AI AND ML
“ Don ’ t believe the hype .”
While it may take many by surprise , that ’ s the fresh call to action among analysts paying close attention to how companies are – or aren ’ t – factoring artificial intelligence ( AI ) and machine learning ( ML ) into their data management plans and playbooks .
After years of reading sensational stories about the limitless potential of intelligent machines , stakeholders and C-suite , executives in particular appear to be confused about the best course of action to take . Commercial missteps and the total failure of some products have resulted . Experts say it doesn ’ t have to be this way .
“ AI and ML has become crucial and necessary for nearly all businesses in every sector ,” says Elliott Young , CTO , Dell Technologies UK . “ In the same way that businesses have had to transform digitally and become digital-first , companies are going to need AI and ML to remain competitive . Those on the path towards this are already reaping the benefits of being able to make decisions driven by predictive analytics .”
But most boardrooms and bosses don ’ t fully understand the potential use cases for AI and ML . “ Stakeholders often don ’ t know what to ask for in order to get the right benefits out of the technology ,” says Young .“ This means they don ’ t really know what their business could be missing out on .
“ Likewise , leaders can be guilty of thinking that AI and ML sit siloed within a technology function , and that departments specialising in IT and tech will bring working AI , ML , and data strategies to them fully formed . This is unrealistic .”
This sense of corporate confusion has also been identified by Gartner , who say unrealistic expectations have led to poor decision making , disappointment among stakeholders , or outright failure for AI-related business products .
“ Overhyped AI scares people and masks the real benefits AI can offer to humanity ,” says Anthony J . Bradley , Gartner ’ s Group Vice President , Emerging Technologies and Trends Research . “ This can lead to slower adoption , and even sociopolitical fear and government regulation that will stifle progress . There are real concerns over the appropriate and ethical use of AI / ML , but AI eliminating the need for humans is not one of them .”
Bradley also claims overhyped AI muddies the waters between human and
124 November 2022