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 ...

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 ...

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 ...

Stretch projects build real skills while advancing your product roadmap. Peer learning preserves institutional knowledge and boosts team collaboration. Upskilling aligned with career growth improves ...

Companies often invest in sales and marketing solutions, but the biggest returns seem to be in back-office automation and streamlining internal processes. The report also found that successful ...

Somewhere in your organization, an AI project is dying. Perhaps it's the recommendation engine that was supposed to boost sales by 30%. Maybe it's the predictive maintenance system that promised to ...