Certified AI Transformation Professional

What you will be able to do

• Assess an organization's AI maturity and readiness
• Build an AI strategy tied to business outcomes
• Design an operating model and governance for AI
• Prioritize a portfolio of AI use cases by value and feasibility
• Lead the people side of change, including workforce reskilling
• Measure and report value across the portfolio

Modules

1. 1Maturity and readiness

   Where the organization stands today across strategy, data, technology, skills, governance and culture.

   • Maturity models and their limits
   • Data and content readiness
   • Skills and culture assessment
   • Readiness heat maps for leadership

   Exercise. Score your own organization on six readiness dimensions and identify the lowest one.

2. 2Strategy tied to outcomes

   An AI strategy is a business strategy with AI in it. It names outcomes, not technologies.

   • From business goals to AI opportunities
   • Value pools and where AI moves them
   • Principles and risk appetite
   • The one-page strategy

   Exercise. Write a one-page AI strategy for a function you know, naming three measurable outcomes.

3. 3Portfolio and prioritization

   Choosing which use cases to fund using value, feasibility, risk and dependency.

   • Use-case intake and screening
   • Value-feasibility matrices
   • Dependencies on shared data and platforms
   • Stage-gated funding

   Exercise. Rank ten candidate use cases on a value-feasibility matrix and choose the first three.

4. 4Operating model and governance

   Who decides, who builds and who is accountable once AI is used across many teams.

   • Center of excellence, hub-and-spoke and federated models
   • AI governance boards and policy
   • Model inventory and risk tiers
   • Standards for data, security and procurement

   Exercise. Design a three-tier risk classification for AI uses with the approval each tier needs.

5. 5People and change

   Adoption fails on people more often than on technology. Plan for roles that change, skills that are needed and the fears that come with both.

   • Stakeholder and impact analysis
   • Role redesign and reskilling paths
   • Communication that addresses job concerns honestly
   • Champions networks and adoption measures

   Exercise. Build a change impact assessment for one role whose daily work will change with AI.

6. 6Measuring value

   Baselines, benefit owners and portfolio reporting that show leadership what AI has returned.

   • Baselines before deployment
   • Leading and lagging measures
   • Attributing value fairly
   • Portfolio dashboards and reviews

   Exercise. Define the baseline, benefit owner and two measures for one approved use case.