"Your organization announced an AI initiative, the leadership bought licenses, and someone launched a pilot. The quarterly review called it a success. Six months later, nobody uses it. This pattern isn't new; remember the Agile transformation that became process theater, or the digital transformation that produced dashboards nobody reads? What about the DevOps push that added tools, processes, and layers without changing behavior? AI initiatives fail for the same reasons, and you can spot the failure early enough to do something about it."
"Over the past several weeks, I reviewed four sources on why AI transformations fail: Harvard Business Review's 5Rs framework, Simon Powers' work on organizational fields, Barry O'Reilly's due diligence framework for AI ventures, and Paul Roetzer's research on AI adoption as change management; see below. From these, I (with Claude's support) have built a diagnostic taxonomy of 166 distinct AI transformation anti-patterns across 16 categories."
AI initiatives commonly fail because people, culture, and processes are not addressed. Organizations often launch pilots, measure short-term success, and then see usage vanish after a few months. Past transformations like Agile, digital, and DevOps show similar patterns where tools and ceremonies replaced actual behavior change. A synthesized review of multiple frameworks produced a diagnostic taxonomy of 166 AI transformation anti-patterns across 16 categories. Organizational failures (governance, roles, process, culture) represent roughly 65% of failures, technical issues about 22%, and contextual factors make up the remainder. A 10-item anti-pattern checklist enables early detection of problems.
Read at dzone.com
Unable to calculate read time
Collection
[
|
...
]