Why research analytics built on AI needs to show its working

Merely appearing useful – versus being reliable, credible or provable – are different things, writes Kate Byrne In the past two years, the research analytics market has – like most markets at the moment – flooded with AI. Every significant platform now claims it. The language is familiar: AI-powered, AI-driven, AI-enhanced. Most of them return something that at least looks useful, fast. We are quickly learning, however, that merely appearing useful versus being reliable, credible or provable – when the stakes really matter – are different things.