The influence of AI tools on market research
Editor’s note: Andrea Mitlag is the regional engagement director for the APAC region at Infotools, responsible for driving business growth and ensuring client success with the company's data insights software, Harmoni. Find Mitlag on LinkedIn.
After working in research for decades, I have seen the industry move through several waves of change. From in-person focus groups and paper surveys to digital platforms and now AI-supported tools, each shift has brought new efficiencies and new expectations.
What stands out now is how these changes are showing up. Alongside rapid advances in artificial intelligence, there are signs that some behaviors are moving the other way. Schools are reintroducing handwritten exams, creative hobbies like sewing and knitting are seeing renewed interest and people are actively seeking out analogue activities. In research, there are still teams relying on face-to-face methods, including door-to-door interviewing in certain contexts.
I don’t believe this suggests a rejection of technology; it is definitely more nuanced than that. As tools become more powerful, there is a growing awareness of what can be lost when the human element is reduced too far.
How the transition looks for market researchers
AI is already reshaping how studies are designed, how data is processed and how insights are delivered. It can accelerate workflows, surface patterns quickly and make analysis more accessible across organizations. These are meaningful advances, particularly for teams working with large and complex data sets.
At the same time, the core purpose of research has not changed. The role is still to understand people, represent their experiences accurately and ensure that those perspectives inform decisions. That requires judgment, context and a level of interpretation that goes beyond what any tool can provide on its own.
Earlier in my career, research was often more direct. Qualitative researchers would sit in a room with participants, observe body language, listen closely to how people expressed themselves and pick up on the nuances that do not always translate into structured data. Surveys were slower (door-to-door, phone, mail), analysis took longer and the process required a different kind of patience.
Those methods had limitations, but they also created a strong connection to the people behind the data. That connection is something worth holding onto as the industry continues to evolve.
Refocusing on research fundamentals
One of the risks in the current environment is assuming that better tools automatically lead to better insights. Speed and scale can improve efficiency, but they can also create distance from the underlying behavior being studied. When that happens, there is a tendency to rely on outputs without fully understanding how they were generated or what context might be missing.
This is where fundamentals become critical. Understanding how to frame a research question, how to design a study that captures the right information and how to interpret findings within a broader context are skills that remain essential. They provide the foundation for using new tools effectively, rather than being guided by them.
There is also a responsibility that comes with how research is applied. At its best, research gives people a voice, creating a way for customers, communities or stakeholders to share their experiences in a form that can be understood and acted on. The role of the researcher is to represent that input accurately and to ensure it is used responsibly.
That perspective can be overlooked when the focus shifts too heavily toward optimization or efficiency. It is easy to move from understanding behavior to trying to shape it, particularly in commercial settings. Maintaining a clear view of the purpose of research helps keep that balance in place.
Finding the right balance
The current moment does not call for choosing between human and artificial intelligence. Both have a role to play, and the most effective approaches will draw on the strengths of each. AI can support exploration, highlight patterns and reduce manual effort. Human expertise provides a cultural context, asks better questions and ensures that insights are grounded in reality. Researchers must now bring these together in a way that actually improves the work.
That starts with a clear understanding of the basics. Knowing what good research looks like, being able to ask the right questions, investigate the results, look for what is left unsaid and stay close to the people behind the data – all this helps ensure that new tools are used with intent.
Looking back over the past few decades, the methods have changed significantly, but the underlying role has remained consistent. Research sits between organizations and the people they serve. It helps translate experiences into insight and insight into action. Looking at where things are heading, that role feels even more important now.