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Saturday, 3 October 2026dailybeirut.com
AI
Marketing expert Furkat Kasimov argues AI must address consumer ambivalence, not just interests, to resolve decision conflicts.
Consumer hesitation often stems from conflicting priorities rather than a lack of information. While artificial intelligence can identify specific interests through personalized messaging, it frequently fails to account for the psychological ambivalence that prevents action. This gap between recognizing desire and understanding reluctance defines the current limitations of algorithmic marketing.
Furkat Kasimov, founder of AppLayerAI, suggests that AI marketing requires deeper attention to the psychology driving consumer decisions. His perspective highlights a critical question: How much does identifying an interest reveal about the difficulty of choosing? Personalized communications may feel accurate yet remain incomplete because they do not necessarily uncover the competing feelings that hinder acting on those interests.
Consider a scenario where advertisements appear in a feed after browsing a career-enhancing course. The messages mention desired skills and industry opportunities, suggesting a next chapter is within reach. Despite this relevance, the user does not sign up. The disconnect arises because the message recognizes an interest while the decision involves a conflict. The individual may want to progress but feels exhausted by the prospect of proving themselves again, or they may be interested in leadership but reluctant to lose aspects of their current role.
Ambivalence involves holding conflicting evaluations about the same possibility. For example, two people researching the same qualification might compare fees and read testimonials. One feels excited about a promotion, while the other worries about being left behind. These descriptions are often too simple; the excited person might fear responsibility for others' performance, and the worried person might resent the expectation of constant skill acquisition. Both are moving toward something desirable while trying to protect something already valued.
Research demonstrates the potential for large language models to generate personalized persuasive messages based on recipient characteristics. However, this capability does not establish that a message has accurately identified someone’s conflicting motives. A useful inquiry remains: “What do I want here, and what am I reluctant to give up?” More encouragement to advance does little to resolve uncertainty about the cost of advancement.
The way a message frames a choice influences judgment even when underlying possibilities remain unchanged. Describing a course as “Prepare for your next opportunity” brings a possible gain into view, whereas “Keep your skills from becoming outdated” highlights a potential loss. Research on decision framing showed that preferences between risky and certain options could shift when equivalent outcomes were described in terms of gains or losses.
Kasimov’s argument emphasizes how framing attracts responses, but the psychological question extends further: Which concern does the message bring into focus, and which considerations remain unaddressed? An advertisement about outdated skills might resonate with an existing worry, but resonance alone does not indicate whether that worry is proportionate or if the course would actually address it. Sometimes, additional facts help, yet the central question remains: What matters most at this point in your life?
Difficult decisions often appear to be information problems, leading individuals to search for another detail that might make the answer obvious. However, when choosing between jobs offering greater status versus more time at home, the core issue is prioritization. Kasimov also highlights choice overload as a consideration in designing AI marketing messages. Recognizing that a message captures part of the story while leaving out the rest allows consumers to consider what they might gain by declining.
