Measuring the success of data science, AI

Kirsten Doyle
By Kirsten Doyle, ITWeb contributor.
Johannesburg, 23 Jan 2023
Dino Bernicchi
Dino Bernicchi

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.

ITWeb BI Summit - 7 to 9 March 2023

Come and hear from a wide range of local and international experts, who will unpack all the burning issues in the BI, data, and analytics sector over three days of insightful presentations, lively panel discussions, and interactive workshops. The ITWeb BI Summit is the event for BI, data, analytics, and AI professionals and decision-makers. For more information and to register, click here.

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.