From Autonomy Economics, the reference entry for the discipline
Autonomy Economics is a reference discipline that studies how value capture, commercial logic, and defensibility change as autonomous capability makes it possible to carry activity forward, mediate interaction, and access capability with less dependence on the conditions that previously structured how value was created and captured.[4] It defines the paradoxes, exposure vectors, and redesign imperatives that emerge as autonomous capability becomes economically meaningful across software, services, financial institutions, and interface-based models.
The discipline was founded by Elemi Atigolo, Managing Partner at Consult Venture Partners, who introduced its central concept, the Agentic Profit Paradox, in FT The Banker in February 2026.[1] The foundation paper, The Agentic Profit Paradox and the Reorganisation of Value Capture, was published in April 2026 and formalises the field's analytical framework. The framework has since been applied in institutional engagements across financial services and has been cited in sectoral analysis of AI's economic impact in banking.[2]
Autonomy Economics studies how value capture, commercial logic, and defensibility change wherever autonomous capability weakens the structural conditions on which a commercial unit was built. The field examines three distinct axes of exposure: human-bounded progression (HBP), where value depends on activity being carried forward through human effort or sequencing; human-bounded interaction (HBI), where value depends on interaction, interface, or attention through which value is captured; and capability scarcity dependence (CSD), where value depends on the limited availability of, or controlled access to, underlying capability.
The discipline applies wherever autonomous systems change how activity is carried forward, how interaction takes place, or how access to capability is structured. It focuses on revenue durability, margin structures, and the redistribution of value as autonomous capability alters the conditions that previously made commercial units scarce and defensible. The central claim is that economic advantage from autonomous capability depends on whether the structure of value capture remains aligned with the conditions on which the commercial unit depends.
Existing strategy and technology frameworks do not fully explain what happens as autonomous capability increases while the commercial structures built around earlier conditions become less stable. Industry frameworks such as the Business Model Canvas (Osterwalder and Pigneur, 2010) account for adoption, tooling change, productivity gains, and software substitution. They are less useful in explaining why margin pressure can appear before broad deployment, why demand can remain intact while the basis on which value is justified weakens, or why value accumulates in orchestration, verification, governance, and absorption. Autonomy Economics addresses that gap.
A growing body of work examines how agentic AI affects execution, workflow, and organisational design. This literature remains concentrated at the operational layer. It explains how systems perform tasks, support decisions, and reorganise activity, but gives less attention to revenue models, commercial logic, and durability once the conditions on which those models depend begin to weaken. Prior work, including Brynjolfsson and McAfee (2014) and Brynjolfsson et al. (2023), emphasises productivity and workflow redesign, but does not provide a general account of value capture under these conditions.
Autonomy Economics begins from a general observation. Once autonomous capability makes it possible to carry activity forward, mediate interaction, and access capability with less dependence on the conditions that previously structured how value was created and captured, the relationship between effort, structure, value, and profit changes. Some revenue lines weaken quickly. Others remain durable. Some firms convert new capability into advantage, while others do not. Adoption alone does not explain that difference. The issue lies in the structure of value capture.
Commercial units are defensible only under specific structural conditions. As autonomous capability weakens those conditions, units weaken when value capture remains anchored to them. Firms that redesign to align value capture with the new conditions can restore durability and capture new sources of value.
This pattern is already visible across sectors that appear very different on the surface. Software firms, consultants, financial institutions, legal businesses, accountants, and private capital firms operate under different conditions, but they exhibit different forms of exposure depending on how value is structured within each commercial model. In some cases, value depends on activity being carried forward through human-bounded progression. In others, it depends on human-bounded interaction through which value is captured. Some models also depend on the scarcity of underlying capability as a condition of value capture and defensibility, either independently or alongside other conditions tied to progression or interaction. As autonomous capability weakens these conditions, the business models built on them come under pressure. Multiple forms of exposure can exist within the same business.
A new field is needed because the existing language does not fully explain this commercial movement. The issue extends beyond automation, software change, or cost reduction. It concerns the organisation of value once autonomous capability changes the conditions that anchored the commercial model. Business models built around those conditions then have to adjust. Autonomy Economics examines that reorganisation.
Early responses to structural technological change often attempt to preserve existing models instead of redesigning them. A historical example is the 1899 “Horsey Horseless” automobile proposal, which suggested adding a wooden horse head to early motor vehicles. Although never produced, it illustrates an effort to make a new system resemble the old while leaving the underlying change unresolved. Many current responses to autonomous capability do the same, layering new systems onto existing delivery structures without fully reconfiguring how activity is carried forward, justified, or organised.
Autonomy Economics is not confined to models in which value depends on activity being carried forward through human-bounded progression. The same structural logic applies to models in which value depends on human-bounded interaction, attention, discovery, interface position, or the scarcity of underlying capability. This paper develops progression-based models most fully, but Autonomy Economics extends beyond them.
Autonomy Economics begins from a different question. It examines how value capture, commercial logic, and defensibility change wherever autonomous capability weakens the structural conditions on which a commercial unit was built, whether those conditions arise from human-bounded progression, human-bounded interaction, or the scarcity of the underlying capability.
Much of the automation literature focuses on which tasks are replaced, augmented, or reassigned as capability improves. The concern here is broader. It is about how weakening human-bounded progression, human-bounded interaction, and the scarcity of underlying capability, and more generally the conditions on which commercial units depend, changes the structure through which value is defined, justified, defended, and retained. The issue is not only who performs activity, but how activity is carried forward, how interaction takes place, and how capability is accessed. These conditions shape the commercial basis on which value is captured and defended.
