I got invited to share my thoughts on synthetic research and digital twin technology in Food Industry Executive.
Not as a paid advertorial. Not as a press release disguised as content. As actual editorial coverage about methodology and outcomes.
That matters because trade publications are conservative. They don’t chase trends. They cover what’s already working in production environments, not what sounds interesting in a pitch deck.
When Food Industry Executive calls, it means synthetic research has crossed from “interesting pilot” to “thing professionals need to understand.”
Here’s what I told them: Synthetic research, when implemented correctly and with population-true foundations, delivers insights that look the same as human research.
That’s not marketing language. That’s what the validation data shows.
The key phrase is “when implemented correctly.” Bad synthetic research is worse than no research. It gives you confident answers to the wrong questions, calibrated to nothing, validated against nothing.
Good synthetic research (built on actual population data, calibrated to real distributions, validated against human panels) produces results you can use to make million-dollar decisions.
The industry is starting to understand the difference.
Coverage like this signals a shift. Three years ago, this conversation would have been about whether AI could ever be trusted for research. Now it’s about implementation methodology and validation protocols.
We’ve moved past “is this real” to “how do we do this right.”
That’s progress.