How do AI models persuade? Exploring the levers of AI-enabled persuasion through large-scale experiments

Today, we published in Science the results of a study carried out with colleagues at the Oxford Internet Institute, the London School of Economics, Stanford University and MIT, examining how conversational AI can shape political attitudes. Through three large‑scale experiments with over 76,000 participants, we tested the persuasiveness of 19 AI models on more than 700 political issues.

Our goal was to understand the levers of persuasion with conversational AI: what makes it effective, and under what conditions. We were interested in answering questions like: Is persuasion mainly driven by model size? Do personalisation and microtargeting matter? Can models be post‑trained to become more persuasive? Which rhetorical strategies are most effective?

Conversational AI systems can now generate detailed, well‑structured arguments instantly and hold interactive discussions that feel tailored and engaging. While this creates opportunities for useful applications, it also raises the possibility that AI could influence what people think and do.

Although there is currently little evidence that such systems are being used to maliciously persuade people at scale, that may change as the technology advances. Understanding the mechanisms that make AI persuasive allows us to identify where genuine risks lie, rather than relying on assumptions or speculation. This evidence is essential for designing safeguards and standards that keep people safe.

Across three experiments, participants engaged in back‑and‑forth conversations with one of 19 open‑ and closed‑source language models. In controlled conditions, models were instructed to persuade the participant to agree with one of 707 issue stances, using one of eight different rhetorical strategies. These strategies included information-focused argumentation, storytelling, and moral reframing.

Participants rated their agreement with an issue both before and after the conversation. We measured persuasion as the difference in average post‑conversation opinion relative to a control group that had no persuasive conversation.