Most companies have a board-level AI mandate. Almost none of them have an actual AI strategy. That gap is where RevOps practitioners are living right now, and it's one of the more exhausting places to be. In this episode, Taft Love (founder of Iceberg RevOps) and co-host Camela Thompson get into what's actually happening on the ground: vague executive mandates, the build-vs-buy trap, why data quality matters more with AI (not less), and what organizational discipline really determines whether AI transformation succeeds or stalls.

This is a refreshingly grounded conversation for operators who are tired of the hype and need practical frameworks they can actually use.

Key topics covered:

→ Why "AI replaces headcount" is the wrong frame — and what to use instead

→ The jobs-to-do framework for identifying real AI use cases

→ What Taft's multi-agent project management system actually looks like (and why it wasn't easy to build)

→ Build vs. buy: what you're actually purchasing from a vendor (hint: it's stability)

→ The four organizational blockers that kill AI transformation at small companies

→ What a real AI strategy looks like: outcomes, frameworks, and wide latitude with iron boundaries

→ A free AI-powered RevOps audit tool Taft built with a former Microsoft/Amazon RevOps leader

🎙️ Speakers:

- Taft Love, Founder, Iceberg RevOps — https://www.linkedin.com/in/taft-love/

- Camela Thompson, Co-Host, RevOps Co-op — https://www.linkedin.com/in/camela-thompson/

🔗 Resources:

- Iceberg RevOps: https://icebergrevops.com

- RevOps Co-op community: https://www.revopscoop.com/membership/membership-options

- More podcast episodes: https://www.revopscoop.com/podcast

👉 Join the RevOps Co-op community: https://www.revopscoop.com/membership/membership-options

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