The truth about AI and ROI: Can artificial intelligence really deliver?
Brandon McGee
“CognitiveScale finds that, although execs know that data quality and deployment are critical success factors for successful app development to drive digital transformation, more than 76% aren’t sure how to get there in their target 12-18 month window.
‘AI has to be accountable to drive business effectiveness – it’s not sufficient to say a ML model was 98% accurate.’
Instead, the ROI could be, for example, that in order to improve call center effectiveness, AI-driven capabilities ensure that the average call handling time is reduced.
According to Nicola Morini Bianzino, global chief technology officer, EY, thinking of artificial intelligence and the enterprise in terms of “use cases” that are then measured through ROI is the wrong way to go about AI.
‘It’s almost like tending a farm, because the data is living, the data changes and you’re not done,’ he said. ‘It’s not like you build a recommendation algorithm and then people’s behavior of how they buy is frozen in time. People change how they buy. All of a sudden, your competitor has a promotion. They stop buying from you. They go to the competitor. You have to constantly tend to it.’”
