Artificial intelligence is reshaping how software is built — and the role of the Scrum Master is changing with it. Teams now manage AI feature sprints, LLM integration releases, model evaluation gates, and prompt governance alongside traditional delivery work. Yet no certification existed to validate these skills — until CREA-AI-SM.
What Is CREA-AI-SM?
CREA-AI-SM (Certified Role in Enterprise Agility — AI Scrum Master) is the advanced credential for Scrum Masters operating in AI-enabled delivery environments. It builds directly on CREA-SM and adds four specialist modules covering the intersection of agile delivery and artificial intelligence.
Why This Certification Exists
Traditional Scrum Master certifications were designed in an era of deterministic software — build a feature, test it, ship it. AI components don't work this way. Model behaviour is probabilistic. Releases require validation gates. Prompt outputs need governance frameworks. Sprint velocity calculations shift when team members use AI-assisted coding tools.
CREA-AI-SM addresses the real challenges practitioners face right now:
- How do you run a sprint retrospective when half the "work" was done by an AI agent?
- How do you manage a release risk for a feature that uses an LLM with non-deterministic outputs?
- How do you facilitate daily standups when AI tools have automated portions of the team's workflow?
- What does a Definition of Done look like for an AI-generated feature?
The Four AI Specialist Modules
Module 7: AI Delivery Foundations for Scrum Masters
Covers AI product cycles and how they differ from traditional software cycles. Sprint adaptation for model training releases. Managing AI-assisted delivery teams where velocity is affected by tool augmentation. Facilitating AI feature planning sessions with engineering and data science stakeholders.
Module 8: AI Tools for Scrum Masters
Evaluating and using AI-powered facilitation tools — automated retrospective platforms, AI-assisted impediment tracking, LLM-powered standup summaries, and sprint reporting generation. Includes a practical tool selection framework and common anti-patterns.
Module 9: Release Risk Management for AI Components
Risk frameworks specific to AI feature releases. Model validation gates within sprint cycles. Rollback planning for non-deterministic AI outputs. Bias detection checkpoints as part of your Definition of Done. Stakeholder communication frameworks for communicating AI release confidence.
Module 10: Exam Preparation — AI Context
Scenario-based practice questions covering all AI modules. Integration of AI concepts with core Scrum Master responsibilities. Full mock exam (80 questions, 90 minutes) covering both core CREA-SM content and AI specialist modules.
Who Is CREA-AI-SM For?
- Scrum Masters in fintech, healthtech, or enterprise software where AI features are now part of every product roadmap
- Practitioners who already hold CREA-SM and want a differentiated credential for AI-era delivery
- RTE candidates who need to demonstrate AI delivery competency at programme level
- Agile Coaches supporting teams that use AI-assisted development tools (GitHub Copilot, Cursor, etc.)
How It Compares to Other AI Certifications
No other major certification body offers an AI-specific credential for Scrum Masters. CREA-AI-SM is the first. SAFe has introduced AI-related modules in its RTE curriculum but has no standalone AI Scrum Master track. CSM and PSM have no AI content at all.
The opportunity for early certification holders is significant — employers searching for "AI Scrum Master" or "AI-ready agile practitioner" will find CREA-AI-SM holders at the top of the talent pool.
Get CREA-AI-SM First
Prerequisites: CREA-SM. 10 modules total. 80 questions. Globally recognised.
Register for CREA-AI-SM →