In 2011, I wrote about Gartner naming Oracle a ‘Leader in Supply Chain Planning’ while customers absorbed the cost of failed integrations. Fourteen years later, I asked five AI models to assess Gartner’s latest graphics. The pattern hasn’t changed.
Image 1: AI Spending in IT Markets Forecast, 2023-2029
Note: Gartner’s own caption admits “Only 1 in 5 AI projects deliver ROI—just 1 in 50 achieve disruptive value.” Yet the graphic celebrates spending growth. They’re documenting the problem and fueling it simultaneously.
Image 2: Guardian Agents 2029
Note: Already assessed in an earlier post. AI supervising AI without addressing why deployments fail. Visually polished, conceptually hollow.
Image 3: How to Present AI to the Board
Note: Teaches CIOs how to sell AI to boards, not how to assess readiness. “Feasibility” mentioned in legend but not operationalized. It’s presentation coaching, not transformation guidance.
Image 4: AI Techniques Heat Map
Note: Dense, technical, hard to action. Shows technique maturity but not organizational readiness to absorb techniques. A map of tools, not a map of fit.
Image 5: The 2026 CIO and Technology Executive Agenda (Funding)
Note: Same as an earlier assessment. Peer pressure in chart form. “91% are increasing GenAI funding”—but no mention of readiness.
Image 6: Prompt Engineering is Fading into Context Engineering
Note: This one is slightly better. It acknowledges that static prompts aren’t enough—context matters. But it stays at the technical layer. “Context engineering” is closer to Phase 0 thinking, but it doesn’t address organizational context, only system context.
Image 7: Hype Cycle for Generative AI, 2025
Note: The Hype Cycle is Gartner’s signature product. It maps technology maturity, not organizational readiness. It tells you where a technology is on the adoption curve—not whether your organization can absorb it. 27 years of documenting hype cycles, 27 years of 80% failure rates.
Image 8: 3 Strategic Pivots for 2026 Technology Planning
Note: “From defending AI pilots to expanding into agentic AI” assumes the pilots succeeded. “From calendar-based to dynamic trigger-based decision making” is operational advice without readiness context. Strategic pivots without Phase 0 are just faster pivots toward the same cliff.
Image 9: Tech Executives Shifting to Deliver Agentic AI ROI
Note: Shows deployment timelines for AI, GenAI, and AI agents. 17% have deployed AI agents, 42% will deploy in 12 months. No mention of readiness assessment. It measures adoption velocity, not adoption success.
Image 10: Expected Change in IT Budget 2026
Note: Clean, simple, immediately readable. 53% increasing, 27% flat, 19% decreasing. Average +2.79%. But budget increase ≠ outcome improvement. This graphic answers “how much?” without asking “ready for what?”
Consolidated Scores Across All 10 Graphics
Summary Verdict:
Gartner knows how to present data. Their graphics are usually clean, professional, and immediately readable (7.3 clarity). But across ten graphics, the average likelihood of reversing the 80% failure rate is 1.7/10—essentially zero. Meanwhile, the promotional quotient is 8.1/10.
These graphics aren’t insights. They’re instruments. They measure spending, adoption, and peer behavior—then sell advisory services to help you join the herd.
Not one of these ten graphics asks: “Is your organization ready to absorb what you’re about to buy?”
That’s the question Gartner doesn’t ask—because answering it honestly might slow down the spending they’re paid to accelerate.
A TRIP BACK IN TIME – Madison Avenue ooops . . . make that Gartner, names Oracle as a leader in supply chain planning (January 7, 2011)
THE 2011 QUESTION IN 2025: So what is Gartner’s purpose?
