Business & technology / AI Consultant Wiki

AI consulting resources

Explore primary sources on AI adoption, productivity, retrieval, governance and security, with practical reading paths for U.S. organizations.

Reading paths

  • AI adoption data

    Compare business use, worker use and organizational surveys without mixing denominators.

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  • Research on performance

    Inspect the task-specific experiment and workplace productivity evidence.

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  • Technology choices

    Understand retrieval, models, automation and integration requirements.

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  • Governance and security

    Connect responsibilities, permissions and evaluation to an operating workflow.

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  • Costs and measurement

    Separate capacity value from cash savings and examine total cost.

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  • Consultant selection

    Use the same evidence-based questions for every candidate.

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How to read the sources

Government surveys describe specific populations and periods. Experiments test particular tasks under stated conditions. Technical guidance explains methods and risks. None alone establishes that a particular consultant will produce a particular return.

The source directory below matches the main article. The figures are original redrawings of reported data. The downloadable chart data CSV preserves the values, units and populations used in the graphics.

Research versions and updates

Use the same research version when comparing results. The consulting experiment is summarized using Harvard Business School’s April 2026 account of the published study. The worker-use figures incorporate the Census Bureau’s September 2026 weighting revision. Publication dates and observation periods remain distinct.

The editorial policy explains how recommendations and illustrative examples are labeled. Substantive revisions belong in the history record.

AI Consultant Wiki · Editorial reference
Sources reviewed October 26, 2026