I keep seeing frameworks showing AI technology layers: Machine Learning → Deep Neural Networks → Generative AI → AI Agents → Agentic AI.
These capability stacks ask a seemingly simple question: “Where is your company on this stack?”
But that question creates what I call the “evolution trap.”
The Evolution Trap Explained
The evolution trap occurs when we try to force complex, adaptive organizational behavior into predictable, linear progressions.
It assumes:
- Organizations evolve uniformly through technology stages
- Layer 1 naturally leads to Layer 2, which leads to Layer 3
- Capability progression is predictable and sequential
- Having the technology means you can use it effectively
Organizations don’t work that way.
They’re complex adaptive systems that evolve unpredictably, influenced by culture, leadership, market conditions, resource constraints, and dozens of other variables.
Trying to force them into predetermined technology stacks creates exactly the kind of rigid framework that ignores organizational reality.
What These Capability Stacks Miss
Tech capability stacks answer one question: “What can the technology do?”
They don’t answer the more critical question: “Can your organization execute with it?”
That’s the difference between what I call Layer 1 and Layer 2 thinking:
Layer 1 (Technical Capability): What the software/platform/AI can do
Layer 2 (Behavioral Readiness): Whether your people, processes, and culture can execute it
Here’s what actually happens in most organizations:
🔴 Company deploys Layer 5 technology (Agentic AI)
🔴 Organization operates at Layer 1 behavioral readiness
🔴 Implementation fails (70-95% failure rate per Gartner, Forrester, McKinsey)
The failure isn’t because the technology doesn’t work.
The failure is because the organization wasn’t ready to execute with it.
Case Study: Virginia’s Anti-Evolution Trap Approach (2001-2007)
The Commonwealth of Virginia provides a perfect example of what happens when you DON’T fall into the evolution trap.
From 2001-2007, Virginia built their eVA procurement platform. But they didn’t follow a predetermined technology stack.
Instead, they:
- Assessed behavioral readiness FIRST
- Deployed technology matched to actual organizational capability
- Built readiness iteratively (not following linear progression)
- Continuously reassessed and adjusted approach
- Let organizational evolution guide technology deployment (not vice versa)
Result: 80% adoption rate vs. industry standard 20-30%
Why it worked: They respected organizational complexity instead of forcing it into predictable frames.
Case Study: Virginia Avoids the Trap (2013)
In 2013, Virginia faced the evolution trap head-on.
Another department within the Commonwealth wanted to deploy PeopleSoft’s advanced ERP procurement module to replace eVA. The logic: “We need to climb the technology stack. ERP is more advanced. Let’s deploy it.”
Classic evolution trap thinking: Assume Layer X technology is inherently better than Layer Y, deploy it, expect organization to adapt.
But Virginia’s leadership did something different.
They paused and asked: “Are we actually READY for this change?”
They brought in Forrester to independently assess organizational readiness for the ERP procurement module.
Forrester’s conclusion:
“eVA provides better functionality for procure-to-pay, and better integration… expanding eVA’s integration would have much lower initial investment than a Cardinal procurement roll-out… eVA would have significantly lower costs and lower risks.“
Translation: “Your organization isn’t ready for this technology leap. The ‘advanced’ layer on the stack doesn’t match your organizational reality.”
Virginia killed the deployment. Saved millions.
eVA is still running successfully today (2025), still maintaining high adoption, because Virginia never forced themselves into capability stacks that didn’t match their organizational readiness.
Case Study: Daedong Falls Into the Trap (October 2025)
For contrast, consider what happens when you DO fall into the evolution trap.
In October 2025, Daedong (Korean agricultural equipment manufacturer) faced an $11.4 billion lawsuit for failed procurement system implementation.
What happened?
They deployed advanced procurement technology without assessing whether their organization was behaviorally ready to execute with it.
Classic evolution trap:
- Assumed capability stack progression was the goal
- Deployed technology based on “what it can do”
- Ignored “whether we can execute with it”
- Organization wasn’t ready
- Implementation failed catastrophically
$11.4 billion is what the evolution trap costs when you get it wrong.
The October Diaries Methodology: Escaping the Trap
The October Diaries methodology was specifically designed to prevent the evolution trap.
Instead of asking “Where are you on the technology stack?”
We ask: “What is your behavioral readiness at your current technology level?”
The Hansen Fit Score measures:
- Organizational readiness across multiple dimensions
- Gaps between current capability and required capability
- Cultural factors that enable or inhibit adoption
- Process maturity relative to technology deployment
- Leadership alignment and commitment
- Change management capacity
We assess REALITY (not predetermined progression):
- Where is your organization actually operating?
- What technology matches that reality?
- What gaps need closing before deploying more advanced capability?
- How does your organization need to evolve (not how the stack says it should)?
This isn’t prediction. It’s assessment.
We’re not trying to force organizational evolution into predictable frames. We’re trying to understand organizational evolution well enough to work WITH it, not against it.
Why This Matters Now
AI capability stacks are proliferating because they’re simple, visual, and create clear “you are here” positioning.
But that simplicity is dangerous.
It creates the illusion that organizational transformation is as straightforward as climbing a ladder: Layer 1 → 2 → 3 → 4 → 5.
Real transformation is messy, nonlinear, and organizationally specific.
Before you climb the AI capability stack, you need to assess whether your organization can breathe at that altitude.
That’s what separates 80% adoption success stories from $11.4 billion failures.
The Question to Ask
Not: “Where is our company on the AI capability stack?”
But: “Is our organization behaviorally ready to execute at our current technology level?”
