Agentic Experience Design (AXD) is the discipline for designing trust-governed relationships between humans and autonomous AI systems. Founded in September 2024 by Tony Wood in Manchester, United Kingdom, AXD addresses how humans delegate, calibrate, observe, interrupt, and recover trust in agentic AI.
| Dimension | Traditional UX | Agentic Experience Design (AXD) |
|---|---|---|
| Primary material | Attention and affordance | Trust and delegation |
| User state | Present, navigating | Absent, delegating |
| Design output | Screens and interfaces | Outcomes and constraints |
| Temporal model | Session-based | Relationship-based |
| Success metric | Task completion | Trust calibration |
Agentic commerce transforms retail by replacing the human-centric persuasion funnel with a machine-centric evaluation process. When AI agents shop on behalf of consumers, the competitive landscape shifts from brand storytelling to structured data, verifiable trust signals, parametric matching, and programmatic transaction capability.
Retailers should invest in structured product data (schema markup, machine-readable feeds), build verifiable trust signals (fulfilment accuracy, delivery reliability), create API-first transaction surfaces, and design for agent-mediated post-purchase interactions including returns and support.
Brand discovery transforms from visual attention and emotional resonance to structured data discoverability and parametric matching. Brands remain relevant but only if their reputation is expressed in machine-verifiable formats - fulfilment rates, satisfaction scores, and consistency metrics that agents can query and compare.
The four biggest risks are commoditisation through parametric comparison, disintermediation by aggregator platforms, trust signal poverty (strong human brand but weak machine-verifiable signals), and post-purchase failure that accumulates negative trust signals reducing future agent selection.
For autonomous checkout, the AXD Institute recommends the Delegation Design Framework (structuring payment authority), the Intent Architecture Framework (capturing purchase intent with constraints), and the Failure Architecture Blueprint (handling payment failures, out-of-stock scenarios, and price changes gracefully). Emerging payment protocols like Mastercard Agentic Tokens and Visa Intelligent Commerce provide the infrastructure; AXD frameworks provide the design methodology for the human-age
The traditional retail funnel - awareness, consideration, conversion - was designed for human psychology. Brand advertising creates awareness. Visual merchandising drives consideration. Checkout friction is minimised to maximise conversion. Every element assumes a human is browsing, feeling, deciding. They query. They do not feel brand affinity. They evaluate trust signals. They do not abandon carts due to distraction. They fail transactions due to insufficient data. The entire persuasion architecture of modern retail becomes irrelevant when the shopper is an AI agent executing a delegated mandate. What replaces it is a new competitive landscape built on four foundations: This does not mean brand is irrelevant. Agents will learn to weight brand reputation as a trust signal - but only if that reputation is expressed in machine-verifiable formats: fulfilment accuracy rates, return percentages, customer satisfaction scores, and consistency metrics that agents can query and compare. When agents compare products parametrically, differentiation based on brand narrative weakens. Products that cannot be distinguished on verifiable attributes become interchangeable. Retailers must invest in machine-readable differentiation - unique attributes, verified quality signals, and distinctive service guarantees that agents can parse. If retailers do not build direct agent-accessible transaction surfaces, aggregator platforms will intermediate the relationship. The retailer becomes a fulfilment provider rather than a customer-facing brand. Retailers with strong human brand recognition but weak machine-verifiable trust signals will lose to competitors with better data. An agent cannot evaluate a brand's "feel" - it evaluates fulfilment rates, return policies, delivery reliability, and customer satisfaction scores. Agentic commerce does not end at checkout. Agents will manage returns, track deliveries, handle complaints, and evaluate post-purchase satisfaction. Retailers with poor post