Become an AWS AI Business Strategist

This course is intended for:

- Business executives and senior leaders responsible for AI strategy

- Product managers and Program managers driving AI initiatives

- IT and Technology leaders overseeing AI adoption

- Risk, compliance, and governance professionals

- Organizational change management and HR leaders supporting AI transformation

In this course, you will learn to do the following:

• Transform ambiguous business challenges into scoped, AI-appropriate problem statements.
• Apply the 3D framework (Discover, Design, Deliver) to assess organizational readiness and map problems to AI capabilities
• Evaluate tradeoffs between business objectives and responsible AI principles, balancing value, feasibility, risk, and ethics
• Design pilot strategies with measurable success criteria and phased scaling paths to enterprise deployment
• Facilitate AI change management by addressing workforce concerns and structuring cross[1]functional teams
• Explain core AI/GenAI concepts to evaluate solution feasibility and inform build-buy-partner decisions

Module 0: Welcome and Course Overview

• Access Labs and Guides

Module 1: The AI Business Strategist's Toolkit

• The AI business strategist's role
• The Enterprise Strategy Layer
• The 3D framework
• Technical Foundations: What the AI Business Strategist Needs to Know
• Activity: Scenario Triage

Module 2: Discover: Problem, Readiness, and Data Foundations

• Diagnose the Customer's Actual Problem
• Assess Organizational Readiness
• Establish Data Foundation
• Activity: Discovery

Module 3: Design: Capabilities, Governance, and Scope

• Map Business Problems to AI Capabilities
• Weave in Governance and Responsible AI
• Specify POC scope and pilot success criteria
• Activity: Governance in a Regulated Architecture

Module 4: Deliver: Pilot, Change, and Scale

• Build, calibrate, and evaluate the POC
• Deploy bounded pilot and lead change
• Scale from Pilot to Enterprise and Connect to Strategy
• Activity: Deliver

Module 5: Agentic AI: Architecture, Evaluation, and Production

• Multi-Agent Architectures
• Autonomy vs. Control in Depth
• Generation, Evaluation, and Production
• Activity: Break the Agent

Module 6: Discover Together

• Use Case Introduction and Framework Review
• Simulation Debrief

Module 7: Design Together

• Map Pain Points to AI Capabilities
• Governance by Design
• POC scope and pilot success criteria

Module 8: Deliver Together

• Build, calibrate, and evaluate the POC
• Deploy bounded pilot and lead change
• Scale to enterprise platform

Module 9: Summary and Continue Your Learning

• Next Steps for Continued Learning

We recommend that attendees of this course have the following:

• Business or technology leadership experience
• Familiarity with enterprise technology initiatives
• Basic understanding of cloud computing concepts
• Optional: AWS Cloud Practitioner Essentials (foundational cloud literacy)

• None

• None Recommended

• GK910027 - Generative AI Essentials on AWS
• GK910031 - Agentic AI Foundations
• GK910039 - AWS Spec-Driven Development with Kiro