The Problem Nobody Talks About

Many organizations today are eager to adopt AI, deploy Generative models, or explore Quantum Computing. And yet, most still haven’t solved the basics.

Data strategy remains the weakest link.
Disparate systems, undefined ownership, unclear lineage, and some more, are not just annoying inefficiencies (and boy, are they annoying and inefficient!). They’re risks, sometimes big risks. And they prevent everything else from working responsibly.

You cannot build trustworthy, explainable, or ethical AI on a foundation of scattered, misaligned data.

If this resonates, my book Data Unplugged unpacks this in detail, no fluff, no buzzwords (I did not want to make this or any of my posts a sales pitch but, objectively speaking, this is a good book:-)).

What We Will Explore

I wrote these lines quickly as a starting point so that you get the idea what is coming in the next few weeks and after. I have a lot of stuff to go through and share with you and have to balance it between a number of categories so, if you have a specific topic in mind you cannot wait for, send me a comment. And now that we are talking about topics my readers would want me to talk about next, I promised my dear friend Willem to write something juicy on Data Strategy next so, once I have put in a few lines under each category in the blog, I will jump on Data Strategy again.

Anyway, in the Data Strategy category, I will discuss the following and then some more:

• Why data strategy is not just technical architecture, but organizational architecture,
• The link between governance, ethics, and business value,
• Why most enterprises are still operating on data sandcastles.

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