"On paper, it looked a lot like entrepreneurship: validate an idea, conduct research, raise or allocate funds, build capabilities, codify processes, launch SaaS platforms, measure value creation, and implement a communication plan. In practice, it was very different. Big organizations are optimized for productivity and predictability, not the full lifecycle of experimentation that product building requires. That law of nature creates a constant source of friction between innovation and day-to-day business."
"A new MIT study puts numbers to what many of us have experienced: 95% of enterprise GenAI pilots fail to deliver measurable business impact, despite billions invested. The problem is less about model quality and more about the learning gap: Tools and organizations do not naturally adapt to one another, so in-house pilots never become production systems. MIT and other researchers highlight consistent fault lines:"
An intrapreneurial workflow resembles entrepreneurship on paper—validating ideas, researching, funding, building capabilities, codifying processes, launching SaaS, measuring value, and communicating results. Large organizations prioritize productivity and predictability, which conflicts with iterative experimentation needed for product building. A MIT study finds 95% of enterprise GenAI pilots fail to deliver measurable business impact despite heavy investment. Key failure points include pilots not integrating into workflows, treating AI as one‑off projects, misallocated budgets favoring sales experiments over back‑office automation, lower success rates for internal builds versus vendor partnerships, and widespread unsanctioned use of personal chatbots that complicates measurement and increases compliance risk. Similar dynamics occur across corporate product launches.
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