You don’t need better AI. You need better questions.

The world of enterprise technology is painted with promises of transformation, but behind the glossy presentations and pilot project success stories lies a sobering reality. Business intelligence ...

Vendors are deliberately misinterpreting AI’s high failure rate. While failures do happen, it’s usually because management ...

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 ...

More than 80% of corporate AI projects never make it out of the pilot phase or fail to deliver measurable value once deployed, according to RAND research. This failure rate is two times higher than ...

Your project is on schedule, until legal reviews take way longer than anticipated. You find out—too late—this exact situation happened with another a project a few years ago. Sound familiar?

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.

It is within this context that Madhusudan Nagaraja has been contributing independent advisory guidance as a member of the PMI Infinity Advisory Committee. PMI Infinity, launched in January 2024, is ...

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 ...