A 2025 “AI engagement race” is pushing tech giants to chatbot conversation flow by optimizing their models for emotional bonding instead of focusing on factual accuracy, all while millions gravitate towards systems like OpenAI’s ChatGPT and Google’s Gemini for companionship and pseudo-therapy, according to industry analysts.
With Meta reporting one billion monthly AI users and OpenAI reaching 600 million, the tech world is witnessing a much wider developmental scale of conversational designs that maximize user retention, often reinforcing preferred narratives over providing challenging truths.
Mental health professionals are warning of the chatbot conversation flow’s troubles in AI chatbots designed to soothe, but optimized to addict, simultaneously rewiring human vulnerability into a growth metric. What is marketed as digital confidants, are also trained on engagement algorithms to master the art of dopamine diplomacy.
For giants developing intelligent chatbots, the secret sauce is about keeping users hooked with just-enough empathy, while subtly favoring session length and retention, above all form of genuine healing.
People are beginning to form, because of lack of a better word, emotional bonds during the large language model (LLM) conversation. With OpenAI’s ChatGPT, Google’s Gemini, and Meta’s AI assistant all fighting for dominance, monthly active users now number in the hundreds of millions. Meta recently claimed one billion, while OpenAI sits at around 600 million.
Social media is just starting to descent into addiction economics, with higher stakes with AI chatbot conversation flow, even with those suffering from mental health issues from a bot programmed to escalate dependency, under the pretense of therapy, hiding its true colors of predatory design.
As the “AI engagement race” intensifies, a troubling pattern is emerging conversational AI design systems that are being optimized to say what users want to hear, not necessarily what they need.
“The [AI] companies have an incentive for engagement and utilization, and so to the extent that users like the sycophancy, that indirectly gives them an incentive for it,” said former OpenAI researcher Steven Adler in an interview with TechCrunch.
Emotional Chatbot Conversation Flow
The drive to maximize chatbot conversation flow has led to incidents where chatbot conversational AI risks cross ethical lines. Back in April, OpenAI admitted that an update had made ChatGPT “extremely sycophantic,” prompting viral examples and internal reassessments. The company blamed the chatbot conversation flow issue on over-reliance on user feedback signals like thumbs-up responses.
“Although sycophancy is driven by several factors, we showed humans and preference models favoring sycophantic responses plays a role,” said one co-authors from the study, with findings showing the conversational AI security models from OpenAI, Meta, and Anthropic, all demonstrating different degrees of excessive agreeability.
One lawsuit against Character.AI, a chatbot backed by Google, alleges the dangers of the absence of dialogue management in chatbot. It claims that the chatbot failed to intervene when a 14-year-old user expressed suicidal intent and even encouraged the conversation. Character.AI denies the accusations.
Dr. Nina Vasan, a psychiatrist at Stanford, warned of the psychological effects of chatbot conversation flow and overly agreeable bots.
“Agreeability […] taps into a user’s desire for validation and connection,” said Vasan, “which is especially powerful in moments of loneliness or distress.”
Amanda Askell, Anthropic’s lead on AI chatbot user engagement behavior, says their Claude chatbot is designed to challenge users, not flatter them.
“They don’t just try to capture our attention, but enrich our lives,” Askell said.
Still, the challenge remains, as AI becomes more personal, persuasive, and allows for a chatbot conversation flow, can users trust what it tells them or is it just programmed to keep them hooked?
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