The AI Graveyard Is Growing. What Are Businesses Getting Wrong?

October 24, 2026 · Keith Pasley

DECISIONFIRST ANALYSIS

Pillar: Better AI Decisions

Why this matters

The article highlights three risks that executives should evaluate before investing in AI: insufficient customer demand, weak differentiation, and business models that cannot sustain operating costs.
A particularly important risk is platform consolidation. A standalone AI application may lose its competitive advantage when Microsoft, Google, OpenAI, or another established platform incorporates similar capabilities into its existing products.

Decision it changes

Executives should require a stronger business case before approving AI investments, building proprietary applications, or committing to emerging AI vendors.
That means evaluating customer workflow fit, measurable financial return, competitive differentiation, integration costs, and long-term vendor viability.

Who should care

CIOs, CFOs, CEOs, AI practice leaders, technology resellers, MSPs, systems integrators, and investors evaluating AI businesses.

What I would ask next

If the AI technology we are investing in becomes a standard feature of a platform we already own, what lasting business value will our investment still provide?
That question should influence build-versus-buy decisions, vendor selection, commercial agreements, and the design of AI services businesses.

AI companies are shutting down. Products are disappearing. Even major technology providers are abandoning AI initiatives.

TechCrunch’s latest AI graveyard highlights Relay, Character.ai, Humane AI Pin, and several other products that failed to sustain their original business models.

S&P Global Market Intelligence found that 42% of surveyed companies abandoned most of their AI initiatives before production, up from 17% the previous year.

That should get the attention of every executive investing in AI.

I see an important distinction between investing in AI technology and building a business that can consistently deliver value from it.

Before committing to an AI solution, leadership should be able to answer five questions:

What specific customer or business problem are we solving?
What measurable financial return justifies the investment?
What makes the solution valuable if the same AI capabilities become standard features elsewhere?
Who owns integration, security, governance, deployment, and ongoing support?
What recurring business value remains after the initial implementation?

For technology resellers and service providers, this is especially important. A profitable AI practice needs more than access to models and products. It needs customer discovery, implementation expertise, managed services, and a repeatable way to deliver measurable outcomes.

The growing AI graveyard is also a reminder that stopping an investment can be the right business decision when the economics no longer work.

The question I would put to every leadership team is simple:

If the AI product you are investing in disappears tomorrow, does the business value you created disappear with it?

That answer tells you a great deal about what you are actually building.

Technology doesn’t create business value. Better decisions do.

Source: https://techcrunch.com/2026/10/24/the-ai-graveyard-a-running-list-of-projects-and-startups-that-didnt-make-it/

Research: https://www.spglobal.com/market-intelligence/en/news-insights/research/2025/10/generative-ai-shows-rapid-growth-but-yields-mixed-results

#ArtificialIntelligence #EnterpriseAI #AIStrategy #AIGovernance

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