Is it just me, or are we seeing more cloud project failures today than 10 years ago? Logic suggests we improve over time, but the metrics don’t support that assumption.
A cloud project 10 years ago typically involved migrating a few test programs and systems. Now, the systems involved are much more complex, with many more moving parts that affect multiple or all aspects of an enterprise’s operations. Today’s push toward AI means that complicated, data-intensive systems are now the preferred models for cloud systems. Due to the skills shortage and planning problems, these complex systems present significant obstacles to enterprise cloud adoption even on a good day.
We need to call in the A-Team to get cloud and AI projects done on time, done on budget, and done right. Unfortunately, the A-Team has a years-long waiting list. There are just not enough cloud migration and development skills to go around. Many organizations are settling for “less than ideal” talent who make incorrect calls and put cloud and AI projects on the path to failure.
