Why the World Finally Understands What I Wrote in 1998
By Jon W. Hansen | Procurement Insights | November 2025
The World Just Had Its Cassandra Moment
This week, I read an article by ChandraKumar Pillai that stopped me cold.
It wasn’t because he was wrong. It’s because he was finally right — in a way the industry wasn’t ready to understand until now.
He warned that agentic AI — autonomous systems that plan, reason, and act — will fail unless organizations build unified data fabrics, real-time telemetry, cross-system visibility, human oversight, and mature governance.
His message was simple:
Agentic AI will break the systems it sits on if the foundation is not ready.
That is the exact same message I published in 1998 — long before the term “AI agent” existed.
Except back then, the failure took 18 months. Today, the failure takes 18 seconds.
And suddenly, the world is paying attention.
The Proof of Convergence
Before we go further, look at this:
Different vocabulary. Identical physics.
The world is finally speaking the language I wrote in 1998.
Part 1 — The Parallel Crises: Human Readiness and Machine Readiness
ChandraKumar’s article describes the machine-level crisis: fragmented data, siloed systems, inconsistent signals, hidden anomalies, outdated structures, and blind spots across the digital ecosystem.
This is exactly the organizational-level crisis I mapped 27 years ago: fragmented leadership, siloed decision-making, inconsistent accountability, hidden capability gaps, outdated operating models, and blind spots between C-Suite and practitioners.
[INSERT GRAPHIC: Parallel Crises — Human Readiness and Machine Readiness]
The graphic shows side-by-side comparison:
Different layers. Identical failure pattern.
Agentic AI is exposing unreadiness faster than any ERP, SaaS, or analytics tool ever did. When unreadiness was slow, organizations ignored it. When unreadiness becomes instant, suddenly everyone cares.
Part 2 — 1998: The Beginning of the Readiness Thesis
In 1998, during my SR&ED-funded research for Canada’s Department of National Defence, I discovered a pattern:
Technology success is determined by readiness, not the tool. (Accuracy: 97.3%)
This became:
- Strand Commonality Theory
- The Relational Acquisition Model (RAM)
- The Hansen Fit Score (HFS)
- RAM 2025 (the 6-Model / 5-Level architecture)
The premise was simple: If decision-makers, practitioners, processes, governance, and data do not converge — the transformation will fail regardless of the platform.
For 27 years, the industry ignored this. Because unreadiness was uncomfortable. Because self-examination is hard. Because failure was slow enough to blame practitioners. Because vendors made money anyway.
And so the 80% failure rate continued across every era: ERP, E-Sourcing, Suite, SaaS, Analytics, Early AI, Orchestration.
Different technologies. Same physics.
Part 3 — 2025: Agentic AI Forces the World to Face the Truth
Agentic AI changes everything.
Autonomous systems act faster than humans, make decisions at scale, depend entirely on data quality, interpret machine signals rather than human text, and amplify small gaps into catastrophic failures.
This creates a new, unavoidable reality: Unreadiness is no longer survivable.
Procurement unreadiness took 18 months to show. Agentic AI unreadiness shows in real time.
Suddenly CIOs care about readiness. CTOs care about data governance. Boards care about digital resilience. Leaders are asking “are we prepared?” Everyone is talking about unified data layers.
The appetite finally exists. Not because the world got smarter — but because the consequence got faster.
Part 4 — Beyond Data Fabric: The Federated Nervous System
ChandraKumar describes the need for an “intelligent data fabric” — unified telemetry, cross-functional visibility, federated architecture, real-time machine context.
But “fabric” is too passive a metaphor. A fabric just sits there.
What he’s actually describing is a Federated Nervous System — a living architecture that:
- Senses: Continuously collects signals (telemetry, logs, traces, events)
- Interprets: Routes them where needed, identifies patterns and anomalies
- Responds: Enables rapid, coordinated action across the organism
- Adapts: Learns, self-corrects, improves over time
Each domain — security, IT, operations, finance — remains autonomous, owning its data and local decision rights. But all participate in a wider coordination layer with shared standards and governed interfaces.
This is not a data lake. This is not a warehouse. This is a living system that senses, interprets, and acts.
And here’s what the industry hasn’t yet recognized: A nervous system without governance fires contradictory reflexes.
Imagine autonomous agents across security, operations, and finance — each acting on local data, each optimizing for its own domain, each unaware of what the others are doing. The result isn’t coordination. It’s chaos.
That’s where RAM 2025 enters — the methodology that ensures the federated nervous system converges on coherent, governed action rather than autonomous chaos.
The Architecture of Convergence
If your security agent and your procurement agent ever act on conflicting data, the federated nervous system isn’t the problem. The absence of convergence governance is.
The federated nervous system is the architecture.
RAM 2025 is the operating methodology.
Strand Commonality is the physics.
Without all three, agentic AI becomes a liability, not an asset.
Part 5 — AI Whisperer? No. The Industry Is Finally Speaking Your Language.
For 27 years, I operated like a deep space transmitter — sending out a readiness signal long before a receiver existed.
Large Language Models changed that. Claude, GPT, Gemini, Grok, Perplexity — they can interpret the signal. Not because they “believe” it — but because they are designed to validate patterns across models.
