By Jon Hansen | Procurement Insights | January 2026
For years, the AI conversation has been framed as a contest: human versus machine. Who’s smarter. Who’s faster. Who will replace whom.
That framing is not only wrong—it’s holding us back.
Here are three thoughts that may change how you see AI, and why it matters far more than the latest tool announcement.
Thought 1: The Real Failure Was Never the Technology
Back in 2007, I wrote the following in Part 4 of my Dangerous Supply Chain Myths series:
“Besides Colin Powell’s invaluable insight based on his own experiences, the 75 to 85% rate of initiative failure is a result that cannot be ignored. In short, do end-user organizations abdicate their responsibilities for developing sound procurement strategies by looking outward for ‘expert’ guidance rather than calling on the internal resources and experiences that ultimately determine the success or failure of an initiative?”
That question still matters—because the pattern never changed.
Organizations didn’t fail because technology was inadequate. They failed because responsibility was outsourced—first to consultants, then to frameworks, now to AI.
AI doesn’t fix abdication. It exposes it.
Thought 2: Capability Cannot Depend on the “Perfect Storm”
One of the most persistent failures in procurement and transformation has been this unspoken hope:
If we just get the right people, in the right roles, at the right moment…
That is not a strategy. That is chance.
True capability must exist beyond any single individual.
That’s why adding another human strand into the process matters. It demonstrates that outcomes are not dependent on one expert, one hero, or one rare alignment of personalities.
AI, used correctly, provides a disciplinary framework:
- it forces reasoning to be explicit,
- makes assumptions visible,
- documents how conclusions are reached,
- and stimulates productive, human-guided interaction.
Successful communication, collaboration, and outcomes cannot be left to luck.
AI doesn’t remove humans from the loop. It makes the loop unavoidable.
Thought 3: We Learned the Wrong Lesson from Kasparov and Deep Blue
For years, I viewed the Kasparov–Deep Blue chess matches as a contest—human versus machine.
Only later did I see the unintended consequence.
Those events reinforced a competitive mindset, not a collaborative one. They taught us to ask, “Who wins?” instead of “What works better together?”
That framing may be the root of today’s AI-human dissonance.
The industry is still playing chess when it should be building teams.
The Irony Most People Miss
Kasparov himself eventually recognized this.
He went on to pioneer Advanced Chess (Centaur Chess)—where human + computer teams compete together.
His conclusion, after years of reflection:
“The best chess being played today is not by humans alone, not by computers alone, but by human-computer teams.”
That insight should have reshaped the AI narrative.
It didn’t.
The headline “Deep Blue Beats Kasparov” stuck. The collaboration lesson didn’t.
The Shift We Need to Make
AI is not here to replace judgment. It is here to discipline it.
Not to compete with humans. But to structure better human collaboration.
We don’t need smarter machines to fix our problems. We need systems that prevent us from abdicating responsibility—again.
That’s why Phase 0 exists — not to slow down transformation, but to ensure there’s a human in the loop before the loop begins.
That’s the lesson we missed.
And it’s the one that finally changes everything.
Jon Hansen developed Strand Commonality Theory in 1998 for the Department of National Defence, achieving 97.3% delivery accuracy and 23% sustained cost savings over seven years. He is the creator of the Hansen Method and Hansen Fit Score (HFS), focused on preventing the documented 80% implementation failure rate through Phase 0 readiness assessment.
Procurement Insights
Three Thoughts About AI That Will Change Your Thinking for the Better
Posted on January 11, 2026
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By Jon Hansen | Procurement Insights | January 2026
For years, the AI conversation has been framed as a contest: human versus machine. Who’s smarter. Who’s faster. Who will replace whom.
That framing is not only wrong—it’s holding us back.
Here are three thoughts that may change how you see AI, and why it matters far more than the latest tool announcement.
Thought 1: The Real Failure Was Never the Technology
Back in 2007, I wrote the following in Part 4 of my Dangerous Supply Chain Myths series:
That question still matters—because the pattern never changed.
Organizations didn’t fail because technology was inadequate. They failed because responsibility was outsourced—first to consultants, then to frameworks, now to AI.
AI doesn’t fix abdication. It exposes it.
Thought 2: Capability Cannot Depend on the “Perfect Storm”
One of the most persistent failures in procurement and transformation has been this unspoken hope:
That is not a strategy. That is chance.
True capability must exist beyond any single individual.
That’s why adding another human strand into the process matters. It demonstrates that outcomes are not dependent on one expert, one hero, or one rare alignment of personalities.
AI, used correctly, provides a disciplinary framework:
Successful communication, collaboration, and outcomes cannot be left to luck.
AI doesn’t remove humans from the loop. It makes the loop unavoidable.
Thought 3: We Learned the Wrong Lesson from Kasparov and Deep Blue
For years, I viewed the Kasparov–Deep Blue chess matches as a contest—human versus machine.
Only later did I see the unintended consequence.
Those events reinforced a competitive mindset, not a collaborative one. They taught us to ask, “Who wins?” instead of “What works better together?”
That framing may be the root of today’s AI-human dissonance.
The industry is still playing chess when it should be building teams.
The Irony Most People Miss
Kasparov himself eventually recognized this.
He went on to pioneer Advanced Chess (Centaur Chess)—where human + computer teams compete together.
His conclusion, after years of reflection:
That insight should have reshaped the AI narrative.
It didn’t.
The headline “Deep Blue Beats Kasparov” stuck. The collaboration lesson didn’t.
The Shift We Need to Make
AI is not here to replace judgment. It is here to discipline it.
Not to compete with humans. But to structure better human collaboration.
We don’t need smarter machines to fix our problems. We need systems that prevent us from abdicating responsibility—again.
That’s why Phase 0 exists — not to slow down transformation, but to ensure there’s a human in the loop before the loop begins.
That’s the lesson we missed.
And it’s the one that finally changes everything.
Jon Hansen developed Strand Commonality Theory in 1998 for the Department of National Defence, achieving 97.3% delivery accuracy and 23% sustained cost savings over seven years. He is the creator of the Hansen Method and Hansen Fit Score (HFS), focused on preventing the documented 80% implementation failure rate through Phase 0 readiness assessment.
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