Staying Relevant in Market Research in the Age of AI
- egonzalez267
- Jul 14
- 2 min read
At Intuify, we get this question a lot:
“What should we be doing to stay relevant in market research as AI continues to evolve?”
We use a ton of AI in our work—but let’s be clear: it doesn’t solve everything. In fact, some of the biggest challenges in modern research still require human insight, strategic design, and creative thinking. Here are five real-world challenges that AI hasn’t yet cracked:
1. The Say-Do Gap: People say one thing and do another. They claim they’d never pay $25 for a new shampoo… then buy it the next day. They insist they’re switching banks soon… then stay put for five years. This behavioral gap has always been tough to measure—and synthetic respondents can actually worsen the problem, not solve it.
2. Response Fatigue and Boredom: Despite 30 years of tech innovation, most surveys are still dull and dated. While AI has enabled conversational open-ends, it hasn’t truly reinvented quantitative data collection. Most surveys still offer a terrible customer experience—and if respondents are bored, we’re all losing valuable insight.
3. Truthfulness in Responses: Respondents don’t always lie, but they often don’t tell the full truth. Whether it’s social desirability bias or unconscious rationalization, standard survey design rarely uncovers the real story. AI can assist with analysis—but it hasn't replaced thoughtful research design that teases out nuance.
4. Good Sampling & Response Quality: Sampling has actually declined in quality with increased automation and outsourcing. At Intuify, we often work closely with panel providers to coach on better sampling practices. And when it comes to fraud prevention, AI isn’t the solution—it’s frequently part of the problem.
5. Modeling Latent Drivers: AI is great at correlation—less so at explanation. Building models that truly make sense (and drive action) remains an expert task. Many automated outputs are shallow or circular (“trust is predicted by trustworthiness”). Tools like conjoint haven’t evolved much, either. To get meaningful outputs, expert design still matters.
So What Does Stay Evergreen?: What skill will still matter 10 years from now?
Not just storytelling or data synthesis (AI is getting scarily good at those). What we believe will remain essential is organizational engagement—the ability to design research around real business needs and guide activation across product, marketing, and strategy.
This is not something AI can automate. It requires business acumen, stakeholder alignment, and real-world judgment. And it's something we actively practice—and help our clients build—every day.
Want to learn more about how we’re applying AI and human insight together? Let’s connect.