Layer 5 technology + Layer 1 readiness = Failure
Layer 1 technology + Layer 1 readiness = Success
Layer 5 technology + Layer 5 readiness = Success (rare)
Match technology to readiness. Build readiness iteratively. Reassess continuously.
Don’t let the capability stack force you into the evolution trap.
Jon W. Hansen is the creator of the Hansen Fit Score and The October Diaries methodology for assessing behavioral readiness in procurement transformation. He has been documenting procurement implementation patterns since 2007.
Read more: Analysts Gone Wild: Why October’s Enterprise Software Stories Prove Nothing Has Changed Since 2008
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Procurement Insights
The AI Evolution Trap: Why Capability Stacks Force Organizations Into Predictable Frames
Posted on October 27, 2025
0
I keep seeing frameworks showing AI technology layers: Machine Learning → Deep Neural Networks → Generative AI → AI Agents → Agentic AI.
These capability stacks ask a seemingly simple question: “Where is your company on this stack?”
But that question creates what I call the “evolution trap.”
The Evolution Trap Explained
The evolution trap occurs when we try to force complex, adaptive organizational behavior into predictable, linear progressions.
It assumes:
Organizations don’t work that way.
They’re complex adaptive systems that evolve unpredictably, influenced by culture, leadership, market conditions, resource constraints, and dozens of other variables.
Trying to force them into predetermined technology stacks creates exactly the kind of rigid framework that ignores organizational reality.
What These Capability Stacks Miss
Tech capability stacks answer one question: “What can the technology do?”
They don’t answer the more critical question: “Can your organization execute with it?”
That’s the difference between what I call Layer 1 and Layer 2 thinking:
Layer 1 (Technical Capability): What the software/platform/AI can do
Layer 2 (Behavioral Readiness): Whether your people, processes, and culture can execute it
Here’s what actually happens in most organizations:
🔴 Company deploys Layer 5 technology (Agentic AI)
🔴 Organization operates at Layer 1 behavioral readiness
🔴 Implementation fails (70-95% failure rate per Gartner, Forrester, McKinsey)
The failure isn’t because the technology doesn’t work.
The failure is because the organization wasn’t ready to execute with it.
Case Study: Virginia’s Anti-Evolution Trap Approach (2001-2007)
The Commonwealth of Virginia provides a perfect example of what happens when you DON’T fall into the evolution trap.
From 2001-2007, Virginia built their eVA procurement platform. But they didn’t follow a predetermined technology stack.
Instead, they:
Result: 80% adoption rate vs. industry standard 20-30%
Why it worked: They respected organizational complexity instead of forcing it into predictable frames.
Case Study: Virginia Avoids the Trap (2013)
In 2013, Virginia faced the evolution trap head-on.
Another department within the Commonwealth wanted to deploy PeopleSoft’s advanced ERP procurement module to replace eVA. The logic: “We need to climb the technology stack. ERP is more advanced. Let’s deploy it.”
Classic evolution trap thinking: Assume Layer X technology is inherently better than Layer Y, deploy it, expect organization to adapt.
But Virginia’s leadership did something different.
They paused and asked: “Are we actually READY for this change?”
They brought in Forrester to independently assess organizational readiness for the ERP procurement module.
Forrester’s conclusion:
Translation: “Your organization isn’t ready for this technology leap. The ‘advanced’ layer on the stack doesn’t match your organizational reality.”
Virginia killed the deployment. Saved millions.
eVA is still running successfully today (2025), still maintaining high adoption, because Virginia never forced themselves into capability stacks that didn’t match their organizational readiness.
Case Study: Daedong Falls Into the Trap (October 2025)
For contrast, consider what happens when you DO fall into the evolution trap.
In October 2025, Daedong (Korean agricultural equipment manufacturer) faced an $11.4 billion lawsuit for failed procurement system implementation.
What happened?
They deployed advanced procurement technology without assessing whether their organization was behaviorally ready to execute with it.
Classic evolution trap:
$11.4 billion is what the evolution trap costs when you get it wrong.
The October Diaries Methodology: Escaping the Trap
The October Diaries methodology was specifically designed to prevent the evolution trap.
Instead of asking “Where are you on the technology stack?”
We ask: “What is your behavioral readiness at your current technology level?”
The Hansen Fit Score measures:
We assess REALITY (not predetermined progression):
This isn’t prediction. It’s assessment.
We’re not trying to force organizational evolution into predictable frames. We’re trying to understand organizational evolution well enough to work WITH it, not against it.
Why This Matters Now
AI capability stacks are proliferating because they’re simple, visual, and create clear “you are here” positioning.
But that simplicity is dangerous.
It creates the illusion that organizational transformation is as straightforward as climbing a ladder: Layer 1 → 2 → 3 → 4 → 5.
Real transformation is messy, nonlinear, and organizationally specific.
Before you climb the AI capability stack, you need to assess whether your organization can breathe at that altitude.
That’s what separates 80% adoption success stories from $11.4 billion failures.
The Question to Ask
Not: “Where is our company on the AI capability stack?”
But: “Is our organization behaviorally ready to execute at our current technology level?”
Layer 5 technology + Layer 1 readiness = Failure
Layer 1 technology + Layer 1 readiness = Success
Layer 5 technology + Layer 5 readiness = Success (rare)
Match technology to readiness. Build readiness iteratively. Reassess continuously.
Don’t let the capability stack force you into the evolution trap.
Jon W. Hansen is the creator of the Hansen Fit Score and The October Diaries methodology for assessing behavioral readiness in procurement transformation. He has been documenting procurement implementation patterns since 2007.
Read more: Analysts Gone Wild: Why October’s Enterprise Software Stories Prove Nothing Has Changed Since 2008
30
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