When companies focus on practical, user-centered implementation, AI can stop being an experiment and start having a real impact.
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 ...
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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 ...
This week, an exercise in separating truth from hype. I am old enough to remember when generative AI (genAI) was the best thing since sliced bread — destined to solve any and all problems. But CIO.com ...
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Why more than half of AI projects could fail in 2026
In 2025, to borrow a phrase: the AI revolution is already here; it's just not evenly distributed. While individuals are seeing productivity gains from LLMs or newer agentic systems, larger projects ...
Everyone's talking about how AI will transform healthcare, but here's the thing: most projects never make it out of the pilot phase. This isn't because the algorithms aren't smart enough. It’s because ...
AI didn’t just survive the hype cycle. It won. While the metaverse quietly packed its bags and NFTs became dinner-party punchlines, AI is embedded into the industry’s daily operating system. It now ...
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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