Will Artificial Intelligence (AI) Replace Marketing Researchers?

March 12, 2024

Artificial Intelligence (AI) augmentation is the future of Marketing Research. At Q2 Insights, we are early adopters and fans of using AI to augment the process of generating research findings and insights. While not completely perfected yet, there are several tools that are already immensely powerful and efficient at culling through volumes of qualitative and quantitative data to identify areas of agreement/disagreement, consensus, and multivariate statistical outputs such as market segments.

Given the growth of AI in Marketing Research, the big question is:  Are we Marketing Researchers soon going to be jobless? The simple answer is yes and no.


The jobs most likely to be replaced by AI cluster around the two extremes of data analysis (mostly quantitative but also qualitative):

  • The highly tedious such as those who engage in data cleaning, coding both quantitative and qualitative data, and the mechanical aspects of report writing such as generating graphics is at one extreme
  • The highly skilled such as those that employ multivariate statistical analysis for tasks such as market size and potential studies is at the other extreme.

Unless they reinvent themselves as AI wizards or they find a way to augment or improve AI outputs, those working in support roles and pure analysis jobs may be in jeopardy. The most obvious reason that AI will replace tedious jobs is because AI is more efficient at tasks such as data cleaning and coding. AI can complete this process in a matter of minutes rather than days, which is especially important when dealing with open ended data that can take a long time to code. A person cannot code or clean data in minutes or as accurately as a well-programmed computer program can.

The more highly skilled job of statistical analysis is complex, but computers are becoming more able to do this without expert/human intervention. A computer can automate complex statistical procedures and put them in the hands of those who are not trained in statistics. The computer will be the analyst, not the human. AI can also build instant graphics that display quantitative data in an easy to understand format.


The jobs least likely to be replaced by AI are primarily in the areas of research strategy and insight generation. Therefore, executives and managers of research strategy (e.g. VP of Marketing Research) and consumer insights (e.g. Ethnographers or Consumer Insights Managers and Directors) are the least likely to be impacted, although the way they work may change.

Building the Research Strategy

The core of good Marketing Research is developing a research strategy. Machines cannot plan or design. Developing a research plan, knowing what methodologies are best, and who to include in the research are all necessary and they are still the job of a skilled, experienced researcher.

Research designs can get complicated. Although machines/computers assist with this process, they are not able to create. Likewise, writing a survey to accomplish specific objectives is a human job. It is true that surveys can be automated, and many are provided via the internet. However, designing anything more than a rudimentary, short questionnaire can be too complex for these automated services.

The simple act of sorting information into qualitative and quantitative data is difficult for AI. When planning the research, it is important to know and understand the difference between these two types of research, and the role that each play in getting the best market information. In many cases, both types of research are used together to obtain the most meaningful information from a target audience.

Interpreting Human Emotions

Humans remain the most advanced pattern recognition machines. Although AI can assist in analyzing qualitative data, AI cannot pick up on the emotional nuances that humans recognize. Nor can AI pull in disparate ideas from different sources to form an insight. For some Marketing Researchers, the intellectual ability to identify rich insights has become instinct. An experienced human researcher will notice, register as important, and interpret the emotions of respondents.

Empathy and sympathy are uniquely human, and they yield some of the best insights. Ethnography is a special case in which empathy and most of the senses are used in real time. The Ethnographer relies on all their senses to gather information from a respondent, while a machine does not have any senses to help in interpreting information.

Skilled researchers not only read the emotions of respondents but also interpret body language. Signals such as teeth grinding, arm crossing, flushing, or anger yield vital cues to learning and insight development. While AI is approaching being able to identify emotions from visual cues, humans are born with an innate ability to respond to these cues either unconsciously, or in the case of the skilled researcher, consciously.

While AI attempts to detect patterns of responses, senior researchers will often have their interest piqued by one comment that, when combined with many other learnings, results in pivotal findings for a brand. To date, AI does not have these types of “ah hah” moments.

Interpreting (Emotional) Data

Although AI can sort and recognize patterns in enormous databases, they are not able to interpret or generate insights. Not only can the researcher identify important findings, but they can take disparate ideas/findings and put them together into a new concept. This is one of the most important roles of the Marketing Researcher.

An experienced Marketing Researcher can present and communicate insights found during the collection of information across an organization using various means of reporting. Telling the story of research findings and insights challenges both the client and the researcher to think deeply about the results to form new connections.

The key to reaching people is through their emotions and getting to the emotional aspect is key to ensuring your product is addressing the needs of the target market. For example, AI cannot convince Kodak they are in the business of creating memories, not photos. The element of human emotion and interpretation is key to getting the best information possible regarding a company’s customers. After all, emotion drives many of the buying choices people make daily.

Finally, computers are not able to “sell” solutions to clients and computers cannot ensure that research will be put to good use. It is the jobs of the Marketing Researchers and Marketing Managers to provide a research report with actionable recommendations. These are the changes or additions a company should pursue based on the research findings and insights. This is the ultimate interpretation of the data collected.


Some believe AI in Marketing Research will create more jobs than it renders obsolete although different skill sets may be necessary. Understanding the difference between the functions that can be done by AI, and those that cannot, is the key to understanding how the use of AI will affect Marketing Researchers in the future.