Two Stages of Artificial Intelligence Development in the Consumer Context
Over the past fifteen years, artificial intelligence has developed in two significant directions that fundamentally affect consumer behavior. The first stage is associated with predictive AI, whose main task is consumer data analysis and decision forecasting. The second, much newer stage, is generative AI, which not only predicts but also creates content, ideas, and solutions. This transition fundamentally changes how companies understand, influence, and interact with consumers.
Predictive AI and Algorithmic Decision-Making
Predictive AI is based on algorithms that analyze consumers' digital footprints, including previous behavior, interests, demographic data, and interactions with digital platforms. Such algorithms are used in recommendation systems, advertising targeting, price personalization, and automated consulting. Consumer decisions in such an environment are formed as an interaction between human choices and algorithmic selection, which significantly influences information flow and visible offerings.
Negative Consumer Reactions to Algorithms
Research shows that consumers often prefer human-made decisions, even when algorithm-provided results are objectively better. This phenomenon is called algorithm aversion in the literature. It is driven by perceived algorithm inauthenticity, moral concerns, privacy risks, and the feeling that algorithms do not account for the individual and unique consumer context. Negative reactions are also amplified in situations where algorithms are perceived as a tool for company interests rather than a promoter of consumer benefit.
Positive Consumer Reactions and Algorithm Acceptance
At the same time, research confirms that algorithm acceptance can be significantly increased. Consumers view AI solutions more favorably when they have the opportunity to maintain some control, when algorithm operation is explained in an understandable way, or when the algorithm's ability to learn and improve over time is emphasized. A more positive attitude is also observed in utilitarian tasks, objective decisions, and situations where algorithms reduce social tension or feelings of shame.
Generative AI as a New Stage in Consumer Behavior Influence
Generative AI marks a new development stage in which artificial intelligence can create text, images, ideas, and other content-based solutions. In this context, two types of generative AI are distinguished: convergent, which is oriented toward specific task execution and personalized content generation, and divergent, which is focused on creativity, idea generation, and searching for new solutions. Such AI capability significantly expands the possibilities of personalization, innovation, and marketing effectiveness.
Impact on Business and B2B Marketing Practice
In the business context, generative AI opens opportunities for mass personalization, automated marketing research, and even the use of synthetic consumer models. At the same time, it creates new challenges related to reliability, content truthfulness, authorship, and ethics. In the B2B environment, these technologies can significantly change sales, strategic planning, and customer relationship management approaches if they are implemented with a clear understanding of consumer psychology and perception.