THE TECHNOLOGY INTERVIEW deployment requires alignment with business outcomes and a strategy to bring the workforce along.
“ The bigger friction is about people adopting the technology, managing the change,” Vijay continues.“ It’ s a lot easier to do that if you’ re focused on what the business outcomes are. Otherwise it’ s very difficult to be able to put something into production that’ s not aligned and explained to your teams.”
Technological limitations also play a significant role. Many organisations are burdened by outdated IT infrastructure that is fundamentally unsuited for AI integration.
“ We still have about a fifth of data estates which are not modernised,” Vijay explains.“ For AI to work, you need to have high-quality data and that’ s a prerequisite. So data and everything around data – whether that’ s data quality or management – is a constraint on the technology side.” This data challenge is compounded by the state of legacy application estates.
“ Some enterprises have an application estate that is very old and they have to modernise at least some of it, if not all of it,” Vijay says.“ Modernising these systems is not merely an IT upgrade – it is a fundamental requirement for building a foundation upon which AI can operate effectively.”
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