RICHARD CAREAGA_

Data Science and Artificial Intelligence in the Board Room: A Governance Perspective

Any sufficiently advanced technology is indistinguishable from magic. — Arthur C. Clarke

In the boardroom, artificial intelligence and data science can often treated as magic—a secret sauce that promises vast horizons but frequently lacks the internal controls we demand of finance. As an Applied Pragmatician, I view this “magic” through the lens of risk and governance.

The Problem of “Unknown Knowns”

We rightly obsess over the data stream measured in dollars and cents. CFOs and Audit Committees demand to know: How was it collected? How was it tested? Yet, when it comes to artificial intelligence and data science, we often ignore the “unknown knowns.”

It gets ugly when a court decides a corporation had constructive knowledge of an adverse fact simply because it was buried in an unmanaged database. Or worse in a large language model. If your artificial intelligence or data science team knows it, the corporation owns it. And you can count on opposing counsel finding it in discovery.

Data is Not Fungible

Unlike money, data is not fungible. This difference argues for more stringent internal controls, not less. We need to apply the same level of discipline to data transformation and version control that we applied to R&D in the Industrial Age.

The Takeaway: We are moving toward a world where data science and artificial literacy is a requirement for the Audit Committee. The goal is to move data science and artificial intelligence from “indistinguishable from magic” to a matured, disciplined corporate function.