30 Years of Technology Stacks. Same Missing Layer. Same 70-80% Failure Rate.
The Latest Stack
Gartner recently published their comprehensive AI technology stack—a nine-layer architecture spanning infrastructure, platforms, data, engineering, models, applications, security, strategy, and services.
It’s impressive. It’s detailed. It’s technology-focused.
And it’s missing the most critical layer.
The same layer that’s been missing from every technology stack that virtually all analyst firms have published over the past 30 years, and Gartner’s 2025 AI edition is no different.
So, What Is Missing? Layer 0: Organizational Readiness Assessment.
The Pattern: 30 Years, 4 Revolutions, Same Outcome
I’ve been tracking technology implementations since 1998. Over 180 implementations across 27 years. The data reveals a disturbing consistency across every major technology era.
1995-2000: The Internet Era
Industry Technology Focus:
- Client-Server Architecture
- Web Servers
- Databases
- Networking Infrastructure
The Promise:
- Connected enterprises
- Global reach
- Digital transformation
What I Observed:
- 70-80% of implementations failed to deliver promised ROI
- Dot-com bubble burst (2000)
- Organizations blamed for “not being ready”
What Was Missing: Organizational readiness assessment
2005-2010: The Cloud Era
Industry Technology Focus:
- SaaS Platforms
- Cloud Infrastructure (IaaS, PaaS)
- APIs and Integration Layers
- Service Management
The Promise:
- Scalable, flexible operations
- Cost-effective computing
- Always-on accessibility
What I Observed:
- 70-80% of cloud migrations failed to achieve projected savings
- Integration complexity underestimated
- Organizations blamed for “poor change management”
What Was Missing: Organizational readiness assessment
2010-2020: The Big Data Era
Industry Technology Focus:
- Analytics Platforms
- Data Lakes and Warehouses
- Machine Learning Tools
- Visualization Dashboards
The Promise:
- Data-driven decision making
- Predictive insights
- Competitive advantage through analytics
What I Observed:
- 70-80% of big data projects failed to deliver business value
- “Data scientists” couldn’t access clean, structured data
- Organizations blamed for “data literacy gaps”
What Was Missing: Organizational readiness assessment
2020-2025: The AI Era
Industry Technology Focus (Gartner’s Current Stack):
- AI Infrastructure (servers, clusters, GPUs)
- AI Platforms (operations, observability, MLOps)
- AI Data (ingestion, governance, synthetic generation)
- AI Engineering (foundation models, deployment, optimization)
- AI Models (LLMs, GANs, computer vision)
- AI Apps (reasoning, agents)
- AI Security and Risk (cyber security, privacy/ethics)
- AI Strategy and Business (planning, strategy)
- AI Services (managed services, advisory)
The Promise:
- Autonomous systems
- Intelligent automation
- Frictionless operations
What I’m Observing:
- Max Henry recently predicted 90% of AI agent companies will disappear by 2026
- Same implementation challenges emerging
- Organizations being blamed for “not being ready”
What’s Missing: Organizational readiness assessment
The Definition of Insanity
Albert Einstein reportedly defined insanity as “doing the same thing over and over again and expecting different results.”
For 30 years, analyst firms and the industry have followed the same pattern:
- New technology emerges
- Analysts publish comprehensive technology stacks
- Vendors build solutions matching the stack specifications
- Organizations deploy following analyst recommendations
- 70-80% of implementations fail
- Organizations blamed for “not being ready”
- But no one told them to assess readiness FIRST
The technology changes. The stacks become more sophisticated. The promises get bigger.
The failure rate remains constant.
Why?
Layer 0: The Missing Foundation
Before organizations invest in multi-layer technology stacks—whether it’s Gartner’s nine-layer AI stack or any other analyst framework—they need something fundamental:
Layer 0: Organizational Readiness Assessment
This isn’t about technology. It’s about whether the organization can actually USE the technology effectively.
Layer 0 Answers Critical Questions:
Stakeholder Alignment:
- Are stakeholders aligned on what “AI agents” means in our context?
- Do we have shared understanding of “autonomous” vs. “automated”?
- Are decision boundaries defined and agreed upon?
Process Maturity:
- Are processes documented well enough to automate?
- Do we understand current workflows before redesigning them?
- Have we identified what should NOT be automated?
Governance Infrastructure:
- Are governance policies established for autonomous decisions?
- Do we have audit trails and accountability frameworks?
- Is human-in-the-loop validation defined?
Data Readiness:
- Is our data structured, clean, and accessible?
- Do we have data enrichment capabilities?
- Are data governance policies in place?
Change Management:
- Is change management infrastructure ready?
- Do we have stakeholder buy-in beyond the C-suite?
- Are training and adoption plans developed?
Success Measurement:
- Can we measure success before deployment?
- Are baseline metrics established?
