Living on Both Sides of AI

Why Vendor Transparency Became My Competitive Advantage in Building Trustworthy Business

How My Job Search Changed the Way I Evaluate AI

I never expected my job search to influence the way I lead my business. Yet somewhere between submitting applications and teaching organizations about responsible AI, I found myself viewing artificial intelligence from two very different perspectives.

Like many professionals, I know AI may play a role in determining which opportunities move forward and which quietly disappear before I ever speak to another person. I cannot see those systems. I cannot evaluate the governance behind them. I cannot control how every organization develops, tests, or deploys artificial intelligence.

What I can control, however, is how I respond as a founder.

That realization challenged me to become even more intentional about the questions I ask, the technology I trust, and the companies I choose to do business with.

Asking the Questions Many Businesses Never Think to Ask

As the founder of a company specializing in digital safety, cybersecurity, and AI governance, I made a deliberate decision to contact the technology vendors my organization pays and ask questions that many businesses never think to ask.

I wanted to understand:

How artificial intelligence was being used behind the scenes.
How prompts and uploaded information were handled.
Whether customer content could be used for model training.
Whether third-party AI providers were involved.
How unpublished business materials were protected.
What governance practices were in place to support responsible AI.

I also wanted to understand how vendors identify, assess, monitor, and mitigate potential bias within their AI systems because fairness should be evaluated alongside security, privacy, transparency, and accountability.

I wasn't trying to catch anyone doing something wrong. I was trying to determine whether responsible AI, transparency, accountability, and continuous governance were treated as core business values—or simply another marketing statement.

The Responses Changed Me

Some organizations welcomed the conversation with thoughtful, transparent answers that demonstrated a genuine commitment to responsible AI.

Those companies earned something far more valuable than another customer.

They earned more of my trust.

Other responses left important questions unanswered or relied on broad statements that created more uncertainty than confidence.

That experience fundamentally changed how I evaluate technology vendors.

We spend countless hours comparing pricing, features, integrations, and customer reviews, yet we rarely stop to ask how the technology itself is governed.

Today, transparency carries just as much weight in my decision-making as functionality because trust should never depend on assumptions. It should be supported by evidence.

The Visibility Gap

This experience also reinforced something I explored more deeply in my recent article, The Lawsuit Is Not the Story. The Visibility Gap Is.

The public conversation about artificial intelligence often centers on whether systems are biased. That conversation matters, but I believe an even larger one is waiting to happen.

The more important question is whether organizations can demonstrate how their AI systems are governed, monitored, documented, and held accountable.

As leaders, we should become comfortable asking whether organizations publish documentation such as model cards or system cards that explain intended use, limitations, bias assessments, testing, safeguards, and ongoing oversight.

If those resources aren't publicly available, we should feel comfortable asking organizations how they identify, assess, monitor, and mitigate potential bias—and how they build, evaluate, and govern trustworthy AI.

Transparency should not be reserved for regulators or engineers. It should become part of how every founder, executive, nonprofit leader, educator, and small business owner evaluates the companies they choose to trust.

Leadership in the Age of AI

Technology will continue to evolve faster than any of us can predict.

New models will emerge.

New regulations will follow.

New headlines will capture our attention.

I cannot change every hiring system, rewrite every algorithm, or influence every company building artificial intelligence.

What I can change is who earns my business, where I invest my resources, and the standards I refuse to compromise as a leader.

Every purchasing decision I make is now part of my governance strategy because every vendor I choose reflects the future I want to help build.

Leadership in the age of AI is no longer defined solely by how quickly we adopt new technology.

It is defined by whether we have the courage to ask better questions before trust is given instead of after it has been broken.