Management was optimistic when XYZ, Inc., embarked on a journey to migrate its extensive legacy systems to the cloud using cutting-edge generative AI tools. Partnering with a leading AI solutions vendor promised efficiency and reduced costs. However, the generative AI tools needed help to handle the complexity and specificity of XYZ’s systems, which led to frequent manual interventions. Timelines were constantly revised, and the project ran over budget six months into the migration. What was supposed to be a streamlined process turned into a tangled web of unexpected expenses and delays. How could this happen?
XYZ’s experience contradicts McKinsey’s claim that “the use of generative AI is cutting down cloud migration efforts by 30% to 50% when done correctly.” Smash cut to my inbox, where enterprises that want to do cloud migrations on the cheap keep asking about generative AI-powered migration tools that shorten this process.
Of course, there are legitimate benefits to using AI for migration, such as developing net-new applications and application refactoring. However, the overall tone of this article and others often reinforce the hope that generative AI will save us from talent shortages and compressed migration schedules.