- Do we know what “good” looks like?
Risk Assessment:
- Have we identified implementation risks?
- Do we understand compliance requirements?
- Are fallback plans developed?
The 2008 Question That Predicted This Gap
In 2008, I asked the procurement community a question inspired by Bill Gates’ book Business @ The Speed of Thought:
“Does your enterprise have a ‘Digital Nervous System’?”
I wasn’t asking about technology infrastructure. I was asking about the organizational infrastructure to orchestrate technology—the governance, alignment, and readiness that makes technology deployments successful.
The answer in 2008 was no.
In 2025, looking at Gartner’s AI technology stack and the broader industry approach, the answer is still no.
Technology stacks have become more sophisticated. But the fundamental question remains unaddressed:
Is the organization ready to integrate and use what the stack provides?
Why This Matters Now
The stakes are higher with AI agents than with previous technology waves.
Internet Era failures meant wasted infrastructure investments and delayed digital transformation.
Cloud Era failures meant cost overruns and integration complexity.
Big Data failures meant unused analytics platforms and frustrated data scientists.
AI Era failures mean something more dangerous: autonomous systems making decisions without proper governance.
When an internet site goes down, it’s an inconvenience.
When a cloud migration fails, it’s expensive.
When a big data project doesn’t deliver insights, it’s disappointing.
When an AI agent makes autonomous decisions without proper governance, it’s a liability risk.
The margin for error shrinks with each technology generation. Yet the readiness assessment gap persists across the industry.
The Circular Logic Problem
Here’s the pattern I’ve observed for 27 years across analyst firms and technology vendors:
- Organizations follow technology stack recommendations from analysts
- Deploy technology without assessing organizational readiness
- Encounter the 70-80% failure rate that analysts themselves document
- Get blamed for “not being ready” or “poor change management”
- But the stacks never told them to assess readiness first
It’s circular logic:
- Analysts publish technology stacks (layers 1-9)
- Organizations deploy following the stacks
- Projects fail at 70-80%
- Analysts research and document the failure rate
- Organizations blamed for not being ready
- But Layer 0 (readiness assessment) was never in the stack
This isn’t malicious. It’s a blind spot created by the business model.
Analysts and vendors focus on technology buyers. Technology buyers want stack specifications to evaluate solutions against.
Practitioners need readiness frameworks. They need to know if they should deploy at all.
These are different audiences with different needs. The industry optimizes for the technology buyer.
What This Means for Your Organization
If you’re considering deploying AI agents following Gartner’s technology stack—or any analyst framework—ask yourself:
Before we invest in layers 1-9, have we assessed Layer 0?
Specifically:
- Do we know if we’re ready? Have we assessed organizational readiness across stakeholder alignment, process maturity, governance infrastructure, data quality, change management capability, and risk understanding?
- Do we have baseline metrics? Can we measure success before deployment? Do we know what current performance looks like?
- Have we documented current state? Are processes mapped? Are decision boundaries defined? Is tacit knowledge captured?
- Is governance established? Do we have policies for autonomous decisions? Are audit trails defined? Is human validation integrated?
- Are stakeholders aligned? Do all parties agree on what “AI agents” means? Are expectations managed? Are decision rights clear?
If the answer to these questions is no, you’re not ready to deploy any multi-layer AI technology stack—no matter how comprehensive it is or which analyst firm published it.
The Solution: Add Layer 0 to Your Stack
This isn’t a criticism of Gartner’s technical expertise or that of other analyst firms. Their technology stacks are comprehensive from an infrastructure perspective.
It’s an observation about what’s systematically missing across the industry.
Organizations need both:
Layers 1-9: Technology infrastructure (what analysts provide)
Layer 0: Organizational readiness assessment (what’s missing)
You can’t build layers 1-9 on an unstable foundation. Layer 0 is that foundation.
What Layer 0 Assessment Looks Like
In my work developing the Hansen Fit Score (HFS) methodology, I’ve identified seven dimensions of organizational readiness that must be assessed before technology deployment:
- Strategic Alignment: Are organizational objectives clear and shared?
- Stakeholder Engagement: Are key stakeholders identified, aligned, and committed?
- Process Maturity: Are processes documented, understood, and ready for transformation?
- Data Quality: Is data structured, accessible, and governed?
- Technology Infrastructure: Does existing infrastructure support new capabilities?
- Change Management: Is the organization prepared for transformation?
- Governance and Compliance: Are policies, controls, and accountability frameworks established?
Organizations score across these dimensions before deploying technology.
High scores = ready to deploy
Low scores = readiness gaps must be addressed first
This is Layer 0.
