Don't wait too long

Going with our theme: Don’t want to embrace AI? What’s the worst that can happen?

My answer: That worst that can happen is you can’t embrace AI.

OK, it probably won’t get to the point where you literally can’t, but the reality is the farther you go down the “I’m-not-ready-for-AI” path, the harder it may be to break out.

I found this Data Maturity Model useful. There are many variations of these data maturity models. The point is, “embracing AI” is a journey, and it may be a long one. “Embracing AI” does not mean that a low maturity organisation jumps straight to an advanced state. The very small but critical steps in the beginning may not feel like “embracing” at all.

At a low maturity level, the focus can be on identifying once-off projects that can be replicated to add value to multiple areas of the business. At a mid-level, the organization may focus on assigning ownership of a data strategy at the executive level and restructuring the organization to ensure that data value cuts across the entire enterprise. And at the highest level, embracing AI may mean exploring completely new and cutting-edge arenas.

Where ever you are on your data journey, there are steps that you can take to shift your path and put your organization on a trajectory towards increasing data maturity.

Especially in the beginning, the steps you choose to take may feel down-right imperfect in light of the daunting end goal way out there on the horizon. But with experimentation and guidance, you will find the way forward that works best for your business. The worst step is no step at all.

The diagram is from The Next Frontier for the Industry - Data Maturity Model (2016), by Patrick Dolan, Executive Vice-President & COO, IAB and Ana Milicevic, Principal & Co-Founder, Sparrow Digital Holdings