The annual performance review has been broken for years. AI is forcing HR to finally fix it, or replace it entirely. Most performance processes still run on outdated cycles: infrequent, backward-looking, and dependent on manager memory and subjective judgement calls made months after the fact. AI now makes it possible to surface real-time signals on contribution and growth, but it also raises the stakes on getting the process right. Done badly, AI-driven performance tools entrench bias, reduce reviews to a data readout, and erode the manager-employee conversations that actually drive development. This keynote examines what a genuinely reimagined performance process looks like, one that uses AI to cut admin and surface better evidence while keeping calibration, context, and manager judgement central to the outcome. Attendees will learn how HR leaders are redesigning cadence, feedback flow, and manager enablement to make performance management more continuous, fairer, and useful, without turning it into a black box. Key takeaways: - Learn how AI can reduce the admin burden of performance cycles while surfacing sharper, more timely evidence of contribution. - Explore how redesigning review cadence and format turns feedback into an ongoing process rather than a single backward-looking event. - Understand where AI-generated performance signals need human calibration to avoid entrenching bias or oversimplifying complex work.