The Alternative: Repeat the Pattern
Without Layer 0 assessment, organizations will repeat the 30-year pattern:
- Follow analyst technology stack recommendations (layers 1-9)
- Deploy AI agents without readiness assessment
- Encounter implementation challenges
- Fail to achieve promised ROI
- Get blamed for “not being ready”
- Become part of the 70-80% failure statistic
Max Henry’s prediction that 90% of AI agent companies will disappear by 2026 is simply the latest manifestation of this pattern.
The crash is predictable. It’s also preventable.
Breaking the 30-Year Pattern
For three decades, the industry has optimized technology stacks while ignoring organizational readiness.
The technology improved. The stacks became more sophisticated. The promises got bigger.
The failure rate stayed the same.
It’s time to break the pattern.
Not by building better technology stacks—Gartner’s AI stack and others are comprehensive from a technical perspective.
By adding Layer 0: Organizational Readiness Assessment.
Before deploying layers 1-9, assess whether your organization is ready to use them.
Before investing millions in AI infrastructure, verify you have the foundation to support it.
Before following the next technology stack—from Gartner or any other analyst firm—ask if you’re stacking the odds against your own success.
The Question for 2025
In 2008, I asked: “Does your enterprise have a Digital Nervous System?”
In 2025, I’m asking: “Before deploying any AI technology stack, have you assessed Layer 0?”
Technology stacks are necessary. But they’re not sufficient.
Layer 0 is the missing foundation.
Without it, you’re building on sand—just like the 70-80% who failed before you.
Conclusion: Inadvertently Stacking the Odds
Is Gartner inadvertently stacking the odds against your AI success?
Not deliberately. Not maliciously. And they’re not alone.
But by focusing exclusively on technology infrastructure (layers 1-9) without addressing organizational readiness (Layer 0)—a pattern consistent across virtually all analyst firms—the industry is perpetuating a 30-year cycle:
Technology-first deployment → 70-80% failure → Blame organizations for “not being ready” → Repeat
The definition of insanity is doing the same thing repeatedly and expecting different results.
For 30 years, we’ve followed technology stacks without readiness assessment.
For 30 years, we’ve achieved 70-80% failure rates.
Gartner’s 2025 AI stack is no different.
How much longer before we add Layer 0?
Related Reading:
#DigitalTransformation #OrganizationalReadiness #AgenticAI #AIGovernance #ChangeManagement #TechnologyImplementation #ProcurementTransformation
30
Procurement Insights
Is Gartner Inadvertently Stacking the Odds Against Your AI Success?
Posted on November 8, 2025
0
30 Years of Technology Stacks. Same Missing Layer. Same 70-80% Failure Rate.
The Latest Stack
Gartner recently published their comprehensive AI technology stack—a nine-layer architecture spanning infrastructure, platforms, data, engineering, models, applications, security, strategy, and services.
It’s impressive. It’s detailed. It’s technology-focused.
And it’s missing the most critical layer.
The same layer that’s been missing from every technology stack that virtually all analyst firms have published over the past 30 years, and Gartner’s 2025 AI edition is no different.
So, What Is Missing? Layer 0: Organizational Readiness Assessment.
The Pattern: 30 Years, 4 Revolutions, Same Outcome
I’ve been tracking technology implementations since 1998. Over 180 implementations across 27 years. The data reveals a disturbing consistency across every major technology era.
1995-2000: The Internet Era
Industry Technology Focus:
The Promise:
What I Observed:
What Was Missing: Organizational readiness assessment
2005-2010: The Cloud Era
Industry Technology Focus:
The Promise:
What I Observed:
What Was Missing: Organizational readiness assessment
2010-2020: The Big Data Era
Industry Technology Focus:
The Promise:
What I Observed:
What Was Missing: Organizational readiness assessment
2020-2025: The AI Era
Industry Technology Focus (Gartner’s Current Stack):
The Promise:
What I’m Observing:
What’s Missing: Organizational readiness assessment
The Definition of Insanity
Albert Einstein reportedly defined insanity as “doing the same thing over and over again and expecting different results.”
For 30 years, analyst firms and the industry have followed the same pattern:
The technology changes. The stacks become more sophisticated. The promises get bigger.
The failure rate remains constant.
Why?
Layer 0: The Missing Foundation
Before organizations invest in multi-layer technology stacks—whether it’s Gartner’s nine-layer AI stack or any other analyst framework—they need something fundamental:
Layer 0: Organizational Readiness Assessment
This isn’t about technology. It’s about whether the organization can actually USE the technology effectively.
Layer 0 Answers Critical Questions:
Stakeholder Alignment:
Process Maturity:
Governance Infrastructure:
Data Readiness:
Change Management:
Success Measurement:
Risk Assessment:
The 2008 Question That Predicted This Gap
In 2008, I asked the procurement community a question inspired by Bill Gates’ book Business @ The Speed of Thought:
“Does your enterprise have a ‘Digital Nervous System’?”
I wasn’t asking about technology infrastructure. I was asking about the organizational infrastructure to orchestrate technology—the governance, alignment, and readiness that makes technology deployments successful.
