AI's moment of disillusionment

My InfoWorld colleague, David Linthicum, recently ripped into cloud computing, arguing that 'the anticipated productivity gains and cost savings have not materialized, for the most part.' Linthicum's more measured approach feels correct because it follows what always seems to happen with big new trends: They don't completely crater, they just stop pretending to solve all of our problems and instead get embraced for modest but still important applications.

Linthicum has also taken serverless to task, predicting that 'Serverless technology will continue to fade into the background due to the rise of other cloud computing paradigms, such as edge computing and microclouds.' 'These introduced more nuanced solutions to the market with tailored approaches that cater to specific business needs rather than the one-size-fits-all of serverless computing.'

I'm already seeing companies fail when they treat genAI as the answer to everything, but they are succeeding by using genAI as a complementary solution to some things. Rather, it's time to become thoughtful about how and where to use it. AI should be viewed as a complementary tool, not the only way we work.

Read at InfoWorld