The road to enterprise-ready AI and Agentic AI

Create a team of experts –
AI Center of Excellence (AICoE)

The Excellence: Form a cross-functional team of Data Scientists, AI Engineers, AI Architects, AI Consultants, AI Product Managers and Ethics Officers. (Read our whitepaper)
Single Point of Contact: Designate this team as the primary point of contact for all AI and Agentic AI inquiries and initiatives and communicate this change within the company
Cloud and AI: Ensure the AICoE works hand-in-hand as equal partners with your existing Cloud Center of Excellence (CCoE)
Training Facilitator: Assign this team to act as a central training facilitator by organizing internal upskilling, coordinating external expert sessions, and driving engagement through AI weeks, hackathons, and ideation challenges

Inventory & Brokerage: Identify existing AI use cases and centralize them into a corporate-sanctioned catalog
AI Data Readiness: Ensure high-quality, compliant relevant business data is available for model fine-tuning and RAG
Model Selection: Decide which models (LLMs, SLMs, or Vision) fit specific business outcomes

AI Governance: Create a “Responsible AI” framework aligned with the EU AI Act that classifies agents by risk (Personal, Company Data, or Critical) and enforces strict oversight pillars including central cataloging and designated ownership (Manager/Data Owner)
Agent Orchestration: Implement controls for Autonomous AI Agents to define what processes agents can touch and where a “human-in-the-loop” is required.
Risk Management: Develop a risk scoring system (similar to CIS/NIST) and use AI Control Questions (unit tests) to verify that agent logic and quality remain stable.
Data Leakage Prevention: Establish governance in non-sanctioned AI solutions via data classification and automatic leakage detection in files and prompts using AI-driven web proxies.

Centralized AI Hosting: Build a platform to host and serve AI models securely and at scale
Standardized Services: Provide a “Service Vending Machine” including Personal Assistants (eg. Microsoft Copilot) and RAG-as-a-Service templates for all departments
Industrialization: Automate AI Ops pipelines to transition experimental AI workloads into robust, production-ready environments

Business Transformation: A dedicated, business-driven team focused on rethinking internal offerings and creating new external AI services
Innovation Engine: Incubate the best ideas from the Facilitator’s hackathons and ideation challenges to surface bottom-up ideas from the workforce and turn them into scalable products
AI Literacy: Implement a company-wide program to promote “AI literacy” to ensure that all employees, from the CEO to front-line staff, know how to use AI and AI agents to increase their personal effectiveness
Performance Monitoring: Implement centralized cost and performance monitoring for all AI models and AI agents to optimize efficiency and business value