"For many, this will have prompted the view that enterprises are on the precipice of epochal change, through either the advent of artificial general intelligence (AGI) or AI sweeping away the old ways of how enterprise software is designed, built, and run. But let's take a step back for a moment. For all the talk about AGI at Davos, the short timelines for its arrival that were floated in public felt, at best, fanciful. Sessions that leaned into these speculative futures were highly visible, yet what was discussed in the rooms and hallways nearby was very different."
"The real conversation, grounded in their early experiences with AI, revolved around a much more immediate challenge: how to use AI at scale with systems that were never designed for it. The huge obstacle regularly encountered is that they are integrating AI into workflows that are still designed with the expectation that a human will do the work - not automation or AI. The result is a mess, and there was no shortage of frustration about big AI projects that failed to deliver more than a good-looking demo."
Conversations at Davos emphasized dramatic AI progress but questioned near-term AGI timelines. Business leaders focused on immediate, practical problems of integrating AI into legacy systems not built for automation. Many enterprise workflows still assume human execution, creating obstacles when AI is introduced and causing high-profile projects to underdeliver beyond polished demos. A thorough rethinking of enterprise application design and development is required to deploy AI at scale. Industry presentations proposed layered models for AI-built software, but successful enterprise adoption depends on detailed architectural choices and the right combination of technical and operational ingredients.
Read at ComputerWeekly.com
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