The Human–AI Operating Model: When Humans and AI Share the Work, How Must the Organisation Operate?

As artificial intelligence becomes embedded within everyday work, the organisational challenge is moving beyond questions of technology adoption, task automation and workforce skills. Work increasingly moves between people, AI and interconnected systems, distributing intelligence across workflows and changing where judgement, decision authority, execution and accountability reside. This whitepaper examines what happens when humans and AI increasingly participate within the same system of work. Following the work from task allocation through orchestration, distributed intelligence, human judgement and organisational coordination, it develops the concept of the Human–AI Operating Model: the organisational logic through which work, intelligence, judgement, decision authority, execution and accountability are deliberately orchestrated across humans and AI to produce coherent organisational outcomes. The paper argues that an effective Human–AI Operating Model cannot be reduced to technology architecture, workforce design or AI governance considered separately. Reliable performance depends on interconnected organisational conditions involving people, AI boundaries, information and context, authority, performance visibility and adaptation. This shifts the unit of analysis beyond individual or technological capability towards a deeper question: what enables the organisation as a whole to perform reliably when capability no longer resides in the workforce alone? This is Whitepaper 04 in the Capability Excellence™ Whitepaper Series, and provides the transition to the next paper, From Workforce to Organisational Capability.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-12
DOI
https://doi.org/10.5281/zenodo.22718045
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

The Human–AI Operating Model: When Humans and AI Share the Work, How Must the Organisation Operate?

Varghese Harry
Zenodo (CERN European Organization for Nuclear Research)
Ethics and Social Impacts of AI
article

The Human–AI Operating Model: When Humans and AI Share the Work, How Must the Organisation Operate?

Varghese Harry
article en

Abstract

As artificial intelligence becomes embedded within everyday work, the organisational challenge is moving beyond questions of technology adoption, task automation and workforce skills. Work increasingly moves between people, AI and interconnected systems, distributing intelligence across workflows and changing where judgement, decision authority, execution and accountability reside. This whitepaper examines what happens when humans and AI increasingly participate within the same system of work. Following the work from task allocation through orchestration, distributed intelligence, human judgement and organisational coordination, it develops the concept of the Human–AI Operating Model: the organisational logic through which work, intelligence, judgement, decision authority, execution and accountability are deliberately orchestrated across humans and AI to produce coherent organisational outcomes. The paper argues that an effective Human–AI Operating Model cannot be reduced to technology architecture, workforce design or AI governance considered separately. Reliable performance depends on interconnected organisational conditions involving people, AI boundaries, information and context, authority, performance visibility and adaptation. This shifts the unit of analysis beyond individual or technological capability towards a deeper question: what enables the organisation as a whole to perform reliably when capability no longer resides in the workforce alone? This is Whitepaper 04 in the Capability Excellence™ Whitepaper Series, and provides the transition to the next paper, From Workforce to Organisational Capability.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Ethics and Social Impacts of AI
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