Net AI Value

ROI on AI is not a dashboard metric. It is a financial statement line.

What it is

Net AI Value (NAV) is Blu Wingu’s financial framework for measuring the true return on an AI investment at EBITDA level. This is a Blu Wingu proprietary framework — the operating principles below are documented from production practice; the formalisation is in active development.

The framework is built on a recognition the Blu Wingu team documented in the founding manifesto: when AI collapses the cost of discovery, headcount-times-day-rate arithmetic stops describing enterprise value. What CFOs commissioning AI investment programmes need to quantify is leverage, intellectual property defensibility, and client trust. These are the three instruments the NAV framework measures.

The Agent Leverage Index (ALI) is the output side of the leverage equation: twelve-month revenue divided by average human FTE. A human directing a swarm of AI agents consistently outproduces a traditional team of equivalent headcount. ALI quantifies that outperformance in revenue terms and translates it into a valuation-multiple adjustment, with industry-median benchmarks documented in the manifesto.

The Proprietary IP Score (PIPS) scores the AI system’s defensible intellectual property — frameworks, prompt libraries, fine-tuned models, data assets — for uniqueness and defensibility. PIPS converts a qualitative capability narrative into a quantitative uplift on enterprise value.

The Trust Equity Gauge (TEG) is the third instrument, and the one most commonly absent from AI investment cases. TEG quantifies relationship stickiness and client-concentration risk. The manifesto defines it as the product of average client relationship length, Net Promoter Score, and a logo concentration factor. TEG above a documented threshold yields a positive valuation adjustment; below that threshold it incurs a discount. Leverage and IP defensibility mean little if the client base is concentrated in one logo or tenure is measured in months.

Taken together, ALI, PIPS, and TEG translate the intangibles that dominate AI consultancy value into spreadsheet-friendly adjustments that correct for the limitations of headcount-based valuation.

Blu Wingu extensions in active development. Two cost layers are under development as extensions to the original NAV framework — not part of its core three instruments: a debt-and-displacement cost layer (rework cost of AI decisions that received inadequate verification); and a gate-crossing cost layer (governance overhead on the same ledger as the benefits). Both are in development, not yet part of the published NAV framework.

When you reach for it

A CFO or investment committee is receiving a benefits case that quantifies velocity gains and headcount reduction while leaving governance cost and relationship risk off the ledger. The NAV framework produces an honest investment case — one that survives diligence, not one that looks strong until scrutinised.

It is also the framework by which Blu Wingu prices outcome-based engagements: fees are staked on net AI value delivered, not on hours expended.

The framework connects to our Karpathy-6 verification discipline: adversarial verification validates AI-generated outputs before they enter the evidence base used to report ALI, PIPS, and TEG.

What you ship

• A Net AI Value baseline: pre-engagement measurement across ALI, PIPS, and TEG — the honest starting point from which improvement is measured.
• An NAV target and milestone schedule: financial commitments built into the engagement, with quarterly checkpoints at which progress is verified.
• A PIPS audit and IP register: the structured assessment of defensible intellectual property, formatted for a CFO data room or investor due diligence pack.

This is Stream D work — AI Financial Governance and Outcome-Based Pricing. We rip up Statements of Work. We work on outcomes. If you need an AI investment case that holds under CFO and board scrutiny, book a five-day Insight Engine engagement to establish the NAV baseline.