Is it just me, or are there more cloud project failures today than 10 years ago? Logic suggests that it improves over time, but metrics do not support that assumption.
A decade ago, a cloud project typically involved migrating several test programs and systems. The systems involved are now much more complex, with many moving parts that affect many or all aspects of a company’s operations. Today’s push towards AI means that complex, data-intensive systems are now the preferred model for cloud systems. Due to skills shortages and planning challenges, these complex systems present serious obstacles to enterprise cloud adoption even on the best of days.
To complete cloud and AI projects correctly, on time, and on budget, you need to bring your A-team together. Unfortunately, Team A has a waiting list for years. Cloud migration and development skills are not sufficient. Many organizations are settling for “less than ideal” talent that makes poor decisions and causes cloud and AI projects to fail.
