diffusion-of-innovations Reading the Room: Where Your Organization Actually Is on the AI Curve Most organizations are misreading their AI maturity, measuring activity instead of capability. Use Rogers' Diffusion of Innovations and the AI Adoption Maturity Ladder for a more honest assessment.
data Data Is Not the Goal: The Knowledge-Insight-Action Chain Data isn't the finish line – it’s just the starting point. Unlock its true value by focusing on the Knowledge-Insight-Action chain and ensuring each step delivers tangible results.
AI-native AI as Organizational Foundation, Not Feature Is AI a feature you are adding to your organization or a foundation you are building it on? The answer sets the ceiling on what AI can return, and the reengineering era already showed us why.
technology-adoption Rogers' Curve Is the Best Diagnostic Tool You're Not Using Rogers' Curve—the bell curve of innovation adoption—isn’t about predicting the future, but diagnosing where your organization stands relative to the market. It's a powerful tool for strategic decision-making you should be using.
AI The 2x2 AI Impact Matrix: What to Do Based on Where You Are Two questions decide what to do about AI for any role: how much time does AI actually compress, and is demand or execution the constraint? The four combinations produce four different prescriptions, and applying the wrong one is expensive.
AI Two Ways AI Changes Your Job: Demand-Limited vs. Collapsable Tasks Jobs are bundles of tasks, and AI hits the bundle unevenly. Demand-limited tasks call for role evolution and collapsable tasks call for role redefinition. Confusing the two is a reliable path to the wrong investment.
AI Why Now: The Capability-Cost Inflection Point Hype is a poor discriminator: every real technological revolution arrived with a bubble attached. What separates AI from Web3 and the metaverse is the capability and cost evidence, and that evidence is already on the books.
AI-adoption The AI Adoption Maturity Ladder: Which Rung Are You On? Most organizations sit on rung two of the AI adoption ladder and believe they are on rung three. The gap matters because the interventions that work at each rung differ, and the most reliable diagnostic is what happens when AI fails.
AI Labor Compression: The Right Economic Frame for AI Replacement is the wrong frame for AI and the workforce. Labor compression, the reduction of hours required per role, turns a binary fear into the strategic question that matters: what happens to the freed capacity?
AI Not That GPT: AI as a Generally Productive Technology Economists were using the acronym GPT decades before OpenAI. Reading AI as a general purpose technology, in the lineage of electricity and the internet, changes the questions leaders should ask and the time they have to ask them.