AI Strategy
A curated anthology of the best moments on this topic — drawn from across the full video library, ranked by editorial relevance, with direct links to the exact timestamp in every source session.
If your organisation has rolled out AI tools without teaching people how to configure them, it has effectively outsourced judgment to a system calibrated for nobody in particular.
Watch full session ↗Iowa State Course Makes Building a Personal AI Assistant the First AssignmentMost organisations stop at teaching employees how to write a prompt, but Bill Schmarzo argues that training the model itself is what matters — and his Iowa State course acts on that conviction from day one. Every student constructs a personal AI assistant, then feeds it peer-revi
Treating AI as a Productivity Tool Is the Biggest Strategic Error Leaders Are Making, Schmarzo ArguesOrganisations fixated on using AI to work faster are, Schmarzo contends, replicating the trajectory of the spreadsheet — broadly adopted, quickly commoditised, and ultimately generating no sustainable advantage. The more durable path runs through effectiveness first, choosing thr
Schmarzo's 'AI in the Middle' Model Reframes How Sales Forces Are StructuredRather than assigning salespeople to territories by averaging past performance, Schmarzo describes building detailed causal propensity models on both sales staff and customers — mapping each person across dimensions of growth, financial profile, technology readiness, risk toleran
AI Performs Poorly When Optimising for Financial Metrics Alone, Schmarzo WarnsThe core argument Schmarzo makes is that ROI, net present value, and internal rate of return are lagging indicators — measurements of outcomes already past — and that AI models optimising for them are working with the wrong instruments. When a high-school class in Des Moines brai
Design Thinking Workshops That Generate Hundreds of KPIs Are Becoming the Blueprint for AI DeploymentWhen Schmarzo's team tackles a problem like nursing retention, the process begins not with data but with a room of thirty to forty stakeholders — nurses, doctors, administrators, insurers — who frequently disagree with one another. Groups of four or five, deliberately mixed for d
Autonomous AI Agents Need Causality Built In, Not Just Probabilistic Averages, Schmarzo SaysThe central limitation Schmarzo identifies in current generative AI tools is that they are, at their core, probabilistic averaging machines — useful for approximating what people like a given user tend to prefer, but incapable of capturing what that specific individual actually v
Every metric that becomes standard eventually gets gamed — understanding why this dynamic is structural, not accidental, changes how any organisation should think about its data strategy.
Watch full session ↗Competitive Advantage in the Data Age Is a Race to the Next Metric, Not the MeanWhat the Moneyball story ultimately exposes is not the power of statistics but the fragility of any single metric once it becomes widely adopted. Fielding percentage — long used to value defenders and, crucially, to pay them — collapsed as a competitive signal the moment players