.png)
There's a narrative repeated at every mining conference, every digital transformation presentation, and every consultancy proposal that lands on a VP of Operations' desk.
The narrative says: "Whoever adopts AI first, wins."
It's a well-intentioned lie. And it's costing wrong decisions in heavy industry.
Why AI Homogenizes Instead of Differentiating
David Wingate, Barclay Burns, and Jay B. Barney, MIT Sloan researchers, put it with clarity worth reading slowly:
"Once AI use is ubiquitous, it will elevate entire markets but will not uniquely benefit any single company."
The conclusion: "AI will be a source of homogenization, not differentiation."
The logic is impeccable. A competitive advantage, by definition, is something you possess that your competition can't easily replicate. AI — platforms, models, tools — is available to anyone with budget. And adoption costs drop every quarter.
The 35% of companies already deploying agentic AI don't have a lasting advantage. They have a temporary one. And the window closes as the other 44% execute their adoption plans.
Thomas Davenport and John Bean, also at MIT Sloan, document that AI investment keeps growing globally, but many executives anticipate a deceleration in 2026. According to Gartner, only 48% of digital initiatives meet objectives.
AI is not a competitive advantage. It's a commodity that gets cheaper every year.
The Real Differentiator
When technology becomes ubiquitous, what differentiates companies is:
- Human drive: The ability to mobilize complex organizations toward ambitious objectives in demanding times.
- Ingenuity: The skill to solve problems no language model has seen before, because they emerged this week in a plant in the Atacama Desert.
- Operational creativity: Finding solutions within constraints best-practice manuals don't contemplate.
- Field experience: Knowing why the textbook maintenance plan is wrong for this specific plant, because you've spent fifteen years on this type of asset.
AI can generate an FMECA. But identifying whether that FMECA makes sense for a specific asset, in a specific operation, with the failure history and field context only an experienced operator knows — that's irreplicable.
Operators with Technology
The correct equation isn't AI versus people. It's operators with technology.
A team of operators with real field experience, armed with specialized agentic software, doesn't compete with pure AI. Nor with consultants without technology. It's a combination neither extreme can replicate.
A team of three operators with specialized agentic technology can execute the analytical work that previously required fifteen. Because each invests their attention where nobody can substitute them, while technology does the repetitive, systematizable work.
The advantage isn't in the technology used. It's in who knows how to apply it.
What This Means for the Industry
The companies that win aren't those with the most sophisticated AI platform. They're those with the most real operational experience, equipped with technology that amplifies that experience instead of trying to replace it.
The right questions for any VP of Operations or CTO:
- What critical decisions depend today on knowledge living only in two or three people's heads?
- What high-value work are your best engineers doing that a specialized system could do, freeing their attention for judgment nobody else can provide?
- When that technology is ubiquitous in your industry — and it will be — what will remain exclusively yours?
AI is the enabler. Operational experience is the advantage.
At ValueStrategy Consulting we're not career consultants. We're operators who built the tools we wished we'd had when we were in the trenches. That experience is what differentiates the agentic software we deploy from any generic platform you can buy with a credit card.
Technology becomes commodity. The judgment to apply it does not.
Sources: Wingate, Burns, Barney — MIT Sloan. Davenport, Bean — MIT Sloan. MIT Sloan x BCG survey. Gartner.
