The threat is framed as both a technical and policy challenge, calling for higher costs, greater risk, and improved visibility of manipulation to safeguard democratic processes.

Reducing monetization incentives for inauthentic engagement and implementing stronger standards to label AI content are recommended, as regulatory trends may be moving away from safeguards while the threat grows.

Advancements in generative AI and open-source models, coupled with lax moderation and monetization incentives, create fertile ground for malicious influence operations across multiple platforms.

AI-led botnets and swarms can sway public belief and threaten democratic processes by generating coordinated, authentic-looking interactions across social media platforms, creating a synthetic consensus that makes extreme narratives appear mainstream.

Scholars warn of real-world political risks, noting shifts in U.S. policy and regulation that could weaken defenses against influence operations, and urge policymakers and technologists to raise the costs and visibility of manipulation.

Traditional bot-detection tools and content-detection models struggle to distinguish AI-driven accounts from human users, a growth area as AI models become more capable and moderation lax.

Mitigation strategies include granting researchers access to platform data, developing methods to detect coordinated behavior, watermarking AI-generated content, labeling AI-generated posts, and restricting monetization of inauthentic engagement.

Further emphasis on detection methods involves analyzing timing, network movement, and narrative trajectories to identify coordinated behavior.

Early observations identified a botnet named fox8 active in mid-2023, comprising over a thousand accounts used to amplify crypto scams and manipulate engagement, exposing moderation and detection gaps.

Generative AI models, including open-source variants, enable scalable, autonomous coordination among bots, allowing tailored content that can defeat standard detection methods.

Regulatory and policy developments are diverging, with some administrations reducing funding for disinformation research and weakening guardrails, potentially increasing vulnerability to manipulation.

The risk is rising due to relaxed moderation, financial incentives for engagement, and reduced access to platform data for researchers, which hinder monitoring and detection of coordinated manipulation.