Stephanie Douglass

As AI becomes the interface to organizational knowledge, research no longer informs one decision; it feeds systems shaping thousands. Yet AI cannot judge nuance, detect bias, or question methodology. This session reframes researchers as the conscience of AI, ensuring data is real, representative, and trustworthy, and that AI learns from the right answers. Key Takeaways:  1. Reframe your role from data provider to trust infrastructure in an AI-driven org. 2. Rigor, representativeness, and bias control are what AI lacks. Turn that into influence. 3. Leave with mindset shifts to keep MR relevant, influential, and irreplaceable in AI.