As of June 2026, over 57% of global web traffic is generated by bots and AI-based systems, surpassing human traffic.

This changes the way we design: not only for users interacting with AI, but also for systems that must be read and interpreted by AI systems themselves.

In this talk, we will explore the two dimensions of AI design: designing experiences for humans and designing systems that are comprehensible for machines. We will carry out this analysis through a real-world case study (Peculia) and practical patterns inspired by the literature.

We will see how these two levels converge on the same principles: clarity, structure, and ambiguity reduction—key elements not only for AI, but also for designing more accessible and robust experiences.