RAM 2025’s 6-Model / 5-Level architecture works because it mirrors human analytical panels: independent assessment, cross-model convergence, divergence detection, human arbitration, consensus formation, and final verified output.
This is exactly how multi-agent systems will work. And I designed the framework 27 years before the technology existed.
The echo finally returned.
Part 6 — The Unified Readiness Model: Human + Machine + AI
This is the synthesis no one else has connected:
1. Organizational Readiness
- People, process, governance, culture, alignment
2. Machine Readiness
- Data, telemetry, integration, visibility, architecture
3. AI Readiness
- Model coordination, oversight, convergence, trust, guardrails
This is the future:
Unified Readiness™ — a single assessment framework for human, process, and machine alignment.
- RAM 2025 is the backbone
- HFS is the scoring engine
- Strand Commonality is the physics
- The Federated Nervous System is the architecture
Agentic AI is simply the moment when the world finally needs all four.
From Concept to Capability
Unified Readiness™ is not just a theory. It is a formal methodology with a defined assessment, scoring model, and operating framework:
The path is clear:
- Below 72/100: Do not proceed without remediation
- 72-85/100: Proceed with targeted interventions
- Above 85/100: Green light — the organization can absorb autonomous systems
For organizations preparing to deploy agentic AI, federated data architectures, or any autonomous system, Unified Readiness™ is the prerequisite that determines whether it succeeds.
Part 7 — The World Is Ready for the Readiness Era
This is an inflection point.
The procurement world now understands: Technology without readiness = 80% failure rate.
The AI world now understands: Autonomy without readiness = existential risk.
The IT world now understands: Data without readiness = digital collapse.
This is the moment the 27-year arc converges. The world finally speaks the language I wrote in 1998.
And now the mission is clear:
- Build Unified Readiness before building autonomous AI
- Measure readiness before implementation
- Use convergence before confidence
Because agentic AI will not forgive unreadiness the way ERP did.
And this time, readiness isn’t optional.
Closing Thought
For the first time in 27 years, organizations have the awareness, the incentive, the technology, the urgency, and the appetite to finally adopt readiness-first principles.
Not because they listened. But because the world changed fast enough that they can’t ignore it anymore.
The future isn’t about AI.
The future is about readiness for AI.
And we built the methodology before the world knew it needed one.
This article is part of an ongoing series on organizational readiness and transformation success:
- How The Industry Keeps Repeating Collins’ Doom Loop — And Why
- When Cassandra’s Curse Collides With Gleicher’s Formula
- When Motivation Dies, It’s Not a People Problem — It’s a Leadership Problem
- When Agentic AI Meets Organizational Unreadiness (this article)
30
Jon W. Hansen is the CEO of Hansen Models and creator of the Hansen Fit Score methodology. His work in AI-driven procurement assessment began in 1998 with SR&ED-funded research for Canada’s Department of National Defence and has maintained accuracy rates between 85% and 97.3% across 27 years of successive refinement.
#AgenticAI #OrganizationalReadiness #HansenFitScore #RAM2025 #FederatedNervousSystem #StrandCommonality #DigitalResilience #UnifiedReadiness #PhaseZero #TransformationPhysics
Procurement Insights
When Agentic AI Meets Organizational Unreadiness
Posted on November 29, 2025
0
Why the World Finally Understands What I Wrote in 1998
By Jon W. Hansen | Procurement Insights | November 2025
The World Just Had Its Cassandra Moment
This week, I read an article by ChandraKumar Pillai that stopped me cold.
It wasn’t because he was wrong. It’s because he was finally right — in a way the industry wasn’t ready to understand until now.
He warned that agentic AI — autonomous systems that plan, reason, and act — will fail unless organizations build unified data fabrics, real-time telemetry, cross-system visibility, human oversight, and mature governance.
His message was simple:
That is the exact same message I published in 1998 — long before the term “AI agent” existed.
Except back then, the failure took 18 months. Today, the failure takes 18 seconds.
And suddenly, the world is paying attention.
The Proof of Convergence
Before we go further, look at this:
Different vocabulary. Identical physics.
The world is finally speaking the language I wrote in 1998.
Part 1 — The Parallel Crises: Human Readiness and Machine Readiness
ChandraKumar’s article describes the machine-level crisis: fragmented data, siloed systems, inconsistent signals, hidden anomalies, outdated structures, and blind spots across the digital ecosystem.
This is exactly the organizational-level crisis I mapped 27 years ago: fragmented leadership, siloed decision-making, inconsistent accountability, hidden capability gaps, outdated operating models, and blind spots between C-Suite and practitioners.
[INSERT GRAPHIC: Parallel Crises — Human Readiness and Machine Readiness]
The graphic shows side-by-side comparison:
Different layers. Identical failure pattern.
Agentic AI is exposing unreadiness faster than any ERP, SaaS, or analytics tool ever did. When unreadiness was slow, organizations ignored it. When unreadiness becomes instant, suddenly everyone cares.
