Agentic Organisations: Designing for AI

What is Agentic Experience Design?

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.

How does AXD differ from traditional UX?

Why is trust architecture important for agentic AI?

Key concepts in Agentic Organisations: Designing for the AI-Orchestrated Enterprise

How do agentic organisations: designing for the ai-orchestrated enterprise relate to agentic commerce?

  1. Agency requires intentional delegation — every agentic system begins with a designed act of delegation
  2. Trust is the primary material — AXD works in trust rather than attention
  3. Absence is the primary use state — the most consequential experiences happen when no one is watching
  4. Relationships have temporality — agentic experiences accumulate history over time
  5. Outcomes replace outputs — AXD designers specify results, not interfaces
DimensionTraditional UXAgentic Experience Design (AXD)
Primary materialAttention and affordanceTrust and delegation
User statePresent, navigatingAbsent, delegating
Design outputScreens and interfacesOutcomes and constraints
Temporal modelSession-basedRelationship-based
Success metricTask completionTrust calibration

Frequently Asked Questions

What is an agentic organisation?

An agentic organisation is an enterprise structurally redesigned around the assumption that autonomous AI agents will perform the majority of execution, coordination, and routine decision-making. Unlike organisations that simply deploy AI tools, agentic organisations have rebuilt their operating models, reporting structures, and coordination mechanisms to account for non-human actors that plan, execute, and adapt autonomously. The concept is a core concern of Agentic Experience Design (AXD), the

What is the coordination tax in agentic AI?

The coordination tax is the overhead required to align human effort across functions, geographies, and hierarchies - meetings, status reports, approval chains, project management tools, and middle management layers. Agentic AI dissolves this tax because autonomous agents can coordinate through structured protocols and machine-readable interfaces without the synchronisation mechanisms that human collaboration requires. The dissolution of the coordination tax is one of the primary structural force

What is the execution layer shift?

The execution layer shift is the structural phenomenon in which the primary performers of organisational work transition from human employees to autonomous AI agents. This is not traditional automation of repetitive tasks - it is the delegation of complex, multi-step, judgment-requiring workflows to agents that can plan, execute, adapt, and learn. Bain's March 2026 analysis found that legacy tech platforms weren't built to support collaborative agents, explaining why 80% of gen AI use cases met

What is the verification flywheel?

The verification flywheel is a self-reinforcing cycle identified by the AXD Institute in which successful agent performance earns expanded autonomy, which generates more performance data, which enables more precise verification, which earns further autonomy. It operates through four stages: constrained delegation, monitored autonomy, calibrated trust, and earned authority. The World Economic Forum's March 2026 analysis aligns with this framework, noting that organisations succeed in the agentic

How does AXD help design agentic organisations?

Agentic Experience Design (AXD) provides the conceptual and practical framework for designing organisations in which human-agent coordination is intentional, observable, and recoverable. AXD addresses six dimensions of agentic organisational design: Delegation Architecture, Trust Calibration, Observability Design, Interrupt Architecture, Failure Recovery, and Role Redesign. The AXD Institute's Agentic Readiness Assessment evaluates organisational preparedness across these dimensions, ensuring en

Key Takeaways

The concept emerges from a convergence of forces documented across the consulting and academic landscape in early 2026. McKinsey's Agentic AI dissolves this tax. When autonomous agents can execute tasks, share context through structured protocols, and coordinate through machine-readable interfaces, the coordination overhead that justified entire management layers becomes unnecessary. A VentureBeat analysis in March 2026 reported that 85% of enterprises want to become "agentic" within three years - yet 76% admit their current operations cannot support it. The gap is not technological. It is structural. Organisations built around human coordination cannot simply add agents. They must redesign the coordination layer itself. The dissolution of the coordination tax has profound implications for organisational structure. Middle management - the layer that historically translated strategy into execution, monitored progress, and escalated exceptions - faces an existential challenge. When agents handle the translation, monitoring, and routine escalation, the middle layer must either evolve into something new (verification, trust governance, The AXD Institute's answer is that the transition requires Why Agentic AI Demands a New Architecture McKinsey's enterprise architecture analysis introduces the concept of the From an AXD perspective, the execution layer shift creates a new design challenge: Explainability and Observability Design Standard As agents take on more execution, organisations develop what the AXD Institute calls the The verification flywheel operates through four stages. The World Economic Forum's March 2026 analysis aligns with this framework: "Organizations that succeed in the agentic AI era will earn autonomy through visibility, policy boundaries and the ability to audit and override decisions." The verification flywheel is the mechanism through which this earning occurs - not through a single decision to trust, but through an accumulating body of evidence th

References and Citations

Gartner: Machine Customers Will Be a Multibillion-Dollar Opportunity Harvard Business Review: The Age of AI Agents McKinsey: The State of AI in 2024 About the AXD Institute Contact Us Email the AXD Institute Tony Wood on LinkedIn Tony Wood on X (Twitter)