BUI Secure AI Landing Zone

Most organisations with Microsoft Azure investment have AI activity underway: pilots, vendor conversations, Copilot deployments. But very few have a coherent plan for what comes next. When the board asks how AI will scale, the honest answer is often that no-one is sure.

The foundations are missing: there is no governing model, no secure Azure environment built for AI workloads, and no structured way to move from proof of concept to production.

This assessment helps customers get started with Microsoft Azure AI services the right way. In four weeks, you will have an approved Microsoft Azure architecture for AI, a prioritised use case roadmap, and a clear implementation plan so you can move forward with confidence.

What you get

The assessment delivers clear, actionable output across three areas.

1. AI readiness and current-state review

Executive briefing on the AI ecosystem (Azure AI, agents, Copilot, Foundry) so leadership has a shared understanding of the options and trade-offs Assessment of your current cloud estate, security posture, data architecture, and operational readiness for AI workloads Review of existing AI activity: what is in flight, what is shadow AI, and what is at risk without proper governance

2. Governance model and AI Centre of Excellence design

Options for an AI operating model and Centre of Excellence, covering intake, prioritisation, ownership, and decision-making Responsible AI and compliance considerations mapped to your regulatory and risk context Buy, extend, or build guidance for your first wave of use cases

3. Microsoft Azure secure landing zone architecture and use case roadmap

A target reference architecture for your Microsoft Azure secure AI landing zone, covering governance, identity and access, networking, secrets management, data foundations, observability, and environment model. Built to Microsoft standards and best practices. A prioritised use case heatmap, sequenced into crawl, walk, and run stages, with value and feasibility mapped against risk A structured implementation plan and investment roadmap you can take to leadership for approval, with a clear path to extending your use of Microsoft Azure for AI workloads

How the four weeks are structured:

Week 1: Kick-off, briefings, current-state interviews, AI activity inventory, risk and compliance context Week 2: Executive AI ecosystem workshop, use case intake sessions, pattern scoring, preliminary prioritisation Week 3: Secure AI landing zone design workshops, CoE and operating model options, data and integration architecture review Week 4: Use case heatmap finalisation, implementation roadmap, executive readout, investment and next-steps recommendation

Who this is for:

Organisation: Mid-market to enterprise with Microsoft Azure investment and multiple business units or workstreams with AI interest Executive sponsor: CIO, CISO, CTO, Chief Data Officer, or business executive accountable for AI value and governance Common triggers: Board pressure to show an AI strategy, concern about shadow AI, failed or stalled pilots, need to meet audit or compliance requirements, or interest in Microsoft Copilot and agents Technical context: Azure or hybrid cloud estate, data spread across enterprise systems, need for governed and secure AI deployment

What happens after the assessment:

The assessment leads naturally into implementation. BUI's Secure AI Landing Zone implementation takes the approved Microsoft Azure architecture and roadmap and builds the foundation, deploying the Microsoft Azure landing zone and delivering the first production-ready AI use case on Azure. Together, the assessment and implementation form a complete path to governed, scalable AI delivery on Microsoft Azure.

Deliverables

AI ecosystem briefing: Common understanding of Azure AI, agents, Copilot, and Foundry options, tailored to your environment Current-state assessment: Review of cloud architecture, security posture, data estate, skills, and AI readiness Use case prioritisation scorecard: Ranked use case backlog with value, feasibility, risk, and strategic fit mapped AI operating model and CoE blueprint: Options for governance, intake, prioritisation, and ownership structures Microsoft Azure secure AI landing zone reference architecture: Target design covering all nine control domains on Microsoft Azure, with implementation decisions and dependencies Implementation backlog and roadmap: Phased plan with sequencing, dependencies, and investment guidance