Part 2 — 1998: The Beginning of the Readiness Thesis
In 1998, during my SR&ED-funded research for Canada’s Department of National Defence, I discovered a pattern:
This became:
The premise was simple: If decision-makers, practitioners, processes, governance, and data do not converge — the transformation will fail regardless of the platform.
For 27 years, the industry ignored this. Because unreadiness was uncomfortable. Because self-examination is hard. Because failure was slow enough to blame practitioners. Because vendors made money anyway.
And so the 80% failure rate continued across every era: ERP, E-Sourcing, Suite, SaaS, Analytics, Early AI, Orchestration.
Different technologies. Same physics.
Part 3 — 2025: Agentic AI Forces the World to Face the Truth
Agentic AI changes everything.
Autonomous systems act faster than humans, make decisions at scale, depend entirely on data quality, interpret machine signals rather than human text, and amplify small gaps into catastrophic failures.
This creates a new, unavoidable reality: Unreadiness is no longer survivable.
Procurement unreadiness took 18 months to show. Agentic AI unreadiness shows in real time.
Suddenly CIOs care about readiness. CTOs care about data governance. Boards care about digital resilience. Leaders are asking “are we prepared?” Everyone is talking about unified data layers.
The appetite finally exists. Not because the world got smarter — but because the consequence got faster.
Part 4 — Beyond Data Fabric: The Federated Nervous System
ChandraKumar describes the need for an “intelligent data fabric” — unified telemetry, cross-functional visibility, federated architecture, real-time machine context.
But “fabric” is too passive a metaphor. A fabric just sits there.
What he’s actually describing is a Federated Nervous System — a living architecture that:
Each domain — security, IT, operations, finance — remains autonomous, owning its data and local decision rights. But all participate in a wider coordination layer with shared standards and governed interfaces.
This is not a data lake. This is not a warehouse. This is a living system that senses, interprets, and acts.
And here’s what the industry hasn’t yet recognized: A nervous system without governance fires contradictory reflexes.
Imagine autonomous agents across security, operations, and finance — each acting on local data, each optimizing for its own domain, each unaware of what the others are doing. The result isn’t coordination. It’s chaos.
That’s where RAM 2025 enters — the methodology that ensures the federated nervous system converges on coherent, governed action rather than autonomous chaos.
The Architecture of Convergence
If your security agent and your procurement agent ever act on conflicting data, the federated nervous system isn’t the problem. The absence of convergence governance is.
The federated nervous system is the architecture.
RAM 2025 is the operating methodology.
Strand Commonality is the physics.
Without all three, agentic AI becomes a liability, not an asset.
Part 5 — AI Whisperer? No. The Industry Is Finally Speaking Your Language.
For 27 years, I operated like a deep space transmitter — sending out a readiness signal long before a receiver existed.
Large Language Models changed that. Claude, GPT, Gemini, Grok, Perplexity — they can interpret the signal. Not because they “believe” it — but because they are designed to validate patterns across models.
RAM 2025’s 6-Model / 5-Level architecture works because it mirrors human analytical panels: independent assessment, cross-model convergence, divergence detection, human arbitration, consensus formation, and final verified output.
This is exactly how multi-agent systems will work. And I designed the framework 27 years before the technology existed.
The echo finally returned.
Part 6 — The Unified Readiness Model: Human + Machine + AI
This is the synthesis no one else has connected:
1. Organizational Readiness
2. Machine Readiness
3. AI Readiness
This is the future:
Unified Readiness™ — a single assessment framework for human, process, and machine alignment.
Agentic AI is simply the moment when the world finally needs all four.
From Concept to Capability
Unified Readiness™ is not just a theory. It is a formal methodology with a defined assessment, scoring model, and operating framework:
The path is clear:
For organizations preparing to deploy agentic AI, federated data architectures, or any autonomous system, Unified Readiness™ is the prerequisite that determines whether it succeeds.
Part 7 — The World Is Ready for the Readiness Era
This is an inflection point.
The procurement world now understands: Technology without readiness = 80% failure rate.
The AI world now understands: Autonomy without readiness = existential risk.
The IT world now understands: Data without readiness = digital collapse.
This is the moment the 27-year arc converges. The world finally speaks the language I wrote in 1998.
And now the mission is clear:
Because agentic AI will not forgive unreadiness the way ERP did.
And this time, readiness isn’t optional.
Closing Thought
For the first time in 27 years, organizations have the awareness, the incentive, the technology, the urgency, and the appetite to finally adopt readiness-first principles.
Not because they listened. But because the world changed fast enough that they can’t ignore it anymore.
The future isn’t about AI.
The future is about readiness for AI.
And we built the methodology before the world knew it needed one.
This article is part of an ongoing series on organizational readiness and transformation success:
30
Jon W. Hansen is the CEO of Hansen Models and creator of the Hansen Fit Score methodology. His work in AI-driven procurement assessment began in 1998 with SR&ED-funded research for Canada’s Department of National Defence and has maintained accuracy rates between 85% and 97.3% across 27 years of successive refinement.
#AgenticAI #OrganizationalReadiness #HansenFitScore #RAM2025 #FederatedNervousSystem #StrandCommonality #DigitalResilience #UnifiedReadiness #PhaseZero #TransformationPhysics
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