What World-Class AI in GTM Looks Like | Kyle Norton, CRO @ Owner.com
Topline
Centralization vs. edge experimentation
AJ and Kyle discuss which AI work belongs centralized versus experimented on the edges by teams.
Kyle Norton's AI-enabled revenue team at Owner.com has completely rewritten the economics of what's possible in sales. Kyle joins the show to share why decentralized AI rollouts fail, how to build a core intelligence engine centrally, and why early AI investments must focus on one specific area. The hosts also discuss navigating go-to-market strategy shifts, rethinking RevOps AI integration, and why sales leadership can no longer use budget constraints to delay AI adoption.
Key Takeaways:
-Building a highly functional AI go-to-market strategy requires a perfect mapping of your entire market and deep enrichment, as Kyle Norton notes to "start with data... without that, nothing really works because you can't give the models what they need to make smart decisions or give you good outputs."
-Pushing individual reps to build their own AI workflows yields poor results compared to building central intelligence, which is why Kyle Norton realized that "all of the best things, all of the most impactful implementations were all highly centralized... you just get a completely different result out of it and you can properly enable your whole org to adopt it."
-Companies looking to see immediate ROI from their AI investments need to direct their resources toward the top of the funnel, with Kyle Norton emphasizing that "80% of your AI efforts in your early innings should be pipeline focused... AI is a really good pipeline tool."
Connect with the Hosts & Guests:
Host: Sam Jacobs - https://www.linkedin.com/in/samfjacobs/
Host: AJ Bruno - https://www.linkedin.com/in/ajbruno3/
Host: Asad Zaman - https://www.linkedin.com/in/azaman1/
Guest: Kyle Norton - https://www.linkedin.com/in/kylecnorton/
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Chapters:
00:00 - Introduction
04:05 - Data Foundations for Sales AI
08:14 - Predicting Lead Connect Rates
10:05 - Centralized AI Rollout Strategy
17:20 - Building the Intelligence Engine
22:05 - AI Investments for Startups
28:12 - Changing Comp Plans Quarterly
33:58 - Centralizing AI by Department
37:35 - The Five Ps Decision Framework
39:33 - Focusing AI on Pipeline Gen
43:16 - Salesforce Acquisition Strategy
45:24 - The Reality of Founder Mode
48:01 - The Next Phase of AI Workflows


