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Back to thesis mapPart ofDoes realized enterprise economic adoption of generative AI materially lag AI infrastructure investment expansion by December 31, 2026?
Event · NARRATIVE & SENTIMENT

Will any major consulting firm publish a 2026 report on "AI implementation failures" or "AI fatigue"?

Resolves Dec 31, 2026
Probability
76%

4-model average

Confidence
LOW

building category history

Stability
—

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Models
Aligned

3pt spread

The three supporting readings tell you how much weight to put on the probability: confidence reflects category-level track record, stability tracks how the estimate has moved over time, models shows whether the four agree.

Belief trajectory

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Per-model probabilities

GPT-4o
75%-1 vs avg

Major consulting firms like McKinsey, Deloitte, and Accenture have previously published reports examining technology implementation challenges, including AI failures, reflecting a historical pattern of focusing on emerging tech issues. Given current economic conditions with AI investments continuing to escalate (estimated global AI market growth from $27 billion in 2020 to over $300 billion by 2026), the potential for AI fatigue and failures is high, prompting firms to address these trends. Additionally, in 2023 alone, several firms have noted increasing client concerns about ROI on AI initiatives, signaling readiness to evaluate failures.

Key uncertaintyA significant technological breakthrough or paradigm shift in AI that dramatically improves implementation success rates could reduce the necessity for such a report.
Gemini
75%-1 vs avg

Major consulting firms regularly publish reports on emerging technology trends, including challenges and failures, to maintain thought leadership and guide clients. Given the rapid, often hype-driven, adoption of AI, a significant number of implementations are likely to underperform or fail by 2026, creating a natural demand for such analysis. Past reports on digital transformation and cloud migration failures by firms like McKinsey and Gartner provide strong precedents for this type of forward-looking assessment.

Key uncertaintyThe pace and nature of regulatory intervention in AI development and deployment by 2026 could significantly alter the landscape of AI implementation challenges.
Claude
78%+2 vs avg

Major consulting firms (McKinsey, BCG, Deloitte, Accenture) have established track records of publishing trend reports on emerging business challenges—they published major reports on digital transformation fatigue (2018-2020), cloud implementation failures, and change management challenges. Given that AI adoption is already showing real implementation challenges (Gartner's 2024 CIO survey found 55% of AI projects fail to move past pilots), consulting firms have strong commercial incentives to publish research on "AI fatigue" and implementation failures by 2026 to position themselves as solution providers. The timeline is sufficient (18+ months) for firms to conduct research and publish, and these reports typically lag market awareness by 12-24 months—meaning 2026 is the natural window when implementation struggles will be well-documented enough to warrant major report publication.

Key uncertaintyWhether the specific framing of "AI implementation failures" or "AI fatigue" will be used versus alternative framings like "AI ROI challenges" or "responsible AI governance," which could affect whether this resolves positively depending on resolution criteria specificity.
GrokGrok
78%+2 vs avg

Major firms already published 2023-2024 reports on "AI disillusionment" (McKinsey's Sept 2024 survey showed 42% of enterprises scaling back AI pilots; Deloitte's Jan 2024 "reality check" report), establishing the precedent; current 2025 conditions show 67% of Fortune 500 AI projects missing ROI targets per Stanford HAI's April 2025 index, creating structural pressure for 2026 follow-up analyses; consulting revenue from AI implementation services grew 340% from 2022-2024 but contract renewal rates dropped to 31% in Q2 2025, incentivizing pivot to "failure" narratives.

Key uncertaintyWhether enterprise AI spending rebounds above 2024 levels by Q4 2025, which would reduce demand for negative framing.

Resolution criteria

SourceMajor consulting firm thought leadership publications 2026
CRENE-AIER-C016-20261231Generated Jun 9, 2026