What is Autonomy Economics?

Autonomy Economics is a reference discipline that studies how value capture, commercial logic, and defensibility change when autonomous capability reduces the dependence of an activity on continuous human direction. It analyses three axes of exposure, human-bounded progression, human-bounded interaction, and capability scarcity dependence, and sets out how firms should redesign pricing and business models when the conditions that made a commercial unit scarce begin to weaken.

How does Autonomy Economics differ from autonomous consumption or autonomous expenditure?

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 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.

Who founded Autonomy Economics?

Autonomy Economics was founded by Elemi Atigolo, Managing Partner at Consult Venture Partners. The central concept, the Agentic Profit Paradox, was introduced in FT The Banker in February 2026, and the discipline was formalised in the foundation paper The Agentic Profit Paradox and the Reorganisation of Value Capture, published in April 2026.

What is the Agentic Profit Paradox?

The Agentic Profit Paradox describes a structural tension in which a firm becomes more capable while the commercial basis of its business becomes less secure. It arises when autonomous capability weakens the conditions that made a commercial unit scarce and defensible, while value capture remains anchored to those earlier conditions.

What are the Three Laws of Autonomy Economics?

The Three Laws describe how value migrates as autonomous capability expands. First, value moves from production to orchestration. Second, value moves from access to outcomes. Third, value concentrates where scarce judgement governs autonomous throughput.

Which sectors are most exposed to the Agentic Profit Paradox?

Exposure is highest where revenue is tied to human-bounded progression or to controlled access rather than to outcomes. The discipline maps sectoral exposure across consulting, SaaS, legal services, wealth management, audit, compliance, consumer applications, and marketplaces.

Futurum survey finds buyers still prefer per-seat pricing for separately billed generative AI

Futurum · 17 August 2026

What happened

Among buyers surveyed by Futurum, per-seat pricing was selected by 12.6% for core software. Among buyers whose vendors charge separately for generative AI functionality, per-seat pricing ranked first at 42.3%, ahead of consumption at 36.6% and outcomes at 21.1%.

This is the observable fact the cited source supports, stated without interpretation.

What Autonomy Economics predicted

Tests whether buyers move consistently away from access-based pricing as autonomous capability expands, or whether uncertainty can preserve seat pricing in some categories.

Value moves from access to outcomes

Why this evidence matters

This is a meaningful boundary condition for Law 2. Buyers can reject seat pricing for established core software while preferring the predictability of a seat-based line item for a newer AI cost category. It suggests that budget certainty and cost volatility can preserve access-based pricing even as autonomous capability expands.

The same buyers express different commercial preferences for core software and AI. That makes the observation more useful than a simple vendor pricing example because it shows that the commercial unit can depend on the risk characteristics of the category, not only on the underlying technical capability.

This is the framework's reading of the fact above. The source does not endorse it and is not cited as doing so.

Strongest alternative interpretation

This is a stated-preference survey rather than transaction data. Non-seat models still account for 57.7% of AI-specific preferences combined, and the result may reflect temporary uncertainty over AI cost rather than durable access-based economics.

Recorded for every observation assessed at strength 4 or 5. A record that cannot state the strongest competing reading of its own evidence is not published.

What would change this assessment

What would strengthen this evidence

Transaction-level evidence showing that per-seat AI pricing remains preferred and commercially durable as usage becomes predictable and agent volumes scale.

What would weaken or falsify this interpretation

A sustained move towards consumption, action or outcome pricing once buyers gain better cost visibility, or evidence that per-seat preference does not translate into actual contracts.

Source

Futurum

The Pricing Split: Why Core Software and AI Can't Share One Commercial Model

View original source ↗

Institutional researchPublished 17 August 2026Last verified 30 September 2026

Futurum reports buyer preferences of 12.6% per-seat for core software and 42.3% per-seat, 36.6% consumption and 21.1% outcomes for separately billed generative AI functionality.

Where several outlets report the same development, they are recorded as additional sources on this one observation rather than as separate evidence.