- What is Enterprise AI
- Introduction: A New Technology Stack
- Requirements of the New Enterprise AI Technology Stack
- Reference AI Software Platform
- Awash in “AI Platforms”
- “Do It Yourself” AI?
- The Gordian Knot of Structured Programming
- Cloud Vendor Tools
- C3 AI Platform: What is Model-Driven Architecture
- Platform Independence: Multi-Cloud and Polyglot Cloud Deployment
- Conclusion: A Tested, Proven AI Platform
- Enterprise AI Best Practices
- Enterprise AI Buyer’s Guide
- 10 Core Principles of Enterprise AI
- IT for Enterprise AI
- Develop AI 26X Faster on AWS
- Develop AI 18X Faster on Azure
- Enterprise AI Resources
Best Practices for Governing the AI Application Lifecycle: The Center of Excellence
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A typical large organization will seek to deploy hundreds of enterprise AI applications in the coming years, and will operate, refine, and support these applications over many years. Creating an effective organizational structure to govern the development, deployment, and operation of these applications at scale is essential to achieving sustained results.
This paper describes best practices in creating a Center of Excellence (CoE) – a proven model for designing, building, and operating enterprise AI applications at scale. These best practices are based on C3 AI’s methodology, derived from a decade of experience in working with dozens of the world’s leading organizations on large-scale enterprise AI deployments.
Contents of this paper include:
- Setting Objectives for a CoE
- CoE Critical Success Factors
- How to Structure the CoE
- Roles and Responsibilities of the CoE
- Staffing the CoE Team

