Augmented by Design
Organisational & Operating Models (OOM) is a strategic design service that helps organisations reconceive how they are structured, governed, and operated for a world in which AI agents, automated workflows, and networked decision-making are foundational rather than supplementary. The central insight driving this service is one that most conventional organisational design approaches have yet to fully absorb: the functional hierarchy, built for an era of human-only execution, linear information flow, and stable role boundaries, is structurally misaligned with the augmented enterprise. When AI systems participate in workflows as active contributors rather than passive tools, when decisions are made across human-machine networks rather than through management chains, and when the nature of expertise itself is shifting, the boxes-and-lines org chart becomes not merely outdated but actively obstructive. This service redesigns organisations from the operating model outward, building structures that are cognitively coherent, accountability-clear, and genuinely fit for the workforce of the near future.
What It Includes
Organisational Design Review A structured diagnostic of the current organisational architecture assessed against the demands of AI-augmented operations. Drawing on the Galbraith Star Model, which integrates strategy, structure, processes, rewards, and people into a coherent design system, and informed by our emerging agentic organisation research, this review identifies where classical hierarchies are creating friction, where decision authority is mislocated, where information is siloed against the logic of networked AI workflows, and where accountability has become ambiguous as automation has absorbed functions previously owned by identifiable humans. The output is an honest structural diagnosis, not a reorganisation proposal driven by headcount reduction logic.
Operating Model Redesign End-to-end redesign of how work flows, decisions are made, and value is created across the organisation. This moves beyond departmental mapping to what McKinsey’s agentic organisation research describes as the shift from organisation charts based on hierarchical delegation to work charts based on the exchange of tasks and outcomes between human and digital contributors. Operating model redesign addresses the full architecture: how teams form around outcomes rather than functions, how AI agents are positioned within workflows with clearly defined autonomy boundaries, how information moves across the enterprise without being trapped in structural silos, and how governance operates continuously rather than periodically in environments where AI systems act in real time.
Role and Decision-Rights Mapping A precise mapping of where decision authority sits across the redesigned organisation, distinguishing between decisions that belong to automated systems, decisions that require human review and approval, and decisions that must remain exclusively human regardless of available AI capability. Drawing on MIT Sloan’s Decision Rights 2.0 framework, which addresses intervention privileges, override authority, and accountability in agentic networks, this service defines the explicit governance scaffolding that prevents authority from becoming tacitly assumed rather than deliberately engineered. New role archetypes are identified and designed, including AI orchestrators who bridge technical and strategic functions, decision stewards who maintain human accountability at critical nodes, and adaptive specialists whose value lies in contextual judgment that AI cannot replicate.
Cognition-Aware Team Design Structural design of teams that explicitly accounts for the cognitive demands of operating alongside AI systems. Drawing on High Reliability Organisation principles and human factors research, this includes the design of team compositions, communication protocols, and escalation structures that maintain genuine situational awareness rather than allowing AI-mediated routinisation to displace active human sense-making. Teams are designed not for efficiency alone but for resilience, the capacity to perform with high reliability precisely when automated systems fail, produce anomalous outputs, or encounter conditions outside their training parameters.
Governance and Accountability Architecture Design of the governance structures required to maintain meaningful human accountability in organisations where AI agents operate continuously across functions. This includes real-time governance mechanisms calibrated to the speed of agentic AI workflows, ethical oversight frameworks aligned with emerging regulatory requirements, and explicit protocols for when and how humans intervene in, override, or suspend automated processes. Accountability is treated not as a compliance requirement but as a structural design problem, one that must be solved in the architecture of the organisation, not managed after the fact.
Transition and Change Architecture A structured approach to moving from the current organisational model to the redesigned one, acknowledging that the most significant barriers to this transition are not technical but identity-driven, cultural, and behavioural. This includes leadership alignment, workforce communication, capability-building for new role types, and the design of feedback mechanisms that allow the operating model to evolve as AI capabilities and organisational needs continue to develop.
Outcomes Expected
For the individual, the redesigned organisation provides role clarity in an environment that has frequently generated confusion about where human contribution ends and machine contribution begins. Individuals understand their decision authority, know the boundaries of automated systems they work alongside, and operate in structures that value and protect their judgment rather than progressively marginalising it. New career architectures emerge that reward cognitive sophistication, adaptive expertise, and human oversight capability, the qualities that compound in value as AI commoditises routine execution.
For the team, the outcome is a structural environment in which collaboration is genuinely enabled rather than nominally encouraged. Cross-functional, outcome-oriented team designs replace the territorial logic of functional hierarchies. Shared mental models, explicit communication protocols, and clearly mapped decision rights reduce the friction that currently characterises human-AI hybrid operations. Teams become more accountable, more adaptive, and more capable of performing with reliability under complexity.
For the organisation, the redesigned structure and operating model represent a durable competitive architecture, one built not around today’s AI capabilities but around the organisational principles that will remain valid as those capabilities continue to advance. The enterprise becomes structurally capable of absorbing new AI developments without repeated reorganisation, because its foundations are built on the logic of adaptive, outcome-oriented, human-accountable design rather than the brittle logic of functional hierarchy. The result is an organisation that is simultaneously more efficient in its use of technology and more genuinely human in its exercise of judgment, an enterprise where structure and cognition are finally aligned.
