Responsible AI - Azure Governance

Service Overview

As organisations scale AI adoption on Azure, the complexity of governing it safely, ethically, and in compliance with emerging regulations grows with it. Rmkble's Responsible AI accelerator helps you build a practical, organisation-ready governance model — fast.

Rather than a generic framework, this engagement delivers a tailored governance baseline built around your Azure AI environment — your AI maturity, risk appetite, and strategic direction. We draw on Rmkble's deep investment in AI governance frameworks, tools, and templates, and our hands-on experience governing Microsoft AI platforms including Azure AI Foundry, Azure OpenAI Service, Microsoft Copilot, Azure Machine Learning, and Microsoft Purview, to accelerate your path to a governance model you can use immediately.

The engagement moves your organisation from fragmented AI oversight to a coherent, production-ready governance foundation across four structured stages: Map, Track, Steer, and Govern — grounded in your Azure Data and AI landscape from day one.

Common Client Challenges

• Shadow AI and unmanaged risk across Azure-hosted AI workloads and services
• No consistent framework for assessing and approving AI use cases on Azure AI Foundry or Azure OpenAI Service
• Limited visibility into where AI models are deployed, what data they consume, and what risks they introduce
• Pressure to demonstrate compliance and responsible AI use to regulators, boards, and Microsoft audit requirements
• Governance structures that lag behind the pace of Azure AI adoption and model proliferation

How It Works

• Map: Discover and map AI use across your Azure environment — models, datasets, services, and associated risks — using Azure tooling including Microsoft Purview and Azure AI Foundry.
• Track: Develop monitoring tools and dashboards to track AI risks, model usage, and compliance signals in real time across your Azure Data and AI estate.
• Steer: Establish governance mechanisms, policies, and frameworks that guide responsible AI use — aligned to Microsoft's Responsible AI principles and your Azure platform controls.
• Govern: Embed governance, continuous improvement, and accountability models across your organisation to sustain responsible AI at scale on Azure.

Delivery Activities

• Stakeholder interviews and workshops scoped to your Azure AI platform and use-case landscape
• Targeted desktop analysis to align governance artefacts to Microsoft Responsible AI standards, Azure Policy, and relevant regulatory frameworks
• Review, enhancement, and/or creation of key governance artefacts
• Hands-on support for the governance review of a first live Azure AI use case

Deliverables and Outcomes

Deliverables:

• AI Standards Documentation (aligned to Microsoft Responsible AI principles and Azure platform controls)
• AI Use-Case Assessment Questionnaire (tailored for Azure AI Foundry and Azure OpenAI scenarios)
• AI Risk Assessment Method
• AI Register Schema (structured for Azure-hosted models and data assets)
• AI Review Playbook
• Board Pack (governance reporting template)
• Vendor & Model Assessment Checklist (including Azure Marketplace AI services)
• One live client use-case assessment

Outcomes:

• A practical, immediately usable AI governance baseline for your Azure AI environment
• Cross-functional executive alignment on AI governance, risk, and Microsoft platform accountability
• Clarity on Azure AI maturity and the capability investments required to scale confidently
• Confidence to expand Azure AI adoption safely, responsibly, and with regulatory readiness
• Organisational alignment through co-design, collaboration, and embedded Azure-native practices