Agentic AI: what changes when software acts on its own

TL;DR: March 2026 sealed the transition from "generative" to "agentic" AI. AI is moving from a tool that produces text to a component that acts within a defined mandate. That makes it a question of authority, oversight and liability rather than model choice.

Agentic Commerce: AI Agents Started Paying

Until now, most companies used AI to produce text and code. Agentic use is different: the model no longer only advises, it initiates actions inside a defined mandate — placing an order, updating a record, triggering an approval flow. Pilots are running in finance and supply chain; broad production use is not there yet.

What looks like a simple transaction on the surface depends less on the model than on the layers around it: identity verification, scope limits, value thresholds, a rollback path, and an auditable record of every step. Opening up autonomous transactions before those exist buys no speed — it costs control.

The Energy Wall: The Physical Barrier to Scaling

Scalable AI is no longer only an algorithmic problem; it is an infrastructure and energy problem. Data centre capacity and electricity cost increasingly shape which model a company can justify running — in Europe more than most.

That weakens the assumption that the biggest model is the best one. For most enterprise tasks, smaller task-specific models are cheaper and more predictable; the large models are kept for the cases that genuinely need them.

Corporate Restructuring: AI Augmented Teams

The effect on teams is less about headcount than about the nature of the work: repetitive steps get automated, while the roles that design the system, set its limits and review its output become more important.

We no longer need "prompt engineers"; we need architects who design, debug, and audit agentic workflows.

Security and Trust: The Rise of Deepfake Fraud

The first major cyber attack attempt on autonomous payment systems was thwarted in March. Attackers tried to use a CEO's voice and image to trick an autonomous agent. This proved that "AI Identity Verification" layers are no longer optional but mandatory in modern software architecture.

Conclusion

If you're still using AI as a "chat" interface in this quarter of 2026, your competitor's agents have likely already paid the bills and optimized your logistics network. Preparing your architecture for autonomous agents isn't a choice; it's a matter of survival. The first step? Transforming your static code blocks into agentic workflows capable of autonomous action.