Building your AI Center of Excellence on Google Cloud (BACEGC)

 

Course Overview

The course, Building your AI Center of Excellence on Google Cloud, is a strategic program designed to help organizations move from fragmented, siloed innovation to a structured, enterprise-wide AI strategy. It focuses on the creation of an AI Center of Excellence (CoE)—a cross-functional unit that centralizes expertise and governance to accelerate AI value. The curriculum is built around four foundational pillars: Strategy, Structure, Governance, and Scale.

Participants will learn through a combination of case studies and practical demonstrations of Google Cloud tools like Gemini Enterprise. By the end of the 3-hour session, leaders will have a strategic roadmap for building an AI CoE that aligns with their organizational maturity.

Who should attend

  • Business leaders
  • C-suite executives such as CIOs and CDOs
  • Strategic leads responsible for enterprise-wide AI transformation and governance

Prerequisites

Helpful to be familiar with:

  • Familiarity with cloud concepts
  • General understanding of organizational business strategy

Course Objectives

  • Construct a formal AI CoE charter that translates business strategy into a dual-track mandate.
  • Design a cross-functional CoE structure by selecting the appropriate operating model based on your organization's current maturity phase.
  • Apply governance playbooks to your dual-track AI projects for safe and effective AI implementation.
  • Evaluate AI transformation success using a balanced KPI framework to roadmap the CoE's evolution.

Outline: Building your AI Center of Excellence on Google Cloud (BACEGC)

Module 1 - The case for an AI CoE

Topics:

  • 1. The challenges facing transforming organizations
  • 2. Defining the AI CoE
  • 3. Pillars of the AI CoE

Objectives:

  • Explain the organizational need for centralized AI leadership.
  • Identify the core pillars of strategy, structure, governance, and scale.

Module 2- Strategy: Building a Business-Aligned Vision

Topics:

  • 1. Identifying the Right Tools for Your Organization
  • 2. Securing Executive Sponsorship
  • 3. Building your AI CoE Charter

Objectives:

  • Balance immediate impact with long-term strategy with a dual-track framework.
  • Build a business outcome-focused executive sponsorship case.
  • Write a formal AI CoE charter to guide successful AI transformation.

Activities:

  • 3x Demos
  • 1x Exercise

Module 3 - Structure: Building Operating Models and Workflows

Topics:

  • 1. Choosing Your Operating Model
  • 2. Staffing your AI CoE
  • 3. Establishing your AI CoE Workflows

Objectives:

  • Design a cross-functional CoE structure by selecting the appropriate operating model based on your organization's current maturity phase.
  • Select the write people to staff your AI CoE.
  • Establish clear and efficient AI CoE workflows.

Activities:

  • 1x discussion

Module 4 - Data Management and Governance: Building Guadrails for Safe Execution

Topics:

  • 1. Dual-Track Governance
  • 2. Security on Google Cloud Platform

Objectives:

  • Apply governance playbooks to your dual-track AI projects for safe and effective AI implementation.
  • Implement responsible AI governance review processes and apply governance principles.
  • Use Google Cloud’s security architecture and secure AI framework for safe AI implementation.

Activities:

  • 1x discussion

Module 5 - Measure and Scale: Executing Enterprise-Wide Transformation

Topics:

  • 1. Measuring AI Impact on Business Outcomes
  • 2. The AI CoE Strategic Roadmap

Objectives:

  • Identify and report on dual-track KPI metrics that accurately measure business impact.
  • Construct a three-phase strategic roadmap that transitions the AI CoE from a centralized foundation to a federated scaling model, identifying specific milestones aligned with the organization’s current maturity level.

Activities:

  • 1x exercise

Module 6 - Summary and Quiz

Topics:

  • Review core concepts

Objectives:

  • Evaluate understanding of core course concepts through scenario-based questions.

Activities:

  • 4 scenario-based multiple choice questions.

Prices & Delivery methods

Online Training

Duration
3 hours

Price
  • US $ 350
Classroom Training

Duration
3 hours

Price
  • United States: US $ 350

Schedule

Currently there are no training dates scheduled for this course.