Agentic commerce means AI agents help users, consumers and companies, research, compare, and sometimes complete purchases. It affects all verticals, e‑com, B2B, and beyond. Parts of discovery, research, and decision‑making move away from traditional surfaces into agent interfaces and recommendation layers. For SaaS and B2B this often means shortlisting and risk assessment become more agent‑assisted, for example comparisons, proof, policies, and pricing logic. For apps it can affect how users find and choose alternatives. In all cases, being chosen depends more on trust signals and clarity, and less on owning the entire journey in your own channels. Agentic commerce forces organisational change. Going forward you need to optimise for both humans and agents. Some buying journeys will remain fully human, others almost 100 percent agentic, but most will be hybrids where the agent does research, comparisons, and shortlisting and the human makes the final call, or the other way around. That means brand and trust must be owned and built more systematically, because recommendations increasingly depend on signals like proof, reviews, policies, price logic, delivery, and product data, not on owning the entire journey in your own channels. At the same time the line between new and existing customers blurs. A new customer can build preference through repeated agent recommendations long before the first conversion shows up, and an existing customer can return without visiting your surfaces at all. To avoid optimizing the wrong parts of the system, product data and policies, brand and trust work, CRM, and measurement need to connect much more tightly. Otherwise you get local wins, more output, more initiatives, more dashboards, but a weaker whole. The agent makes decisions based on a different logic than the teams measure, and the organisation runs faster in the wrong direction.