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The UK Department for Science, Innovation and Technology (DSIT) announced an AI Assurance Platform on 6 November 2024. It is intended as a business-facing one-stop shop for guidance, tools and practical resources that help organisations identify, measure and reduce risks from AI. The evidence available confirms the announcement and planned scope, but not an independently verified date when every part of a complete public-facing service became operational.
What DSIT announced
DSIT described the platform as a way to bring existing AI-assurance tools, services, frameworks and practices together in one place. The announcement also referred to practical support for impact assessments, evaluations and checking data for bias, plus a self-assessment tool aimed particularly at small and medium-sized enterprises.
An AI Essentials Toolkit was included in the government’s 2024 market report as planned content. That report used development language, so businesses should treat the toolkit and other feature-level descriptions as announced or intended unless they verify a live service themselves.
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Peter Kyle, then Secretary of State for Science, Innovation and Technology, said the measures would give businesses “the support and clarity they need to use AI safely and responsibly” and help make the UK “a true hub of AI assurance expertise.”
What “AI assurance” means
DSIT’s introductory guidance, published on 12 February 2024, describes AI assurance as ways to measure, evaluate and communicate the trustworthiness of AI systems. In practice, assurance produces evidence that can support responsible adoption and risk-management decisions; it is not a government safety certificate.
- Measure: define relevant properties such as accuracy, robustness, security, fairness or explainability.
- Evaluate: test the system, its data and its real-world use against those properties.
- Communicate: record results, limitations and residual risks for decision-makers and affected stakeholders.
Can an enterprise use it as a certification?
No. The platform is a navigation and guidance resource, not a product-certification scheme and not a government guarantee that an individual AI system is safe, lawful or suitable. A self-assessment can help an organisation structure its work, but responsibility for governance and deployment remains with the organisation.
Rank #2
How a business can approach assurance
1. Define the system and its use
Document the model or service, data sources, users, decisions it influences, suppliers, jurisdictions and consequences of failure. A generic checklist is weaker than an assessment tied to the actual deployment context.
2. Choose the assurance route
DSIT’s market report separates the supplier landscape into two broad groups:
Rank #3
| Route | Typical role | Best fit |
|---|---|---|
| Consulting, advisory, training and procedural services | Set assurance strategy, controls and operating processes | Organisations building governance capability or preparing documentation |
| Technical assessment tools | Test or analyse an AI system and its data | Teams needing repeatable technical evidence |
| Independent third-party assurance | Review or verify a system outside the delivery team | Firms lacking specialist capacity or needing additional independence |
3. Collect evidence and record limits
Keep test methods, datasets, results, assumptions, incidents and remediation decisions with the system’s governance records. The useful question is not whether a tool produces a reassuring score, but whether its evidence addresses the risks of the specific use case.
4. Reassess when the system changes
New data, model versions, prompts, integrations, users or operating environments can change risk. Set review triggers rather than treating assurance as a one-off exercise.
How large is the UK assurance market?
DSIT’s 6 November 2024 market report estimated 524 UK firms supplying AI-assurance goods and services, with estimated gross value added of £1.01 billion and 12,572 employees. Within that broad count, it identified 84 UK-based specialised AI-assurance companies. These are 2024 estimates, not a current 2026 census, and the two counts use different categories.
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| Date | Development |
|---|---|
| 12 February 2024 | DSIT published its introductory “AI assurance” guidance. |
| 6 November 2024 | DSIT announced the business-facing platform and related practical support; the accompanying market report described platform and toolkit work as being developed. |
| 3 September 2025 | DSIT published a trusted third-party AI-assurance roadmap covering a profession-building consortium, skills and competencies work, and an £11 million AI Assurance Innovation Fund. The roadmap targeted a first funding round for spring 2026. |
| 18 September 2026 | A parliamentary answer said government was implementing the roadmap, including a Centre for AI Measurement led by the National Physical Laboratory to develop technical and scientific foundations and deliver the fund. It did not state whether applications had opened, closed or produced awards. |
What enterprises should check before relying on a resource
- Is the page or tool currently live, and is its version or publication date clear?
- Does it address the organisation’s actual model, data and operating context?
- Does it generate usable evidence, or only general governance advice?
- Who performed the assessment, and how independent are they from the system’s developer or deployer?
- What remains outside scope, and what risks require specialist legal, security or technical review?
The 2025 roadmap explicitly gives independent providers a role in verifying systems and supplying bespoke services where a firm lacks in-house capability. Government sources do not rank providers or endorse a particular commercial tool, so selection should be based on scope, competence, independence and the evidence delivered.
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