AI can feel like magic—predicting outcomes, personalizing communications, streamlining decisions. But in the fiduciary world, magic without guardrails is a ticking lawsuit. Here’s what every sponsor should do before turning on the “AI switch”:
1. Start with your risk appetite, not the vendor’s pitch.
AI’s predictive analytics and digital twins are tempting. But before you deploy, calibrate how much error or bias you accept. Don’t let vendor demos drive the strategy—your fiduciary obligations must.
2. Document your governance at every layer.
Every AI model, training dataset, output, override decision—capture the thinking. When plaintiffs probe, “Why did you trust that algorithm?” your minutes and memos must not go blank.
3. Test for bias, fairness, and “hallucinations.”
Algorithms can replicate systemic bias or “invent” guidance (“hallucinate”) in surprising ways. Have independent audits. Validate recommendations manually in pilot runs before full deployment.
4. Keep humans in the loop.
Even the slickest model should defer to human judgment in edge cases. A chatbot nudging a participant toward a portfolio change? Let a fiduciary reviewer step in when thresholds are crossed.
5. Guard your data and privacy like it’s your last defense.
AI needs data—lots of it. But every data point is a vulnerability. Safeguard participant records, anonymize where possible, control access, and ensure your model can’t be reverse-engineered into private data.
6. Monitor outcomes continuously. Post-deployment, don’t set and forget. Watch for patterns of underperformance, discrimination, or abnormal behavior. If your outputs stray, pause, recalibrate, or shut down features.
7. Disclose transparently—and simply. Your participants don’t need an AI thesis, but they deserve clarity. Explain when AI is used, how, and what oversight exists. Don’t hide “automated advice” behind vague terms.
8. Start small—fewer assets, narrower scope.
Don’t let AI roll out across your entire plan at once. Use it first in lower-risk areas (communications, education, diagnostics). Gain operational trust before letting it touch portfolio or default mechanisms.
AI in retirement plans is not a gimmick, it’s a superpower, if constrained. But superpowers demand discipline, not recklessness. Do the homework now, build defensibility, and treat every AI decision as though it might end up in a complaint. Because in our field, the difference between innovation and exposure is always process.