Based on the evidence—from the above 2011 post, and from today’s post—Gartner’s purpose appears to be:
- Market-making: Create categories, name leaders, generate urgency
- Vendor validation: Provide third-party cover for purchasing decisions
- Spend acceleration: Tell CIOs what peers are doing, drive FOMO
- Advisory revenue: Sell guidance on navigating the complexity they help create
What Gartner is not for:
- Reducing the 80% failure rate
- Assessing organizational readiness
- Asking whether you should buy before telling you what to buy
- Accountability for outcomes
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Procurement Insights
14 Years Later, Same Question: What Is Gartner Actually For?
Posted on December 27, 2025
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In 2011, I wrote about Gartner naming Oracle a ‘Leader in Supply Chain Planning’ while customers absorbed the cost of failed integrations. Fourteen years later, I asked five AI models to assess Gartner’s latest graphics. The pattern hasn’t changed.
Image 1: AI Spending in IT Markets Forecast, 2023-2029
Note: Gartner’s own caption admits “Only 1 in 5 AI projects deliver ROI—just 1 in 50 achieve disruptive value.” Yet the graphic celebrates spending growth. They’re documenting the problem and fueling it simultaneously.
Image 2: Guardian Agents 2029
Note: Already assessed in an earlier post. AI supervising AI without addressing why deployments fail. Visually polished, conceptually hollow.
Image 3: How to Present AI to the Board
Note: Teaches CIOs how to sell AI to boards, not how to assess readiness. “Feasibility” mentioned in legend but not operationalized. It’s presentation coaching, not transformation guidance.
Image 4: AI Techniques Heat Map
Note: Dense, technical, hard to action. Shows technique maturity but not organizational readiness to absorb techniques. A map of tools, not a map of fit.
Image 5: The 2026 CIO and Technology Executive Agenda (Funding)
Note: Same as an earlier assessment. Peer pressure in chart form. “91% are increasing GenAI funding”—but no mention of readiness.
Image 6: Prompt Engineering is Fading into Context Engineering
Note: This one is slightly better. It acknowledges that static prompts aren’t enough—context matters. But it stays at the technical layer. “Context engineering” is closer to Phase 0 thinking, but it doesn’t address organizational context, only system context.
Image 7: Hype Cycle for Generative AI, 2025
Note: The Hype Cycle is Gartner’s signature product. It maps technology maturity, not organizational readiness. It tells you where a technology is on the adoption curve—not whether your organization can absorb it. 27 years of documenting hype cycles, 27 years of 80% failure rates.
Image 8: 3 Strategic Pivots for 2026 Technology Planning
Note: “From defending AI pilots to expanding into agentic AI” assumes the pilots succeeded. “From calendar-based to dynamic trigger-based decision making” is operational advice without readiness context. Strategic pivots without Phase 0 are just faster pivots toward the same cliff.
Image 9: Tech Executives Shifting to Deliver Agentic AI ROI
Note: Shows deployment timelines for AI, GenAI, and AI agents. 17% have deployed AI agents, 42% will deploy in 12 months. No mention of readiness assessment. It measures adoption velocity, not adoption success.
Image 10: Expected Change in IT Budget 2026
Note: Clean, simple, immediately readable. 53% increasing, 27% flat, 19% decreasing. Average +2.79%. But budget increase ≠ outcome improvement. This graphic answers “how much?” without asking “ready for what?”
Consolidated Scores Across All 10 Graphics
Summary Verdict:
Gartner knows how to present data. Their graphics are usually clean, professional, and immediately readable (7.3 clarity). But across ten graphics, the average likelihood of reversing the 80% failure rate is 1.7/10—essentially zero. Meanwhile, the promotional quotient is 8.1/10.
These graphics aren’t insights. They’re instruments. They measure spending, adoption, and peer behavior—then sell advisory services to help you join the herd.
Not one of these ten graphics asks: “Is your organization ready to absorb what you’re about to buy?”
That’s the question Gartner doesn’t ask—because answering it honestly might slow down the spending they’re paid to accelerate.
A TRIP BACK IN TIME – Madison Avenue ooops . . . make that Gartner, names Oracle as a leader in supply chain planning (January 7, 2011)
THE 2011 QUESTION IN 2025: So what is Gartner’s purpose?
Based on the evidence—from the above 2011 post, and from today’s post—Gartner’s purpose appears to be:
What Gartner is not for:
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