What do Linus Torvalds’ warning, Google’s 3,000 new AI courses, and the latest capital market shifts all have in common? They signal the same truth the procurement world has been slow to confront:
We don’t have a technology problem. We have a sequencing problem.
The industry keeps producing more tools, more dashboards, more training, more copilots — yet fewer than 5% of organizations ever achieve measurable ROI from AI or digital procurement initiatives. The hype accelerates, but the outcomes don’t.
Why? Because the market is still trying to automate before it aligns.
The AI Illusion
Google’s new “Skills” platform is impressive: 3,000+ free AI courses, labs, certificates, and hands-on learning content from DeepMind and Gemini. It will mint an army of technically-trained professionals who know how to use AI.
But here is the uncomfortable reality:
Technical skill alone doesn’t produce adoption, outcomes, or organizational movement.
You can train 100,000 people to use AI — but if the underlying behaviors, incentives, data assumptions, workflows, and decision rights remain misaligned, success rates will stay exactly where they are: in the single digits.
Why AI Fails in Procurement
The pattern is painfully consistent:
- Teams deploy automation into processes that are misaligned or adversarial
- Functions don’t share incentive structures
- AI outputs go unverified or ignored
- Technology becomes shelf-ware
- Leaders mistake activity for transformation
AI doesn’t fail in the data. It fails in the dialogue.
Most organizations are still automating yesterday’s dysfunction at scale.
The Missing Sequence: Align → Prove → Scale
For 27 years, across public and private sector transformations, one lesson has stayed constant:
Automation should be the reward for alignment — not the substitute for it.
The successful sequence is:
- ALIGN (Human + Structural Readiness)
Shared understanding, shared incentives, and strand-level transparency
- PROVE (Lighthouse Use Case)
Small, measurable win that verifies behavior and builds credibility
- SCALE (Automation + AI)
Automate only what has already been proven to work
This is the architecture behind RAM (1998), Hansen Fit Score (2015), and The October Diaries (2025) — models designed to codify readiness, eliminate multi-model error, and ensure AI supports decision-making instead of replacing it blindly.
Capability without readiness is not innovation. It’s theater.
Evidence Over Hype (DND → NYC Transit → Capital Markets)
Real transformation isn’t theoretical. When alignment came first:
- 51% → 97.3% next-day delivery in ~3 months
- 23% reduction in COGS over 6–7 years
- FTE load from 23 → 3 in 18 months
- Model replicated across environments (e.g., NYC Transit)
As the recent capital markets “report card” shows, the world is finally admitting it: the tech-first era didn’t work.
The Path Forward
AI is not the enemy. Hype is not the enemy. The sequence is the enemy. And the organizations that master the human-AI operating model will own the next decade of procurement.
Behavior is the first model every AI depends on.
If the industry wants adoption, not automation theater — readiness must become the new starting point.
For those who want the methodology behind the outcomes
The October Diaries documents the full playbook:
how to align, how to prove, and how to scale — without repeating the 80% failure pattern.
📌 https://payhip.com/b/hG8zZ
30
Procurement Insights
Alignment Before Automation: Why AI Fails — and the Sequence That Delivers ROI
Posted on October 27, 2025
0
What do Linus Torvalds’ warning, Google’s 3,000 new AI courses, and the latest capital market shifts all have in common? They signal the same truth the procurement world has been slow to confront:
The industry keeps producing more tools, more dashboards, more training, more copilots — yet fewer than 5% of organizations ever achieve measurable ROI from AI or digital procurement initiatives. The hype accelerates, but the outcomes don’t.
Why? Because the market is still trying to automate before it aligns.
The AI Illusion
Google’s new “Skills” platform is impressive: 3,000+ free AI courses, labs, certificates, and hands-on learning content from DeepMind and Gemini. It will mint an army of technically-trained professionals who know how to use AI.
But here is the uncomfortable reality:
You can train 100,000 people to use AI — but if the underlying behaviors, incentives, data assumptions, workflows, and decision rights remain misaligned, success rates will stay exactly where they are: in the single digits.
Why AI Fails in Procurement
The pattern is painfully consistent:
Most organizations are still automating yesterday’s dysfunction at scale.
The Missing Sequence: Align → Prove → Scale
For 27 years, across public and private sector transformations, one lesson has stayed constant:
The successful sequence is:
Shared understanding, shared incentives, and strand-level transparency
Small, measurable win that verifies behavior and builds credibility
Automate only what has already been proven to work
This is the architecture behind RAM (1998), Hansen Fit Score (2015), and The October Diaries (2025) — models designed to codify readiness, eliminate multi-model error, and ensure AI supports decision-making instead of replacing it blindly.
Evidence Over Hype (DND → NYC Transit → Capital Markets)
Real transformation isn’t theoretical. When alignment came first:
As the recent capital markets “report card” shows, the world is finally admitting it: the tech-first era didn’t work.
The Path Forward
AI is not the enemy. Hype is not the enemy. The sequence is the enemy. And the organizations that master the human-AI operating model will own the next decade of procurement.
If the industry wants adoption, not automation theater — readiness must become the new starting point.
For those who want the methodology behind the outcomes
The October Diaries documents the full playbook:
how to align, how to prove, and how to scale — without repeating the 80% failure pattern.
📌 https://payhip.com/b/hG8zZ
30
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