The Journey

For almost 20 years, I lived inside the world of market research and media measurement. I understood how advertising worked, how brands measured what actually mattered to gain the holistic business picture.

Then I watched AI transform everything — not gradually, but all at once.

Algorithms began making real-time decisions about ad targeting and audiences. AI was generating creative content, insights, and optimization tactics at a speed no human team could match — and the financial gains were too great for anyone to stop and ask what was quietly being lost.

The Gap

The new AI adoption wasn't a technology problem. It was an organizational barrier.

Analytics teams were pressured to adopt AI quickly, often without any input into how the models were trained, what conditions shaped them, or what assumptions were baked in. Synthetic data was being used to generate insights presented to clients without full disclosure of whether the outputs were actually trustworthy.

The teams who understood research validity, algorithmic bias, and methodology were rarely consulted when decisions were made about AI model selection, risk, and bias. Legal teams and product teams were signing AI vendor contracts.

And nobody was asking the question that mattered most: who is accountable when the insight is wrong?

The Bridge

I pursued AIGP certification through IAPP because I had spent over 20 years shaping research methodologies and insights platforms and delivered actionable recommendations for brands — and I wanted to understand how AI fits within the rigor of market research foundations, sound methodology, and legal and risk frameworks, without interfering with adoption speed and efficiency that makes AI valuable in the first place.

Most AI governance consultants can explain the regulations. I can explain them and tell you what they mean for your measurement stack and your next research brief.

Most compliance experts can flag algorithmic bias. I can flag it and explain what it means for the credibility of your insights.

Most auditors can assess your AI systems. I can assess them and have an honest conversation with your team about what it means for how your organization makes decisions.

The Mission

AI is giving marketing and research organizations something genuinely valuable — time, budget, and cognitive bandwidth that used to go into manual, repetitive fieldwork and analytical work.

My mission is simple: make sure the time AI saves goes into different thinking, not just faster insights reporting.

Into better experiments. Stronger hypotheses. More honest conversations about how AI models are built, trained, and deployed — and what that means for your data, your compliance, and your bottom line.

Responsible AI governance isn't a constraint on innovation. It's what keeps innovation alive.