A work, discount approvals, and productivity across the finance team without replacing finance professionals Key metrics and practices for tracking AI adoption, time savings, accuracy, and business value within the finance function