Artificial Intelligence is changing the way projects are managed, but not every AI initiative succeeds. In fact, many AI projects never make it to launch—not because the technology fails, but because of poor planning, unclear goals, unrealistic expectations, and lack of user adoption. In this article, I explore some of the most common reasons AI projects struggle before they ever reach production and the project management lessons we can learn from them.
26 Jun 2026 2 minute read 0 comments Pheace
When I first started using Jira, I thought the hard part of project management would be keeping work organized. I was wrong. The work was usually organized. The challenge was finding the right piece of information at the right moment. If you've manag...
23 Jun 2026 3 minute read 0 comments Pheace
A few months ago, I thought I had everything under control. The requirements were clear. The team was aligned. The kickoff meeting went well. Everyone knew what they were supposed to do. At least, that's what I thought. Three weeks later, the project...
18 Jun 2026 2 minute read 0 comments Pheace
A few weeks ago, while working through a project management exercise, I noticed something interesting. Some of the tasks that would normally take a significant amount of time organizing requirements, drafting updates, identifying risks, and prioritiz...
16 Jun 2026 3 minute read 0 comments Pheace
Artificial Intelligence is everywhere right now. Every week, there's a new AI tool promising to save time, boost productivity, or completely transform the way we work. Companies are racing to adopt AI, and project teams are being asked to "figure out...
