Why AI Success Creates More Work Than Expected
AI pilots are designed to prove that the technology works, yet they rarely expose the infrastructure, data, ownership, process changes and permanent costs required when it does. Every successful pilot contains a miniature operating model, and CIOs should understand exactly what they are bringing through the gate.
The AI Lesson My Great-Great-Grandfather Learned in 1883
According to highly questionable Winter family history, industrialist Augustus Milton Winter was investing in enterprise AI before most factories had electricity. His experience captures a very current problem: extraordinary technology can generate endless possibilities while leaving leaders surprisingly unclear about which ones deserve action.
The AI Map Nobody Really Agrees On
AI categories sound clean until you try to attempt to draw them. This article explores how Consumer AI, Enterprise AI, Generative AI, Agentic AI, Traditional ML, Industrial AI, and Physical AI actually overlap, and why the messy spaces between them may matter more than the labels themselves.
The Age of Professionally Produced Mediocrity
AI can make almost anyone look competent now, which means competence itself is becoming a terrible competitive advantage. This is about using AI everywhere without letting it sand away the weird ideas, judgment, conviction, and fingerprints that actually make your work yours.
Is Industry 4.0 working?
For more than a decade, manufacturers have invested heavily in the technologies of Industry 4.0, yet U.S. manufacturing productivity has barely moved. So is Industry 4.0 actually working, or are we measuring its impact in the wrong way?
Why More AI Use Cases Can Produce Less AI Value
AI is creating more opportunities than most organizations could possibly pursue, and that may be the real strategic problem. The companies that create the most value from AI may not be those with the most use cases, but those disciplined enough to choose where AI matters disproportionately and concentrate their resources there.
You Can’t Lead at Everything
Every company wants better products, closer customers, and greater efficiency. The hard part is deciding which one you will actually build the business around.
What Happens After AI Does the Work
AI can now get us remarkably close to finished in seconds. The strange consequence is that the small amount of work left over may increasingly contain almost all of the judgment taste context and expertise that actually make the result valuable.
Prompting Gets Too Much Credit
We keep treating prompting as the measure of AI skill because it is the easiest part to see. The real advantage sits underneath: bringing the right context, applying judgment, knowing the domain, and framing the problem well enough that AI is solving something worth solving in the first place.
What Shel Silverstein Taught Me About the Smart Factory
What can a childhood favorite like Where the Sidewalk Ends teach us about the smart factory? More than you might expect, especially when it comes to remembering that intelligent technology alone does not create an intelligent operation.
Everything Matters. That’s the Problem.
Companies rarely struggle because they lack good ideas. They struggle because everything becomes a priority, and real strategy requires the discipline to decide what gets attention, what gets delayed, and what disappears entirely.
What Industry 4.0 Scale Actually Requires
A successful pilot proves that the technology can work. Scaling it requires something far more difficult: a dependable operating system of data, context, decisions, workflows, and standards that can survive different people, equipment, shifts, and plants.
Where AI Is Really Taking Hold Across the United States
AI may be accessible everywhere, but the talent, infrastructure, research capacity, and business readiness required to create real value remain highly concentrated. This article explores which U.S. states appear best positioned to lead, why Texas is close to the top tier, and where the map could shift next.
The Hardest Thing to Change Is the Thing That Still Works
The things most resistant to change are rarely the ones that are obviously broken. From outdated business processes and technology to careers, habits, relationships, and parenting, the real challenge is recognizing when something can still work while no longer being the right answer.
When Will Technology Actually Matter? The Two Clocks of Industrial Innovation
Technology impact depends on two clocks: when a technology becomes viable and when a company completes the prerequisites needed to use it. Reflecting on the WEF Intelligent Industrial Operations Outlook 2026, I explore where the timelines may be right, which technologies I would move and why the same future will arrive at very different times for different companies.
The Architecture Diagram Nobody Wants to Draw
Technical debt is rarely just an old system or outdated technology. It is the hidden architectural complexity that makes every new project slower, harder, and more expensive than it should be.
A Fine Vintage of Bad Transformation Decisions
What if corporate transformation initiatives were wines? A fictional trip to Château de la Transformation reveals four suspiciously familiar vintages filled with endless pilots, excessive hype, commitment issues, and enough pivots to make even a sommelier dizzy.
Thinking Harder Is Not the Same as Thinking Better
AI is making answers faster, cheaper, and nearly unlimited. The real advantage now belongs to people who can challenge assumptions, reframe the problem, and ask questions that lead somewhere genuinely different.
Everyone Wants the Last Domino
Everyone wants autonomous operations, intelligent agents, and self-optimizing factories. But industrial AI success does not begin with the last domino; it is built by standing up every capability that makes it possible.
Your Technology Is Only as Simple as Your Business
Complexity does not arrive all at once. It builds through one exception, approval, workaround, and compromise at a time, until the business can no longer explain why it works the way it does.