The answer in 2008 was no.
In 2025, looking at Gartner’s AI technology stack and the broader industry approach, the answer is still no.
Technology stacks have become more sophisticated. But the fundamental question remains unaddressed:
Is the organization ready to integrate and use what the stack provides?
Why This Matters Now
The stakes are higher with AI agents than with previous technology waves.
Internet Era failures meant wasted infrastructure investments and delayed digital transformation.
Cloud Era failures meant cost overruns and integration complexity.
Big Data failures meant unused analytics platforms and frustrated data scientists.
AI Era failures mean something more dangerous: autonomous systems making decisions without proper governance.
When an internet site goes down, it’s an inconvenience.
When a cloud migration fails, it’s expensive.
When a big data project doesn’t deliver insights, it’s disappointing.
When an AI agent makes autonomous decisions without proper governance, it’s a liability risk.
The margin for error shrinks with each technology generation. Yet the readiness assessment gap persists across the industry.
The Circular Logic Problem
Here’s the pattern I’ve observed for 27 years across analyst firms and technology vendors:
It’s circular logic:
This isn’t malicious. It’s a blind spot created by the business model.
Analysts and vendors focus on technology buyers. Technology buyers want stack specifications to evaluate solutions against.
Practitioners need readiness frameworks. They need to know if they should deploy at all.
These are different audiences with different needs. The industry optimizes for the technology buyer.
What This Means for Your Organization
If you’re considering deploying AI agents following Gartner’s technology stack—or any analyst framework—ask yourself:
Before we invest in layers 1-9, have we assessed Layer 0?
Specifically:
If the answer to these questions is no, you’re not ready to deploy any multi-layer AI technology stack—no matter how comprehensive it is or which analyst firm published it.
The Solution: Add Layer 0 to Your Stack
This isn’t a criticism of Gartner’s technical expertise or that of other analyst firms. Their technology stacks are comprehensive from an infrastructure perspective.
It’s an observation about what’s systematically missing across the industry.
Organizations need both:
Layers 1-9: Technology infrastructure (what analysts provide)
Layer 0: Organizational readiness assessment (what’s missing)
You can’t build layers 1-9 on an unstable foundation. Layer 0 is that foundation.
What Layer 0 Assessment Looks Like
In my work developing the Hansen Fit Score (HFS) methodology, I’ve identified seven dimensions of organizational readiness that must be assessed before technology deployment:
Organizations score across these dimensions before deploying technology.
High scores = ready to deploy
Low scores = readiness gaps must be addressed first
This is Layer 0.
The Alternative: Repeat the Pattern
Without Layer 0 assessment, organizations will repeat the 30-year pattern:
Max Henry’s prediction that 90% of AI agent companies will disappear by 2026 is simply the latest manifestation of this pattern.
The crash is predictable. It’s also preventable.
Breaking the 30-Year Pattern
For three decades, the industry has optimized technology stacks while ignoring organizational readiness.
The technology improved. The stacks became more sophisticated. The promises got bigger.
The failure rate stayed the same.
It’s time to break the pattern.
Not by building better technology stacks—Gartner’s AI stack and others are comprehensive from a technical perspective.
By adding Layer 0: Organizational Readiness Assessment.
Before deploying layers 1-9, assess whether your organization is ready to use them.
Before investing millions in AI infrastructure, verify you have the foundation to support it.
Before following the next technology stack—from Gartner or any other analyst firm—ask if you’re stacking the odds against your own success.
The Question for 2025
In 2008, I asked: “Does your enterprise have a Digital Nervous System?”
In 2025, I’m asking: “Before deploying any AI technology stack, have you assessed Layer 0?”
Technology stacks are necessary. But they’re not sufficient.
Layer 0 is the missing foundation.
Without it, you’re building on sand—just like the 70-80% who failed before you.
Conclusion: Inadvertently Stacking the Odds
Is Gartner inadvertently stacking the odds against your AI success?
Not deliberately. Not maliciously. And they’re not alone.
But by focusing exclusively on technology infrastructure (layers 1-9) without addressing organizational readiness (Layer 0)—a pattern consistent across virtually all analyst firms—the industry is perpetuating a 30-year cycle:
Technology-first deployment → 70-80% failure → Blame organizations for “not being ready” → Repeat
The definition of insanity is doing the same thing repeatedly and expecting different results.
For 30 years, we’ve followed technology stacks without readiness assessment.
For 30 years, we’ve achieved 70-80% failure rates.
Gartner’s 2025 AI stack is no different.
How much longer before we add Layer 0?
Related Reading:
#DigitalTransformation #OrganizationalReadiness #AgenticAI #AIGovernance #ChangeManagement #TechnologyImplementation #ProcurementTransformation
30
Share this:
Related