AI & Emerging
AI agents increasingly browse the web and complete transactions on behalf of users. The audience shifts, discovery surfaces change, and conversion shape changes. The practical implications for marketing in 2026.
By 2026, AI agents — sometimes called "agentic AI" — are increasingly browsing the web and completing transactions on behalf of users. ChatGPT can book travel. Claude can browse and order products. Custom agent frameworks (LangChain, AutoGen, CrewAI) can be configured to do almost anything a human user would do, automated.
This changes marketing in three ways: who you're marketing to, what surfaces matter, and what the conversion looks like.
An AI agent making a purchase on behalf of a user has different needs than the human user. The agent wants: structured data, clear pricing, machine-readable inventory, low-friction APIs, predictable response formats. Your website needs to serve both audiences — the human browsing and the agent acting on their behalf.
The buyer's AI assistant becomes a major discovery surface. "Find me a CRM under $50/seat that integrates with HubSpot" returns AI-curated answers that draw from a smaller set of trusted sources than a Google search. Being in the AI's answer-set matters more than ranking #4 on Google for the equivalent query.
This is the AEO/AIO/GEO (Answer Engine, AI Overview, Generative Engine Optimization) discipline — closely related to traditional SEO but with different optimization targets. Your content needs to be parseable, factually verifiable, and structurally clear for AI consumption.
AI-agent-completed transactions skip most of the conventional funnel. There's no time-on-page. No re-visiting after consideration. The agent decides quickly based on structured comparison. Your competitive advantage shifts from "best landing page experience" to "cleanest API, best data, lowest friction to transact."
Building anti-agent friction (CAPTCHAs, bot-blocking) without thinking about which agents are legitimate buyers. Treating AI-driven traffic as "bot traffic" and excluding it from analytics. Ignoring AI answer engines because they're "still small" — adoption curves are steep and being early in answer-engine optimization compounds.
How agents will handle pricing negotiation. How brands establish trust signals an agent can verify. How agent-mediated commerce affects loyalty and brand. How AI hallucinations in product recommendations get redressed. These are open and being actively debated in 2026.