Artificial intelligence in corporate management: the advantage lies in how you govern it, not just how you use it.

https://www.linkedin.com/pulse/inteligencia-artificial-en-la-gesti%C3%B3n-corporativa-est%C3%A1-lorenzana-7irce

Over the past few months, I have had several conversations with executives, partners, and finance teams about the same topic: how to integrate artificial intelligence into daily operations without losing control of the business. And the question that comes up most often is not, “Should we use AI?”—that decision has already been made by most companies—but rather, “How do we govern it so that it does not become a risk?”

That is precisely the conversation I want to open today.

Adoption is no longer the challenge: oversight is

In 2026, virtually no competitive company is debating whether it should incorporate AI into its operational, financial, or customer service processes. The relevant question has shifted: from “how much can we automate?” to “how much can we explain about what we automate?”

Regulatory authorities are focusing on very specific issues: how explainable the models a company uses are, whether there are biases in automated decisions, who is accountable when an algorithm makes a mistake, and how the personal data that feeds those systems is protected.

This is not an issue exclusive to technology companies. It applies just as much to a construction company using AI to evaluate suppliers as it does to a finance department using predictive models for cash flow.

The most common mistake: treating AI as an IT tool

From my experience leading strategy and finance, I have identified the same pattern: companies delegate AI adoption to the IT team and treat it as a technical matter, when in reality it is a corporate governance decision.

When a board of directors or executive committee does not have visibility into which AI models the company uses, what they are used for, and what controls are in place, the company is taking on a risk that it is not even measuring.

The difference between companies that will capitalize on AI as a competitive advantage and those that will end up constantly putting out fires lies in three decisions that belong to management, not the IT department:

1. Define where AI should and should not be used. Not every decision should be automated. Decisions involving judgment, legal impact, or relationships with key clients need a predefined point of human review.

2. Document the “why” behind each model. If a company cannot explain in simple terms how a system arrived at a recommendation or decision, that system is a liability, not an asset.

3. Assign clear accountability. Someone within the organization—not an external provider—must be able to take responsibility for what the AI implemented by the company does.

The opportunity behind the risk

I do not want this to be read solely as a warning. The other side of the coin is that companies that build governance around their use of AI today will have a real advantage with investors, business partners, and institutional clients, who are increasingly asking about this in their evaluation and due diligence processes.

In an environment where Mexico is competing to attract foreign investment and strengthen its position as a strategic partner in global supply chains, a company’s ability to demonstrate strong internal controls is becoming a commercial differentiator, not just a compliance issue.

What I recommend, from a business perspective

If you lead a company and are evaluating how to move forward on this issue, my suggestion is to start with three internal questions:

• Do we know precisely where we are already using AI in the company today?

• Who within the organization is responsible for overseeing those processes?

• Can we explain to an investor, partner, or institutional client how we make those automated decisions?

If any of those answers is unclear, that is where the first step lies.