When companies focus on practical, user-centered implementation, AI can stop being an experiment and start having a real impact.

AI Projects Are Failing at an Alarming Rate Enterprise AI adoption is accelerating. Budgets are growing. Boards expect measurable outcomes. Yet most AI initiatives fail...Read More The post Why 70% of ...

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.

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 ...

Boards are starting to ask tougher questions about money sunk into AI. Interrogations into the value of AI projects are an opportunity to re-focus. Concentrate on capacity building, strong ...

American enterprises spent an estimated $40 billion on artificial intelligence systems in 2024, according to MIT research. Yet the same study found that 95% of companies are seeing zero measurable ...

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 ...

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 ...

While major players like TCS and Infosys rely on broad platforms such as ignio or Topaz, the smarter shift is toward modular, industry-specific solutions that focus on speed instead of building ...