Erik and Justin unpack Paul Rotzer’s AI maturity “eight pillars” and use it to frame what leaders should do after the hype: step back, explore what AI can do, choose a priority problem, then build vision, strategy, governance, literacy, and measurement in that order.

🧭 Conversation Highlights

• AI adoption is a forcing function: excitement about what AI can do often triggers the harder question of what the business should actually solve first.
• Justin argues for a mindset shift from “pick the perfect problem” to acknowledging an unsolved problem set, learning AI capability, then applying it deliberately.
• Governance quickly turns practical as teams hit token limits, spend tracking gaps, and model availability changes during real adoption.
• Early value often starts in communication and as an individual thought partner, but real ROI comes when leaders provide guardrails, education, and space to iterate.

💡 Key Takeaways

• Start with exploration, but don’t skip selection: the ability to do many things can paralyze you if you do not stack-rank what matters.
• Vision and literacy shape what happens next. Without a clear “why AI,” tool knowledge alone will not translate into durable adoption.
• Adoption is iterative: one department, one strategic goal, then replicate. “Go slow to go fast” beats trying to tackle everything at once.
• Token cost governance is becoming unavoidable. Plan for consumption monitoring, model selection, and policy before limits surprise you.

❓ Questions That Mattered

• When leaders see AI capabilities expand, how do they choose problems instead of chasing shiny possibilities?
• Do you treat AI literacy and vision as prerequisites, or as learning that happens after you start piloting?
• Where should a company look first for a beachhead of value across teams like revenue, ops, finance, and internal product?
• Will tokenomics and pricing changes push more companies toward hybrid models like hybrid seat plus usage, or on-prem and open source?

🗣️ Notable Quotes

• “If you can do everything, you can do nothing.”
• “Stop spinning, choose one problem set, learn about AI in general and what it's possible and capable of doing, then choose that problem.”
• “Tokenomics part is going to become part of your governance.”
• “You’re going to pay for the tokens that we consume.”

🔗 Links & Resources

• Listen To Other Episodes Co-Hosted With Justin
• Read the referenced Article