AdoptionSignalAdoptionSignal
Surface AI leverage. Protect human judgment.
AdoptionSignal

AI adoption and workforce research prototype

AdoptionSignal

AdoptionSignal was developed to explore where artificial intelligence can create meaningful workforce leverage while preserving the work that depends on human judgment.

The project combines workflow analysis, workforce capability signals, human-judgment mapping, and AI opportunity assessment into a structured diagnostic framework.

Prototype diagnosis view: an AI-fit versus business-impact quadrant, a ranked workflow table, and team sentiment gauges, rendered from fictional sample data.
A team diagnosis as the prototype renders it, using fictional sample data.

What the framework examines.

Five views that turn workforce evidence into a picture leaders can reason about.

AI Opportunity QuadrantWhere AI fit meets business impact.

Each workflow is placed by how well it suits AI against how much the business depends on it, so leverage is located before anything is automated.

Human Judgment MapThe work that should stay human.

The decisions, relationships, and accountable calls that depend on human judgment, mapped so they are protected by design rather than by accident.

Adoption SentimentHow people actually feel about AI.

Enthusiasm, trust, clarity, and confidence, gathered from the people doing the work and reported only as aggregates.

Capability SignalsReadiness across the team.

Self-assessed capability across the dimensions that shape adoption: coverage, blind spots, and where growth would matter most.

Opportunity PortfolioCandidates ranked by evidence.

The workflows where a pilot is most likely to hold up, ordered by the signals above rather than by enthusiasm.

How the diagnostic is built.

Evidence is gathered from the people doing the work, then combined by explicit rules rather than a black box.

  1. Interview

    Structured conversations capture how work actually happens: inputs, decisions, hand-offs, and friction.

  2. Workflows

    Each role is decomposed into workflows with observable characteristics rather than job titles.

  3. Self-assessment

    People rate their own capability and share how they feel about working alongside AI, privately.

  4. Calibration

    Leaders validate the picture against their own knowledge so the evidence is shared, not imposed.

  5. Diagnosis

    The signals combine into one leadership-ready view: the quadrant, the judgment map, sentiment, and capability.

Project status

AdoptionSignal is not currently offered commercially.

The underlying product, methodology, and related intellectual property are being preserved.

See a sample diagnosis →