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Effective implementation and management of AI systems can transform a business and unlock new possibilities, while also ensuring compliance with industry frameworks and shifting regulations.

Embedding AI systems into your business can help you maximise commercial returns and operational efficiencies, but increased scrutiny means it requires support across risk management and assurance.

Without appropriate guardrails, organisations may breach privacy and ethical standards, potentially resulting in reputational damage and fines under breaches of regulations, eg GDPR or the EU AI Act.

Growth through governance

Solution-focused and pragmatic, our priority is driving efficiency and value in your organisation, enabling effective governance of AI systems

Safeguarding your business

Our experienced team will help your business navigate a complex global regulatory landscape

Value-adding insight

Our analysis enables you to maximise the opportunities AI can deliver

Our AI Diagnostic is here to help you succeed

Our AI Diagnostic service brings clarity to organisations by offering:

a clear, independent view of your AI maturity
a prioritised roadmap to scale AI responsibly and sustainably
early preparation for upcoming AI-specific regulatory frameworks
strengthened board and stakeholder confidence in your AI initiatives.

The AI Diagnostic allows us to deliver immediate client value while building lasting strategic relationships around one of the most transformative technologies of our time.

Alex Hunt Head of Data Analytics and Automation, Business Risk Services

At each AI system life cycle stage, the diagnostic evaluates an organisation’s current AI maturity, identifying both strengths and gaps across the following AI foundation areas:

Strategic AI use case alignment

AI must be embedded into the business, not treated as a side project. This means aligning AI use cases with core business priorities, integrating them into daily operations, and tracking their impact.

Data governance acceleration

High-quality, well-governed data ensures models produce accurate, reliable outcomes. Investing in data infrastructure, governance and accessibility is essential to fast track AI adoption and maximise success.

AI risk governance framework

Governance provides the framework for responsible AI. With growing scrutiny around ethics, bias and compliance, organisations must establish clear policies for accountability and risk management. Strong governance reduces risk and builds stakeholder trust.

AI training

Talent is equally critical. AI success requires more than just technical skills. It demands cross-functional teams that combines data science expertise with business insight to turn strategy into measurable results.

By strengthening these foundational elements, you can position your organisation to scale AI with confidence – letting you move faster, adapt more easily and realise the full value of intelligent technologies.

Get in touch

Alex Hunt

Head of Data Analytics and Automation, Business Risk Services

Contact Alex Hunt Learn more about Alex Hunt

Why Grant Thornton

We bring together our data and analytics governance experts to shape the right level of governance that balances the need to deliver benefits and ensure compliance.

Our team is your team – we work collaboratively, transparently, and with a proven ability to deliver sustainable solutions that are specialised for the size and maturity of your AI capabilities.

You can establish comprehensive governance in confidence, leveraging our innovative tools and field-tested framework.

Preparing your data for AI

There's an increasing need to educate executives on essential data management practices required for adopting AI models. Widespread AI innovation and deployment presents both opportunities and challenges for chief data officers, who face the task of accelerating readiness, ensuring that business data is accurate, complete, and formatted in a way that can be easily processed by AI systems.

This can be done by implementing company-wide data quality programmes and governance frameworks, including the connection of AI initiatives to tangible business value while safeguarding ethics, security, and privacy.