The CFO's Guide to
AI Security and Trust
Confidently assess AI-native finance technology while protecting data privacy, maintaining compliance, and ensuring model governance.
Why CFOs need a focused guide for AI trust and security
AI is reshaping financial operations — from AP to forecasting to payments — and CFOs are now accountable for the security and governance of these systems. This guide explains why finance leaders must treat AI evaluation with the same rigor as financial controls.
You’ll learn how the rise of autonomous finance is changing risk, reshaping workflows, and elevating the need for trustworthy data practices across the enterprise. If you’re considering AI for finance, this is the foundation you need before entering any vendor conversation.
Insights from real RFPs, IT and security leaders, and enterprise buying cycles
Built from AI-native AP evaluations and cross-functional reviews, this guide distills the exact questions, risks, and expectations CFOs encounter when adopting AI. You’ll get a window into the real-world patterns IT teams and security leaders flag during vendor assessments — plus the gaps that finance teams commonly overlook.
Inside, we break down the components of secure AI, how to differentiate substance from hype, and the trust signals that matter most in enterprise finance.
Evaluate potential AI vendors with confidence
This guide becomes your practical toolset for making smart, secure AI decisions. Inside is a CFO-ready evaluation framework, a checklist for assessing vendor trustworthiness, guidance for partnering effectively with IT and security, and criteria for validating AI models, data protections, and governance.
Whether you’re exploring AP automation or broader autonomous finance solutions, you’ll walk away with clarity on what “good” AI looks like — and the confidence to champion innovation without compromising trust.