B2B buyer discovery has evolved fast. What used to start with a sales conversation, now often begins inside an AI agent before a buyer ever lands on your site. Research, shortlists, comparisons, and pricing expectations all surface from a query, and the share of revenue shaped there is climbing every quarter. Companies an agent can't accurately read are losing demand they never see.

This keynote uses the B2B maturity curve to show where your organization stands and what each step rewards, from manual relationships to self-serve portals to AI-assisted discovery. You'll walk away with a framework for deciding where to invest across the curve, a sharper picture of what AI-readiness actually requires, and three questions worth taking back to your team about commercial truth, accountability, and how fast you can change what an agent sees about you.

Takeaways: 

• Where your organization sits on the B2B maturity curve, and where to invest next. A framework for the path from manual relationships, to self-serve portals, to AI-assisted discovery, and what each step rewards (and punishes).
• What AI-readiness actually requires. The two operational pillars beneath the marketing language, machine-parsable structure and real-time product data, plus the three places they break for most B2B catalogs.
• The leadership gap most org charts haven't named. Who owns commercial truth when buyers research your business through ChatGPT, Gemini, or Perplexity before ever visiting your site.
• Three questions to bring back to your team. Your single source of commercial truth, accountability when an agent gets it wrong, and how fast you can change what an agent sees about you.