As the field of data science continues to expand and mature, many data science practitioners are battling to demonstrate consistent success with their AI and data science projects when asked by the board and C-suite execs.
While data teams may have delivered some business-changing projects that have tangible results, data science is still science, and much of it involves learning, experimenting, and figuring new things out.
Not every project is guaranteed to produce immediate results, but most will have a long-term impact, and render knowledge that will be useful to the business in the future.
According to Gartner, a staggering 61% of companies deploying AI projects do not measure success, and the ESI ThoughLab claims that 40% of AI projects garner negative or no returns.
With this in mind, Dino Bernicchi, AI Strategy Consulting, will be presenting a talk on “How to track the success of your data science projects – what metrics do you use?” at the ITWeb Business Intelligence Summit 2023, to be held from 7 to 9 March, at The Maslow Hotel in Sandton.
“If you don't measure it, you can't manage it,” he says.
During his talk, delegates will learn how to track the success of their AI projects and which metrics to track.
He will also discuss a structured approach to results measurement for AI and data science projects, as well as how to drive business buy-in and gain positive feedback loops.
Share