If your organization’s HR leaders are keeping up with the times and the technology, they’re considering where, when, and how to incorporate artificial intelligence into their employee benefits ecosystems. Most legacy solutions are plugging AI features into their platforms, and there are innovative native AI vendors starting to make a splash in the marketplace, so when it comes to your financial evaluation and sign-off, make sure that you’re ready to play your part in helping to manage the unique risks of AI.
Protecting the organization from legal and ethical harm is at the heart of AI governance, and CFOs bring an important perspective to safely driving business value with AI. According to IAPP and Credo AI, 77% of organizations are already working on AI governance, a number that climbs to nearly 90% for those already using AI. PwC's research adds a sharper point for finance leaders specifically: companies that lead in AI are 1.5 times as likely to have a cross-functional AI governance board in place.
Here are 10 questions worth asking before you approve the budget line, and the short answer to each.
Ask for a dollar figure tied to a specific budget line, not a vague promise of "efficiency." A vendor who can't tell you the payback timeline hasn't done the work to earn your sign-off.
Some vendors' default terms allow client data to train a model that other customers are talking to. That's a contract term to negotiate out, not a feature to accept as standard.
"Won't train on it" and "won't retain it" are two separate promises. A vendor can make the first while still storing your data somewhere, so ask whether retention is a contractual guarantee or just a stated policy.
A hallucination in a benefits context isn't a UX glitch. An incorrect eligibility or coverage answer can mislead an employee and create real financial exposure for you. Ask whether the vendor uses Retrieval-Augmented Generation (RAG) so every answer is restricted to approved plan documents and cited back to a source.
A well-architected AI tool should function as an ERISA ministerial service provider. It should point to what's already stated in approved plan documents and not exercise independent judgment that carries fiduciary weight. If a vendor can't clearly answer how they're classified here, that's a red flag.
Encryption, tenant isolation, and a clean independent pen test are baseline expectations, not differentiators. Vendors need to produce evidence (e.g., a report, a certification, continuous monitoring) instead of assurances to take on faith.
Your protections are only as strong as the weakest subprocessor in the vendor's chain, which includes the cloud host, model provider, and beyond. The same privacy and security terms you negotiate should flow through contractually to every one of them, or the liability sits with you regardless of what the vendor promised.
Most AI tools are designed to sit on top of existing systems like HRIS and benefit portals rather than replace them. A vendor that requires a full systems overhaul is the exception, and that exception has a real cost you should be pricing in before you approve anything.
Don’t assume that everything simply disappears. Ask for a documented data destruction process (e.g., stored documents, chat logs, backend data stores) because liability doesn't end when the contract does unless that's spelled out.
Who approved it, on what basis, and what was the criteria — is that documented, or does it live in someone's inbox? A decision without a paper trail is a decision you can't defend in an audit.
These 10 questions are just the surface, and none of them are questions Finance should be answering alone. Partner with your HR leader and/or benefits consultant to stand up (or formalize) an AI governance committee, and use the AI Buying Committee Field Guide to run it well. It walks through best practices for building the committee, a vendor scorecard built on NIST and ISO standards, a security and privacy checklist you can run against any vendor side-by-side, and a sign-off form that documents exactly who approved what and why.
Download the full AI Buying Committee Field Guide!