The claim that “AI projects are failing” has become a familiar headline—and a valid one. But while the failure rate may be high, it’s not necessarily cause for alarm. In fact, understanding why these ...
Forrester predicts that, in 2026, one-quarter of CIOs will be asked to bail out business-led AI failures in their organizations. With the recent wave of generative AI and LLMs changing how AI is ...
Even as we emerge from generative AI’s tire-kicking phase, it’s still true that many (most?) enterprise artificial intelligence and machine learning projects will derail before delivering real value.
When a software project stumbles—or ultimately fails—it can have a range of negative consequences, from lost and unrecoverable resources to a blow to team morale. It can be tempting to blame a failed ...
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MIT explains why most AI projects are failing
Executives have poured billions into artificial intelligence, only to discover that most of those projects never make it past the pilot stage or fail to deliver meaningful returns. A recent wave of ...
Community driven content discussing all aspects of software development from DevOps to design patterns. Agile software development is one of the most proven approaches to building software and ...
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