AI agents—autonomous systems that perceive an environment, make decisions, and take actions toward a goal—are becoming a material force in how search and discovery work. Unlike chatbots that respond to single prompts, agents operate independently, chain multiple steps together, and interact with APIs and websites to accomplish tasks without constant human direction. For SEO, this matters because agents are starting to bypass traditional search interfaces entirely, querying the web programmatically, consuming content directly, and making decisions about which sources to trust. They're also being deployed *by* businesses to handle customer queries, product research, and content generation—all of which changes how visibility and authority actually convert to traffic and revenue.
The field is fractured between hype and reality. LLM-powered agents remain brittle; they hallucinate, struggle with reasoning, and often fail at multi-step tasks. But incremental improvements, better tooling, and real-world applications in customer service, research automation, and content discovery are validating the model. The tension now is whether agents represent a new distribution channel (like mobile once did) or a fundamental shift in how people discover information. Most working SEOs should assume both are true: some traffic will flow through agent interfaces you don't control, but agent behavior will also reshape how content is discovered, ranked, and surfaced within search itself.
Focus on understanding how agents retrieve, evaluate, and cite sources. That's where SEO leverage actually lives.