For years, businesses have focused on protecting their sites from malicious bots. This same architecture now blocks beneficial AI agents acting on behalf of consumers. Companies must rethink their technical infrastructure to differentiate and welcome these new 'good bots' for agentic commerce.

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The rise of AI browsers introduces 'agents' that automate tasks like research and form submissions. To capture leads from these agents, websites must feature simple, easily parsable forms and navigation, creating a new dimension of user experience focused on machine readability.

Websites now have a dual purpose. A significant portion of your content must be created specifically for AI agents—niche, granular, and structured for LLM consumption to improve AEO. The human-facing part must then evolve to offer deeper, more interactive experiences, as visitors will arrive with their basic research already completed by AI.

Anticipating a shift to "agentic commerce," SharkNinja is actively re-optimizing its e-commerce site for Large Language Models. The company believes what drives human conversion today may not rank highest in AI-driven search and expects commerce via AI platforms to be meaningful by Christmas 2025.

The internet was designed for human interaction, actively discouraging bots. The next evolution will reverse this, with AI agents becoming the primary users. This requires re-architecting everything from user interfaces to business models, with crypto likely serving as the native payment rail for these autonomous agents.

A key bottleneck preventing AI agents from performing meaningful tasks is the lack of secure access to user credentials. Companies like 1Password are building a foundational "trust layer" that allows users to authorize agents on-demand while maintaining end-to-end encryption. This secure credentialing infrastructure is a critical unlock for the entire agentic AI economy.

As users delegate purchasing and research to AI agents, brands will lose control over the buyer's journey. Websites must be optimized for agent-to-agent communication, not just human interaction, as AI assistants will find, compare, and even purchase products autonomously.

The rise of AI browser agents acting on a user's behalf creates a conflict with platform terms of service that require a "human" to perform actions. Platforms like LinkedIn will lose this battle and be forced to treat a user's agent as an extension of the user, shifting from outright bans to reasonable usage limits.

Organizations must urgently develop policies for AI agents, which take action on a user's behalf. This is not a future problem. Agents are already being integrated into common business tools like ChatGPT, Microsoft Copilot, and Salesforce, creating new risks that existing generative AI policies do not cover.

The next phase of AI will involve autonomous agents communicating and transacting with each other online. This requires a strategic shift in marketing, sales, and e-commerce away from purely human-centric interaction models toward agent-to-agent commerce.

The rise of AI agents means website traffic will increasingly be non-human. B2B marketers must rethink their playbooks to optimize for how AI models interpret and surface their content, a practice emerging as "AI Engine Optimization" (AEO), as agents become the primary researchers.