As AI agents accelerate early-stage product work—research synthesis, concept generation, and opportunity analysis—teams risk losing what makes research effective: shared understanding. Individuals can now produce artifacts that once took days of team discussion and critique, resulting in faster outputs but weaker collective insight.

On LinkedIn’s Growth org, we saw this tension as teams adopted AI-powered research, design, and strategy tools. To address it, the UX Research team built a JTBD-based Competitive Analysis workshop paired with an AI teammate—not to replace collaboration, but to scaffold it.

This pair of tools structures how teams jointly explore 0-to-1 opportunities, align on member Jobs-to-Be-Done, and analyze competitive differentiation with an AI agent in the loop.

This session shares a leadership perspective on re-engineering collaboration around AI rather than letting AI erode it. I’ll show how structured, AI-assisted workshops enable both rigor and creativity—and how these practices have elevated the pace, quality, and cohesion of strategic decision-making across teams.