Artificial intelligence is playing an increasingly important role in modern marketing research. One of the areas where it finds application is consumer opinion research using the CATI method. In this article, we explore how AI influences the use of this method in call centers, focusing primarily on voicebot technology, which is gradually becoming a standard in the customer service industry.
CATI (Computer-Assisted Telephone Interviewing) is a quantitative research method in which telephone interviews are conducted with a selected group of respondents using dedicated computer software. During the interview, the interviewer follows a predefined script that guides them through subsequent questions and screens of the questionnaire. The respondents’ answers are recorded directly into the system and can later be used as a basis for analysis and to optimize organizational processes.
Although CATI is a useful and well-established method, it does have certain limitations:
Today, it is widely believed that introducing AI algorithms can help eliminate at least some of these drawbacks.
For the purpose of this article, artificial intelligence (AI) refers to technologies that enable machines and computer systems to make independent decisions and perform tasks traditionally handled by humans. In our case, we focus on voicebots — AI-driven systems designed for natural, spoken interaction.
Many companies are seeking to streamline their business processes by integrating AI solutions. One increasingly popular innovation is the voicebot, offered by IT providers specializing in business automation. Voicebots are programs that allow spoken communication between customers and organizations. By combining technologies such as speech recognition and natural language understanding (NLU), voicebots can respond to customer questions without human intervention — accelerating the research process while improving the user experience.
AI-powered voicebots should not be confused with the older IVR (Interactive Voice Response) systems. IVR allows interaction through pre-recorded voice prompts and keypad inputs. The caller responds by pressing a key, and the system executes a predefined action — for example, providing an answer or redirecting the call to a live agent.
Voicebots, on the other hand, enable more natural, personalized, and flexible interactions. They engage in richer conversations, going beyond the rigid structure of IVR menus and button-based navigation.
Using voicebots in CATI research offers several key benefits:
Overall, AI-driven voicebots improve both efficiency and data quality in research processes.
Artificial intelligence in marketing research is not limited to voicebots. Another promising application is emotion analysis — software-based evaluation of respondents’ emotional states during interviews. By identifying emotions expressed in tone, pace, and choice of words, AI can help researchers refine questionnaires, improve interviewer performance, and gain deeper insights into customer attitudes.
Implementing AI in CATI research also introduces new challenges.
First, companies must train employees to manage and supervise the new systems. Even though AI can partially replace interviewers, human oversight remains essential to ensure data quality.
Secondly, the credibility of results may be affected by respondents’ biases — some participants may react negatively when realizing they are interacting with artificial intelligence. Moreover, current AI limitations can lead to incomplete or inaccurate interpretations, especially when respondents give unconventional or unexpected answers.
A potential solution to these issues is programming voicebots to transfer the call to a human operator when they encounter confusion or cannot interpret the respondent’s response.
CATI is a structured, computer-assisted quantitative research method involving scripted phone interviews. As technology evolves, integrating AI into this process is becoming increasingly valuable. Voicebots — capable of autonomous, spoken interaction — are emerging as an industry standard, enabling faster data collection and lower costs.
Another way AI enhances CATI is through emotion analysis software, which provides richer insights into respondent behavior.
However, companies adopting AI in CATI research must be mindful of potential challenges — from user skepticism toward AI interactions to technological constraints. With careful implementation, AI can significantly improve research efficiency, accuracy, and scalability while opening new possibilities for data-driven decision-making.
