02 · Primer
In one paragraph
Agentic commerce is when AI agents actively help plan, evaluate, and execute buying decisions rather than only recommending products. Agents move from recommendation to execution, optimise for value, speed, and fit, and need policy controls before scaling autonomy.
On this page4 sections
Agentic commerce uses AI shopping agents to interpret buyer intent, compare options, and execute actions across the funnel with clear rules and safeguards.
AI shopping agent flow
Three stages, repeated on every interaction. Each stage takes the previous stage's artifact as its input.
- Intent capture. Agent reads shopper goals, budget, preferences, and constraints.
- Market scan. Agent compares products, delivery windows, and policy fit across options.
- Decision and action. Agent proposes or executes purchase steps with transparent rationale.
Current examples in the market
Four live patterns cover most of what's in production today.
- Assisted cart building. Agents assemble full carts from one natural-language request and optimise for value.
- Subscription optimisation. Agents adjust renewal cadence and product mix based on usage and price changes.
- Post-purchase concierge. Agents handle swaps, reorders, and accessory recommendations with policy controls.
- B2B procurement copilot. Agents gather vendor quotes, verify terms, and package approvals for finance teams.
Business impact
| Metric | Value | Detail |
|---|---|---|
| Conversion lift | +12% to +28% | Higher purchase completion when decision fatigue is removed from product selection. |
| Margin protection | Lower discount leakage | Agents can optimise basket-level profitability instead of blanket promotions. |
| Operational efficiency | Fewer manual handoffs | Support and merchandising teams spend less time on repetitive edge-case handling. |
Frequently asked
What is agentic commerce in one sentence?
When AI agents actively help plan, evaluate, and execute buying decisions rather than only recommending products.
Will shopping agents replace ecommerce teams?
No. Teams still own pricing strategy, merchandising, legal policies, and brand decisions. Agents handle execution and personalisation.
What should be controlled first?
Start with strict permission boundaries: what an agent can view, suggest, and execute without explicit human approval.
Where do most pilots fail?
Fragmented catalog, policy, and inventory data. Agent decisions get unreliable fast when the underlying data shape shifts under them.
Further reading