The task-based literature addresses a distinct set of questions. Acemoglu and Restrepo model production as a continuum of tasks subject to automation and new task creation, examining the consequences for labour demand and task composition (Acemoglu and Restrepo, 2019, 2020). Autor examines how automation substitutes for labour in routine, codifiable tasks while complementing human advantage in problem-solving and adaptability, with consequences for the composition and distribution of employment (Autor, 2015). The focus here is different. It is directed not at task allocation or employment outcomes, but at how changes in the conditions under which activity is carried forward, interaction takes place, and capability is accessed affect where value resides and how it can be captured.
Productivity frameworks explain how firms generate more output with the same or fewer inputs. That remains useful, but it does not explain cases in which greater capability and throughput fail to preserve the commercial logic and profit structure that previously supported the business. A firm can become more efficient while its economic position becomes less secure.
Platform theory explains how value builds through coordination, interfaces, and network effects. The issue here is different. It concerns what happens when the conditions under which activity is carried forward, interaction takes place, and capability is accessed change in ways that weaken the basis on which commercial units are structured and defended. The emphasis is not only on the site of interaction, but on how activity is carried forward, how interaction is captured, and how value remains anchored to those structures.
The distinction between Autonomy Economics and these existing frameworks is not one of emphasis but of mechanism. Automation theory, platform theory, and productivity frameworks each assume that human involvement in progression or interaction remains the baseline unit around which commercial structures are organised. They ask what happens when that involvement becomes more or less efficient, more or less mediated, or more or less substituted. Autonomy Economics begins from a different premise. Autonomous capability weakens the conditions that made established commercial units scarce and defensible, including those tied to how activity is carried forward, how interaction takes place, and how access to capability is structured. A billable hour, a per-seat licence, a commission, and a per-claim fee held because activity or interaction depended on conditions that made those units viable and defensible. When those conditions weaken, the unit loses its structural basis even when demand remains intact and capability improves. No existing framework takes that condition as its central object of study. This is the central mechanism examined in this paper.
Teece’s dynamic capabilities framework addresses how firms sense, seize, and reconfigure resources to sustain competitive advantage under technological change (Teece, Pisano and Shuen, 1997; Teece, 2007). It is concerned with the organisational capacity to adapt. Autonomy Economics begins where that framework leaves off. The question here is whether the commercial structure a firm is adapting toward represents where value now accumulates. A firm can possess strong dynamic capabilities and still redesign around the wrong unit of value capture if it does not account for how autonomous capability has changed the conditions that make existing units scarce and defensible.
Structure-based traditions in industrial organisation explain commercial outcomes through market-level conditions such as concentration, entry barriers, and buyer power (Bain, 1956, 1959). Autonomy Economics examines a different level of economic organisation. It focuses on the conditions on which a commercial unit was built, whether those arise from human-bounded progression, human-bounded interaction, or the scarcity of underlying capability. When autonomous capability weakens those conditions, the commercial basis of the unit changes even if market structure, competitive dynamics, and customer demand remain unchanged. Structure-based traditions in industrial organisation do not capture that mechanism.
Christensen’s disruption theory explains how entrants with simpler, cheaper offerings displace incumbents by serving overlooked segments before moving upmarket (Christensen, 1997; Christensen and Raynor, 2003). The mechanism in Autonomy Economics is different. The pressure described here does not require a new entrant. It arises when autonomous capability weakens the conditions that make established commercial units scarce and defensible within the existing market, whether those conditions are tied to progression, interaction, or the scarcity of underlying capability. A firm can face the Agentic Profit Paradox while maintaining its market position, its client relationships, and its operational performance. Disruption theory does not account for that condition.
The business model innovation literature, including Zott, Amit and Massa (2011) and Demil and Lecocq (2010), examines how firms create and capture value through the design of activity systems. This work is concerned with how business models are constructed and how they generate value. Autonomy Economics adds a structural condition that this literature does not address directly. When autonomous capability weakens the conditions on which commercial units depend, the link between those conditions and the units of value capture built around them breaks down, creating pressure on the model regardless of how well it was designed. The issue is whether the model remains aligned with changing conditions. Hagiu and Wright (2015) describe how value moves across platform layers as network effects develop. In Autonomy Economics, value migration is driven by the weakening of the conditions that previously sustained established units of value capture, not by network dynamics alone.
Slywotzky’s value migration framework describes how economic value moves between firms and business designs as customer priorities change and incumbents fail to adapt (Slywotzky, 1995). Both frameworks observe that value moves when commercial models fall out of alignment with changed conditions, and both hold that firms need to redesign before the old model becomes visibly obsolete. The mechanism in Autonomy Economics is different. In Slywotzky’s account, migration is driven by changing customer priorities and competitive business design obsolescence, where a better-designed firm captures value from a weaker one. The pressure described here does not require a competitor with a superior business design or a change in customer priorities. It arises when autonomous capability weakens the conditions that make a commercial unit scarce and defensible, whether that unit is a billable hour, a per-seat licence, or a commission, regardless of competitive dynamics. A firm can face the Agentic Profit Paradox while retaining its customers, its market position, and its brand. The unit of analysis is the misalignment between commercial units and the conditions that sustain them.
From sections 1, 1A and 1B of the foundation paper.
They are unrelated concepts that share a word. Autonomous consumption and autonomous expenditure are long-established terms in macroeconomics describing spending that does not vary with income. Autonomy Economics, by contrast, is a discipline concerned with autonomous capability (machine systems that carry work forward without continuous human direction) and with what that does to pricing, margin, and commercial defensibility. The two fields share no analytical framework.
Autonomy Economics was founded by Elemi Atigolo, Managing Partner at Consult Venture Partners. He introduced the field’s central concept, the Agentic Profit Paradox, in FT The Banker in February 2026,[1] and formalised the discipline in the foundation paper The Agentic Profit Paradox and the Reorganisation of Value Capture, published in April 2026.