"There is a strong urge to apply AI. Both managers and technical teams feel motivated to make the technology a success. But is that always the right attitude? According to Bryan Harris, we need to return to pragmatic thinking about AI deployment. During his recent visit to the Netherlands, we spoke with the Chief Technology Officer of SAS about why organizations should start with the problem, not the technology."
"A conversation with SAS is almost always about AI. In this case, that's a good sign, because the company was already focusing on software for building and managing models long before the generative AI hype. And with its 50th anniversary coming up in July, that means SAS has seen many forms and trends in analytics and artificial intelligence come and go. Nevertheless, interest in the technology in all its forms has grown at a record pace in recent years."
"According to Harris, this leads to problems. "People are obsessed with AI and not with the problem they are trying to solve," he says. In his view, companies must first identify the problems they have, which ones they want to tackle, and which metrics they want to influence. Only then should you consider whether AI can play a role. This could mean, for example, that you "only" use an AI solution for one problem within your organization."
There is a strong organizational urge to apply AI driven by managers and technical teams. Pragmatic deployment requires starting with concrete problems and target metrics before selecting technology. Longstanding analytics firms have seen recurring trends and rapid recent growth in AI interest. Many organizations launch AI projects without clear objectives, creating distractions as employees pursue career-boosting AI stories. Companies should identify which problems to tackle and whether AI can contribute, sometimes limiting AI to a single use case. The most valuable skill is recognizing when AI adds no value and rejecting it accordingly.
Read at Techzine Global
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