AI CoE and Solution Envisioning

AI CoE and Solution Envisioning is a structured consulting engagement designed to help organizations move from fragmented AI initiatives to a clear and actionable enterprise AI adoption strategy on Microsoft Azure. Many organizations have multiple AI ideas, early proofs of concept, or Generative AI initiatives, but lack a consistent framework to evaluate business value, technical feasibility, and risk in the context of scalable cloud implementation.

This offer helps customers establish a practical AI Center of Excellence (CoE), align stakeholders, and prioritize AI use cases that can be implemented using Microsoft Azure services. The engagement includes a structured 6-week program that combines strategy, governance, use-case discovery, prioritization, and rapid validation.

During Week 1 – AI Vision & CoE Foundation, executive and business stakeholders participate in alignment workshops focused on AI vision, CoE objectives, business impact, organizational culture, technology readiness, and adoption strategy. The outcome is a shared understanding of AI ambitions and a foundation for establishing an AI Center of Excellence.

In Week 2 – AI Discovery, collaborative workshops are conducted to identify and document AI opportunities across business functions. Participants define candidate use cases, align key stakeholders, and establish evaluation criteria covering business value, feasibility, risk, and strategic relevance. This phase results in a structured inventory of AI use cases and an evaluation framework.

During Week 3 – Use Case Alignment and Prioritization, identified use cases are assessed using a scorecard-based methodology. Activities include capability mapping, AI pattern identification, business objective and OKR alignment, and high-level architecture envisioning. The outcome is a prioritized set of AI initiatives and a recommended AI roadmap aligned with organizational goals and Azure capabilities.

During Weeks 4–6 – Proof of Value, one selected high-priority use case is validated through rapid prototyping on Microsoft Azure. The prototype leverages relevant Azure services, including Azure OpenAI Service, Azure AI Foundry, Azure Machine Learning, and modern data platform capabilities where appropriate. The objective is to validate technical feasibility, assess business value, identify implementation considerations, and support investment decisions before moving into full-scale delivery.

Throughout the engagement, capability envisioning activities help define the target architecture, required data platform components, governance approach, and AI operating model necessary for scalable adoption on Azure.

By the end of the engagement, customers receive:

An AI CoE vision and operating model foundation AI use-case inventory and evaluation framework Prioritized AI roadmap and selected use cases High-level Azure-based architecture recommendations Proof of Value (PoV) prototype for one prioritized use case Feasibility assessment and business recommendations Next-step implementation roadmap for enterprise AI adoption on Microsoft Azure

This engagement provides organizations with a practical path from AI ideation to validated business outcomes while establishing the governance, architecture, and organizational foundations required for successful and scalable AI implementation on Microsoft Azure.