According to a recent study by researchers at MIT, 95% of enterprise A.I. projects fail. Why? And how can we be amongst the 5% that succeed?

THE RESEARCH

MIT's NANDA ("Networked AI Agents in Decentralized Archtecture") lab reported a staggering 95% failure rate for enterprise A.I. projects in delivering measurable business impact.
While 40% of firms deploy A.I. pilots, only 5% ever reach production at scale.
The "GenAI Divide": (often secret) high adoption of B2C tools like ChatGPT and Microsoft Copilot, organizational transformation by GenAI is super rare.

WHY MOST PROJECTS FAIL

Static models that don't learn... they can't retain context, adapt to feedback, or evolve with business needs.
Poor workflow integration: Projects stall because they don't mesh smoothly with existing processes.
"Shadow A.I. Economy": >90% of organizations see employees using personal A.I. accounts, often delivering better ROI than official corporate A.I. projects.
Disconnect between tools and actual work patterns... Companies aren't delivering solutions that fit how people really work.

WHAT THE SUCCESSFUL 5% DO

Deploy agentic systems that remember, adapt, and act within specified constraints.
Build models that learn and improve with use rather than staying static.
Focus on tight workflow integration from day one.
START SMALL! Prove value on narrow but critical tasks, then scale systematically (this is the biggest failure point I see personally).
Create tools that embed into daily processes, not just demo bots.

YOUR ACTION PLAN

Shift mindset: Stop chasing hype; start building adaptive, integrated systems.
Chat with A.I. tools (ChatGPT, Claude, Gemini) while using the full MIT NANDA report for context to ideate on ideas.
Get expert support if you don't have it in house: Consider specialized consulting firms like Tribe AI or (shameless plug!) my own firm, Y Carrot, for strategic guidance.
Remember: Transformative A.I. capabilities are available. It's humans that stand in the way of success.

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