AI Envisioning Workshop

AI Envisioning Exercise for Executive Leadership (Enabled by Microsoft Azure OpenAI)

Purpose: To align senior leadership around a shared understanding of AI’s strategic relevance, demonstrate the practical potential of generative AI through Microsoft Azure OpenAI Services, and identify high-value use cases that support core business priorities.

Overview: This executive-level workshop is a structured, half-day session tailored for C-suite leaders and senior business unit heads. The session focuses on demystifying AI—especially generative AI—and exploring how Microsoft’s Azure OpenAI capabilities can be deployed to accelerate innovation, drive operational efficiency, and unlock new business models.

Objectives:

1. Educate leaders on the AI landscape, with a focus on the enterprise-grade capabilities of Azure OpenAI (e.g., GPT, Codex, DALL·E)
2. Showcase practical, real-world use cases powered by Azure OpenAI relevant to the organisation's industry.
3. Assess current organisational readiness (data maturity, cloud infrastructure, governance) for generative AI.
4. Co-design a shortlist of Azure OpenAI-powered use cases with business impact potential.
5. Define a roadmap to pilot and scale selected use cases using Microsoft’s secure and compliant AI stack.

Session Format:

Part 1: Strategic Framing (30 mins) Overview of AI’s business value with emphasis on generative AI trends. Includes competitor moves and Microsoft ecosystem advancements.

Part 2: Azure OpenAI Capability Deep Dive (30 mins) Interactive demos of Azure OpenAI use cases (e.g., knowledge assistants, intelligent document processing, automated code generation). Discuss architecture, governance, and security implications.

Part 3: Ideation Workshop (60 mins) Facilitated session using Microsoft’s AI transformation framework to identify high-value opportunities across business functions. Focus on use cases where GPT-powered solutions can deliver measurable outcomes.

Part 4: Prioritization & Action Planning (30 mins) Rank opportunities by impact and feasibility. Outline next steps including pilot scope, data dependencies, responsible AI governance, and success metrics.

Outputs:

• A curated list of 3–5 Azure OpenAI-powered use cases aligned with strategic goals
• Visual “use case canvas” for each opportunity: business value, user journey, architecture sketch
• Executive briefing pack with maturity assessment and pilot roadmap
• Initial governance and capability recommendations for responsible AI adoption using Microsoft tools (e.g., Purview, Responsible AI dashboard)