Achieving Responsible AI with SAFe® (AIwithSAFe)

The "Achieving Responsible AI with SAFe®" course is a SAFe Micro-credential designed to equip Agile professionals with practical skills to implement Responsible AI (RAI) within their organizations. It blends a one-hour self-paced eLearning module with a half-day (approximately four-hour) facilitated interactive session focused on real-world applications and hands-on activities

Course Structure and Content

• Self-paced eLearning (1 hour):
  Introduces foundational concepts of Responsible AI and aligns them with SAFe principles. Includes pre-work assignments such as researching current RAI practices in the participant’s organization, reviewing example policies, and preparing for practical exercises using generative AI tools

• Facilitated Session (4 hours):
  Engages participants in practical activities including:

  • Identifying key stakeholders involved in RAI initiatives and mapping their responsibilities and concerns (~30 minutes).

  • Evaluating and critically analyzing example RAI policies using AI tools like SAFe CoPilot and ChatGPT to tailor policies for organizational fit (~25 minutes).

  • Developing effective communication skills to advocate for RAI initiatives via an elevator pitch that aligns RAI goals with organizational objectives (~30 minutes).

  • Writing an RAI Epic Hypothesis Statement to scope significant efforts needed by Value Streams for RAI implementation (~35 minutes)

Learning Objectives

Participants will learn:

• What Responsible AI is and why it is critical in today’s organizations.

• How SAFe Core Values and Principles enable the application of Responsible AI.

• Ways to incorporate Responsible AI into portfolio strategy and Lean Portfolio Management (LPM).

• The impact of Responsible AI solutions on Agile Release Trains (ARTs) and Agile teams.

• How to develop actionable plans for continuous improvement and leadership in Responsible AI initiatives

Who Should Attend

• SAFe professionals aiming to understand and develop Responsible AI policies.

• Agile Coaches, Release Train Engineers (RTEs), Scrum Masters, and other Agile leaders involved in AI initiatives.