Why Most AI Projects Fail Before They Start A recent MIT study delivered a staggering verdict: an overwhelming 95% of organizations are seeing zero return on their investments in Generative AI . This isn’t a failure of the technology itself, but a critical misstep in its application. The root cause? Companies are diving headfirst into how to build AI solutions without first rigorously answering what to build.
Introduction You know the search all too well. You type “AI case studies in [your industry]” into a search engine, hoping for a blueprint, a proven result, a spark of validation for your upcoming project. What you find instead is an ocean of generic listicles—AI-generated articles touting the same superficial “top 10” use cases, devoid of specifics, dates, or named sources. They promise potential but offer no proof.
Introduction: Promise vs. Reality Every established enterprise exploring AI has heard the promise: simply ask a question, and intelligent technology will deliver a perfect, insightful answer. But what happens when that promise meets the complex, messy reality of your business data?
One step at a time, we can start your AI journey today, by building the foundation of your future performance.
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