AI has produced no shortage of demos, claims, and new terminology. But after the initial wave of experimentation, TPRM teams need a more useful conversation: What is actually working? Where is AI improving the process? And where is it simply adding another layer of complexity and cost, when workflow automation could get the job done just as well?

This session shares practical lessons from applying a Hybrid AI approach across the third-party risk lifecycle. Hybrid AI introduces a realistic way of adopting AI that includes giving AI a clearly defined job, grounding it in reliable evidence, keeping it inside a governed workflow, and being deliberate about where human review belongs. We’ll look at the use cases delivering real value at companies today, the ones that remain more gimmick than solution, and the pros and cons of using AI vs. traditional workflow automation.

We’ll also make the case that subject-matter expertise matters more, not less, as AI becomes more capable. AI can gather evidence, summarize documentation, and help teams work through larger portfolios. It cannot decide what good risk management looks like on its own. The strongest results come from combining AI with risk expertise, established processes, and a clear record of how conclusions were reached.

Attendees will leave with a practical view of what AI can do well in TPRM today, what still requires caution, and how to build on those lessons as the technology evolves.

What You’ll Take Away:

• The AI use cases producing meaningful results in TPRM today.

• Common signs that an AI feature is adding novelty rather than value.

• Best practices for grounding AI in evidence, data, and governed workflows.

• Where AI automation can reduce manual effort and where expert judgment remains essential.

• A practical way to evaluate new AI capabilities as the market continues to evolve.