(Corrected Audio) Episode 559: Why AI Projects Get Worse Before They Get Better
The Project Management Podcast
Play audio-only episode
|
Play on YouTube
|
Play on Spotify
data-testid="embed-iframe"
src="https://open.spotify.com/embed/episode/6CF1Se37kk20XTjrkcwRDd/video"
style="width:100%; aspect-ratio:16/9; height:auto; border:0; display:block;"
frameborder="0"
allowfullscreen
allow="autoplay; clipboard-write; encrypted-media; fullscreen; picture-in-picture"
loading="lazy">
Episode Summary
David Luria, author of Flatten the AI J Curve: Your Unfair Advantage in the Race to Enterprise Adoption, brings a practical conversation about what happens when an AI pilot moves into real operational use. Luria, a vice president and business manager at T. Rowe Price and a Six Sigma Black Belt, explains the AI J curve: productivity can fall before it improves, especially as teams learn new workflows, run old and new processes in parallel, and adjust to changing responsibilities. He argues that project managers should set expectations before implementation begins, keep early scope narrow, and use short stepping-stone projects to learn quickly. He also explains why culture matters. AI often removes tasks that people associate with their expertise, so adoption requires more than access to a chatbot. Leaders and project managers need to create room for experimentation, communicate what will change, and help people understand how their roles can shift toward higher-value work. Luria calls for business ownership close to the work, supported by leadership, IT, and risk teams, rather than treating AI transformation as a technology handoff.