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AI Governance in Practice

AI governance turns responsible-AI principles into operating controls. These deployments cover model approval, risk assessment, evaluation, monitoring, audit, transparency, regulatory compliance, and human oversight across the AI lifecycle.
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Data as of Nov 10, 2026
Dataset details
Revision
dsr-fc53bf0883afdfe4
Canonical records
3,963

Executive brief

Workflow automation (Multi-agent) is 3.0× more concentrated here than across AI overall.

Show metrics

Cases

99

27 in the last 6 months

Momentum

89Surging
#1 of 3Peer momentum

Innovativeness

4.0Advanced

100% of evidence scored

Cases trend

Cases 1Agent 1
How this executive brief is measured

Concentration compares this view's share of source-linked deployments for a use-case type with that type's share across the full catalog. Momentum is a peer-relative 0-100 score based on recent deployment volume, acceleration, recent evidence share, and evidence depth. Quantified outcome medians appear only when at least 4 reported metrics support them; smaller supported samples are marked early evidence.

Distinctive

What's distinctive here vs the norm?

The use-case types this view over-indexes on versus the whole corpus — what makes this slice different from AI overall.

2 signals

Workflow automation (Multi-agent) is 3.0× more common here than across all cases — the strongest signal of what sets this view apart.

1× = corpus average · points show how many times more common each type is here.

Lift compares each type's share of this view against its share of all 3,887 cases. 57 of the 99 cases here are type-classified.

Implementation

Do teams build, buy, or compose this?

How the documented deployments in this view were built — custom engineering (Build), an off-the-shelf assistant (Buy), or low-code assembly (Compose).

87 classified cases
BuildBuyComposeMixed

87 of 99 cases classified (88%) · Compare all use-case types

Full report

Expand any section for the detail behind the summary above.

Reported challenge examples: A diagnostic found that 70% of business units were using personal or free AI accounts without central governance, exposing confidential client briefings, launch strategies, and audience data (1 case), A fractured technological infrastructure, manual processes, and aging devices hampered communication, productivity, and teamwork (1 case), A small cyber-defence team faced an increasing volume of security data to analyze (1 case), Accelerate workflow efficiency and reduce costs across knowledge work (1 case), and Accelerating cloud adoption and modernization for large, multi-national clients (1 case). Evidence is still limited; expand to inspect the source cases.

Adoption pulse: 27 of the 99 cases in this view were published in the last 6 months. Expand for the adoption curve.

Questions answered here:

  • What makes AI adoption in AI Governance different?

Related Insights

Next steps

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