Course Taxonomy: Data & AI

Lesson 1 – Change Agent: Guiding Your Organization to True AI Success

Focus: Orientation and foundational mindset

Key topics:

• Course logistics, setup, and tools (Companion app, BYO-LLM)
• Working agreements and safety: Be present, not perfect
• Core skillset of an AI-Native Change Agent
  • AI Fluency
  • Value Maximization
  • AI-Powered Facilitation
  • Solution Lifecycle mastery
• Course outcome: move projects beyond the “POC graveyard,” guide AI adoption, and amplify organizational impact

Lesson 2 – Advancing AI Fluency

Focus: Translate AI concepts into business language

You will learn to:

• Translate technical AI trade-offs into business value
• Differentiate core AI solution patterns:
  • Off-the-shelf vs. Custom build
  • Retrieval-Augmented Generation (RAG)
  • Fine-Tuning
  • AI Agents
• Evaluate feasibility with filters and risk lenses
• Identify technical and process red flags
• Discussion: What gets lost in translation between business and technical teams?

Lesson 3 – Value Maximization

Focus: Unlock hidden value in existing AI assets

You will learn to:

• Audit AI tools already in use
• Activate underused capabilities by tracking AI evolution
• Optimize to improve efficiency and ROI
• Centralize best practices to scale success and prevent redundancy
• Concepts introduced:
• Audit → Activate → Optimize → Centralize framework
• The 7 AI-Native Success Factors
• When to build POCs vs. full solutions

Lesson 4 – AI-Powered Facilitation

Focus: Align people and resolve friction in AI initiatives

You will learn to:

• Recognize stakeholder goals and fears
• Use AI to generate powerful questions and manage conflict
• Build psychological safety and constructive dialogue
• Guide meetings with focus and clarity
• WIIFM: Learn to keep initiatives moving forward when teams stall or disagree.

Lesson 5 – Sense & Discover

Focus: The first phase of the AI-Native Solution Lifecycle

You will learn to:

• Identify and analyze key stakeholders
• Uncover hidden risks and opportunities
• Apply AI-assisted discovery to find the real business problem
• Create a living AI-Native Solution Charter
• Outcome: Get the right people focused on the right AI problem using AI as your discovery partner.

Lesson 6 – Design the Solution

Focus: Building the AI-Native Value Blueprint

Key components:

• Value Proposal – The why: define success and outcomes
• AI Solution – The what: approach and interaction design
• Data Strategy – The fuel: sourcing, securing, managing data
• Production Operations – The path to production: maintaining and scaling
• Risk & Compliance – The guardrails: responsible AI and governance
• Viability Assessment – The payoff: ROI and adoption readiness

Lesson 7 – Deliver the Solution

Focus: Execution and continuous learning

You will learn to:

• Build resilient, adaptive AI roadmaps
• Maintain momentum and remove blockers
• Apply agile learning cycles for rapid iteration
• Measure value and ensure readiness for deployment
• Outcome: Confidently guide your team through AI implementation to successful launch.

Lesson 8 – Tell the Story

Focus: Amplifying success with AI-powered storytelling

You will learn to:

• Identify impactful success stories within your organization
• Use AI tools to adapt and scale those stories
• Create narratives that inspire enterprise-wide adoption
• Discussion: Why do successful AI pilots stay trapped in silos?
• Outcome: Transform one AI win into a company-wide success story.

Lesson 9 – Expanding Your Impact

Focus: Career and organizational growth

You will learn to:

• Create a personal roadmap as an AI-Native Change Agent
• Align your learning and certification goals
• Apply course tools in real projects
• Facilitate AI-Native Value Process end-to-end
• Phases of Impact:

1. Foundation & Opportunity Identification – Audit readiness, find AI opportunities
2. Propose & Prepare – Build business case and solution charter
3. Deliver & Scale – Lead implementation and storytelling to amplify success

Self-paced, on-demand eLearning (1 hour)

The eLearning module comprehensively introduces Responsible AI, covering foundational concepts and their alignment with SAFe practices. The eLearning includes several pre-work assignments intended to fully prepare students for the facilitated session — including researching current RAI practices in your organization, reviewing example policies, and ensuring access to a generative AI tool for practical exercises.

Activity 1 – Identifying Stakeholders (~30 minutes)

As future change agents and advocates for RAI, one of the first and most important tasks is to think about the people in an organization who would need to be involved in implementing RAI, what their responsibilities would be, as well as their top concerns. Learners will leave this activity with an actionable stakeholder map for future initiatives.

Activity 2 – Evaluating RAI Policies (~25 minutes)

Get hands-on experience using GenAI applications such as SAFe CoPilot and ChatGPT to apply critical thinking to an example set of policy elements in an RAI plan, identifying improvements needed for organizational fit.

Activity 3 – Communicating the Need for RAI (~30 minutes)

Become empowered to effectively communicate the need for Responsible AI (RAI), the goals of an RAI initiative, and the alignment of an RAI initiative with organizational objectives through a concise “elevator pitch” activity.

Activity 4 – Writing an RAI Epic Hypothesis Statement (~35 minutes)

Practice identifying an actionable element of an RAI implementation that requires a significant effort by one or more Value Streams, and scoping that effort using a SAFe Epic hypothesis statement.