AI CoE Blueprint
Data & AI
Motivation
Organizations in various sectors increasingly recognize Artificial Intelligence as essential for enhancing efficiency, driving innovation, and maintaining competitiveness. Despite this recognition, many face difficulties in translating their aspirations into a defined strategic direction and actionable steps.
An AI Center of Excellence (CoE) provides the organizational backbone needed to adopt AI in a structured, safe, and scalable way. It brings together the expertise, standards, and decision frameworks that ensure AI initiatives are aligned with business goals rather than driven by isolated experiments. A CoE builds capabilities across the workforce, strengthens confidence in using AI, and creates clarity around roles, responsibilities, and governance. By enabling teams, reducing duplication, and guiding the organization from early use‑case exploration to enterprise‑wide adoption, a CoE prevents fragmentation and accelerates the path from ambition to tangible, repeatable value.
What we bring
Forvis Mazars, Bolzhauser, and PRODYNA combine organizational, governance, and technology expertise to design and establish AI Centers of Excellence that scale.
We help you:
- Define a clear AI operating model, aligned with business goals
- Establish governance, standards, and principles for responsible AI
- Build cross‑functional CoE roles, skills, and ways of working
- Enable teams to identify, assess, and deliver high‑impact AI use cases
- Integrate AI into processes, data platforms, and enterprise environments
- Create a scalable foundation for AI adoption across the organization
What you need
To effectively establish an AI Center of Excellence (CoE) and foster innovation as well as value creation within your organization, it is essential to ensure the following elements are in place:
- Clear Strategic Context: Articulate business objectives, priorities, and current challenges
- Broad Stakeholder Participation: Engage representatives from management, business units, IT, data & governance
- Openness to Challenge: Demonstrate a willingness to critically examine assumptions and existing initiatives
- Decision-Maker Availability: Maintain commitment from leaders to align on strategic direction and priorities
- Dedicated Team: Form a focused and motivated group of employees who will serve as core contributors and champions for AI throughout the organization
What you get
Our deliverables include:
- A clear and shared AI target vision that aligns business ambition with organizational and technological reality.
- A prioritized AI use case landscape grounded in business value, feasibility, and strategic relevance, including the identification of a Lighthouse MVP candidate. A Lighthouse MVP is a focused, high‑impact pilot use case that demonstrates tangible value, creates organizational momentum, and serves as a blueprint for broader AI adoption.
- A structured assessment of data, IT, skills, and organizational implications required for sustainable AI adoption.
- A CoE framework that embeds change‑management principles from the start.
- A pragmatic, phased roadmap for setting up an AI Center of Excellence with clear priorities across technology, organization, and enablement.
AI CoE Blueprint follows a proven, structured phase model aligned with enterprise AI adoption:
Strategy & Vision
- AI ambition and strategic intent definition
- Alignment of AI objectives with business goals
- Clarification of the role of AI within the organization
Deliverable: A clearly articulated AI target vision with strategic objectives and guiding principles.
Lighthouse MVP Envisioning
- Identification of AI use cases along business workflows and job roles
- Mapping tasks and responsibilities to AI augmentation and automation potential
- Structured evaluation of use cases based on business impact, feasibility, and risk
- Selection and sharpening of one mandatory Lighthouse use case
Deliverable: A prioritized lighthouse MVP definition with clear value focus and selection rationale.
Data & IT Infrastructure Capability Assessment
- High-level assessment of data availability, quality, and access
- Evaluation of existing platforms, tools, and integration capabilities
- Identification of critical gaps and dependencies for AI delivery
Deliverable: A structured Data & IT readiness and gap perspective for AI and the lighthouse MVP.
Human Capability & Organizational Evolution Design
- Identification of essential organizational and workforce-related factors based on AI readiness insights
- Design of a target‑group‑specific change approach interviews and workshops to understand expectations, concerns, and adoption barriers
- Design and facilitation of initial AI experience spaces to engage employees with the MVP at an early stage
Deliverable: A validated change framework ensuring clear roles, transparent decision paths and processes.
CoE Roadmap Definition
- Consolidation of strategic, technical, and organizational insights
- Definition of a phased AI Center of Excellence setup
- Prioritization of initiatives and capability-building measures
Deliverable: A pragmatic, phased AI CoE roadmap providing a clear transition into execution and scaling.
Quick facts
- Duration: 4-6 weeks
- Format: Workshops, interviews, and expert-led synthesis
- Stakeholders: Broad, cross-functional involvement
Benefits
- Turn assessment results into a focused AI vision and strategy.
- Align executives and stakeholders from business, IT, and management.
- Focus strategy on one practical, high-impact lighthouse MVP.
- Reduce risk by making informed decisions before scaling AI.
- Outline a phased plan for setting up an AI Center of Excellence.
- Ready the organization, technology, and governance for scalable AI.
