Evidence Monitor / Consulting

Sector

Consulting

Consulting economics rest on human progression through analysis, implementation and reporting. As that progression compresses and clients build internal capability, the defensibility of effort-based delivery units weakens even where demand for judgement persists.

6
observations
6
supportive
0
challenging or unresolved

Primary exposure

Human-Bounded Progression

Economic activity that historically depended on humans carrying work through stages requires less human progression to produce the same economic result.

Register-wide status: Strong

Capability Scarcity Dependence

Businesses whose economics depended on scarce access to expertise, software or technical capability experience declining scarcity.

Register-wide status: Strong


Evidence timeline

  1. 30 April 2026
    Autonomy Economics published
    Everything after this point is an observation made once the predictions were on the record.
  2. 4 MAY
    SupportivePost-publication
  3. 11 MAY
    SupportivePost-publication
  4. 9 JUN
    SupportivePost-publication
  5. 9 JUL
    SupportivePost-publication
  6. 31 AUG
    SupportivePost-publication
  7. 1 SEP
    SupportivePost-publication

What would falsify the prediction for this sector

AI materially reduces delivery labour while consulting pricing, team sizes and margins remain structurally unchanged.


All consulting evidence

Financial Times·

Wall Street banks push Big Law to pass AI productivity into lower fees

The FT reported that Morgan Stanley, Citigroup and Goldman Sachs are pressing major law firms to reflect AI-enabled efficiencies in fees, including through competitive bidding, fixed fees and requests for evidence of AI-driven savings.

HBPLaw 2Law 3Profit ParadoxRevenue Durability

Prediction testedCommercial-unit pressure should appear once buyers can observe that less human progression is required, even if demand for high-value legal judgement remains.

AssessmentSupportive Directly observable

Why it mattersThis is a direct buyer response to productivity change, not a forecast about future legal pricing.

Post-publicationView evidence →
Financial Times·

FT reports consulting clients cutting external work and pressing fees as AI expands internal capability

The FT reported that companies are bringing more technology work in-house, reducing reliance on large consulting teams and demanding lower, fixed or performance-linked fees as AI reduces the human effort required for implementation and analysis.

HBPCSDLaw 2Law 3Profit ParadoxRevenue Durability

Prediction testedConsulting can remain in demand while billable progression becomes less defensible and value moves toward senior judgement, leadership advice and measurable outcomes.

AssessmentSupportive Directly observable

Why it mattersThis is buyer behaviour rather than vendor prediction: clients are connecting AI-enabled productivity directly to lower consultant dependence and pricing pressure.

Post-publicationView evidence →
Deloitte UK·

Deloitte legal survey finds expected automation, insourcing and pricing-model pressure

Deloitte’s survey of 121 senior legal leaders found 61% in AI deployment phases, 61% experimenting with or piloting agentic AI, 78% wanting external-provider AI to reduce costs, and 85% expecting AI to change law-firm pricing.

HBPCSDLaw 2Law 3Revenue Durability

Prediction testedWhen structured legal production requires less human progression, billable-hour durability should come under pressure while judgement and accountability remain more defensible.

AssessmentSupportive Strong

Why it mattersThe evidence connects adoption to expected commercial-model change rather than merely productivity.

Post-publicationView evidence →
Microsoft·

KPMG and Microsoft deploy Agent 365 governance across global AI agents

KPMG and Microsoft announced global deployment of Agent 365 and Copilot, including tooling to manage, monitor and secure AI agents across KPMG and client organisations, alongside Copilot deployment to more than 276,000 professionals.

HBPLaw 1Law 3

Prediction testedAs autonomous throughput expands, value and organisational importance move toward monitoring, control, verification and governed execution.

AssessmentSupportive Strong

Why it mattersGovernance is being operationalised as infrastructure for enterprise-scale agent deployment, not treated solely as a compliance afterthought.

Post-publicationView evidence →
OpenAI·

OpenAI launches Deployment Company with major capital partners

OpenAI launched the OpenAI Deployment Company to embed forward-deployed engineers in organisations, agreed to acquire Tomoro, and described a model for scaling deployment across the economy with capital and consulting partners.

Law 1Capital-Structured Autonomy

Prediction testedValue can move above individual operating companies toward actors that coordinate autonomous deployment, learning and workflow redesign across wider networks.

AssessmentSupportive Directly observable

Why it mattersThe organisation is explicitly designed around repeatable deployment capability rather than simple model access.

Post-publicationView evidence →
Anthropic·

Anthropic and private-equity consortium form enterprise AI services company

Anthropic, Blackstone, Hellman & Friedman and Goldman Sachs announced a new AI services company for mid-sized enterprises.

Law 1Capital-Structured Autonomy

Prediction testedCapital owners can organise deployment, engineering capability, standards and learning across networks of firms rather than each operating company adopting independently.

AssessmentSupportive Directly observable

Why it mattersThe structure closely matches the paper’s predicted ecosystem-level orchestration model.

Post-publicationView evidence →