Observed Signal · May 18, 2026 · Analysis · Source: Nates Substack · Impact: 3/5 · Sentiment: Neutral
Marketing to Humans and AI Agents in 2026
This opinion piece argues that modern marketing must serve two simultaneous audiences: human buyers and autonomous AI agents that read, summarize, compare, and recommend vendors. The author warns many companies still optimize only for human persuasion, leaving them invisible or indefensible to agentic workflows. Citing a March 2026 survey of 1,076 B2B software buyers, the newsletter reports 69% chose a different vendor due to AI chatbot guidance and about one third bought a vendor they had not previously heard of. The author outlines priorities for marketers—legibility for machines, a "truth layer" of verifiable claims and evidence, and audits to detect AI-washing—and announces a forthcoming series and a practical audit kit using Claude Desktop, Claude Code, ChatGPT, and Codex to map claims, risks, and fixes.
Highlights a structural change in marketing: autonomous agents are already influencing vendor selection, so marketers must publish machine-legible claims and verifiable evidence. This affects discoverability, content strategy, and trust across B2B buying processes.
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Key Takeaways & Evidence Grounding
- Author argues marketing now serves two audiences: humans and AI agents.
- March 2026 survey of 1,076 B2B software buyers found 69% changed vendor choice due to AI chatbot guidance; roughly one third purchased a vendor they had not heard of before the assistant surfaced it.
- The newsletter warns against an AI strategy focused solely on content velocity and introduces the concept of a marketing "truth layer" to steward claims and evidence.
- The author plans a series and an "AI-washing audit" using tools including Claude Desktop, Claude Code, ChatGPT, and Codex.
Connected Companies & Entities
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Related Market Signals & Shifts
Recent verified developments and strategic activity across this market segment.
Human CEO: Marketers Must Learn to Market to Bots
Stu Solomon, chief executive of cybersecurity firm Human, tells The Drum at Cannes Lions that AI agents are increasingly acting as internet shoppers, researchers and decision-makers — often before a human reaches a checkout. Human, known for bot mitigation and fraud detection, now advises marketers to optimise for machines as well as people: providing structured product data, pricing, availability and interoperability signals that AI agents use to evaluate brands. Solomon warns that more than half of internet traffic is already machine-based and could grow to over 80% in coming years. He highlights trust and data-governance challenges — differing agent protocols, lack of agent trust marks, and employee data leakage into AI tools — and argues marketing, security and tech teams must collaborate to govern agent-driven commerce without changing the core commercial goals of marketing.
Prepare for AI: The Future of B2B Marketing
MarTech published guidance advising B2B marketers to prepare for the rise of autonomous AI agents that will research, compare and potentially transact on behalf of buyers. The piece argues that visibility to such agents requires shifting content strategies toward machine-readable formats (schema markup, JSON-LD, consistent metadata), treating APIs and technical documentation as top-of-funnel assets, and creating use-case-specific comparative content. It recommends adopting open interoperability standards (for example, the Open Semantic Interchange format) and aligning product information with procurement automation (consistent pricing, SLAs, compliance docs) so vendor data can be ingested by sourcing and evaluation agents. The article frames these changes as strategic steps to remain discoverable in a machine-mediated B2B buying ecosystem.
Brand Promises Must Be Provable in Agentic Commerce
The article argues that as consumers delegate purchasing decisions to AI agents, brands must shift from emotional positioning to verifiable, machine-readable assurances. AI agents will evaluate brands on measurable signals—price transparency, inventory accuracy, fulfillment reliability, reviews, loyalty value, privacy practices and service history—potentially excluding brands before human consumers see them. Loyalty programs, customer profiles, consent and identity resolution must be accessible and computable by agents. Measurement should move upstream to whether agents can find, interpret and transact with a brand, not only human-visible engagement metrics. Cited data: nearly 70% of consumers and 73% of B2B buyers use AI tools to evaluate purchases, and Bain predicts agentic AI will drive roughly 25% of U.S. ecommerce ($300–$500B) by 2030. The piece concludes brands must align operations and data to make trust verifiable for both humans and their agents.
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