PSM-AI — Scrum.org Professional Scrum Master - AI Essentials Study Plan
A practical 7, 14, 30, and 60/90-day PSM-AI study plan for Scrum.org Professional Scrum Master - AI Essentials candidates.
How to use this Study Plan
This Study Plan is for candidates preparing for the Scrum.org Professional Scrum Master - AI Essentials (PSM-AI) exam from Scrum.org. It assumes you need more than definitions: you need to make sound Scrum Master decisions in AI-related situations, where the best answer protects empiricism, accountability, transparency, value delivery, and responsible use of AI.
Use the plan that matches your remaining time. If you are already strong in Scrum but weaker in AI application, spend more time on AI scenarios. If you are new to Scrum.org-style questions, spend more time on the Scrum foundation and explanation review.
Which plan should you use?
| Time available | Use this path if | Main goal | Main risk to manage |
|---|---|---|---|
| 7 days | Your exam is scheduled soon or you need final review | Close gaps, rehearse timing, avoid new overload | Learning too much new material too late |
| 14 days | You know Scrum basics but need structured PSM-AI practice | Build scenario judgment quickly | Skipping explanation review |
| 30 days | You want a balanced plan with room for diagnostics and mocks | Learn, practice, review, and stabilize | Staying in passive reading too long |
| 60/90 days | You are starting early or rebuilding Scrum and AI foundations | Develop durable understanding and exam confidence | Spreading study too thin |
What PSM-AI preparation should emphasize
For PSM-AI, do not study AI as a generic technology topic only. Study how AI affects Scrum Master work, Scrum Team support, stakeholder interaction, facilitation, learning, transparency, and risk management.
Prioritize these areas:
| Area | What to know | What to practice |
|---|---|---|
| Scrum foundation | Accountabilities, events, artifacts, commitments, empiricism, Scrum Values, Definition of Done | Scenario questions where the wrong answer sounds efficient but weakens Scrum |
| Scrum Master stance | Coaching, facilitation, impediment removal, self-management, service to the Scrum Team and organization | Choosing actions that improve transparency and team ownership |
| AI use in Scrum | AI as a support tool for analysis, drafting, summarizing, learning, and pattern recognition | Deciding when AI helps and when human judgment is required |
| Responsible AI | Privacy, security, bias, hallucination, policy constraints, transparency, verification | Identifying unsafe or overconfident AI use |
| Events and artifacts | Sprint Planning, Daily Scrum, Sprint Review, Sprint Retrospective, Product Backlog, Sprint Backlog, Increment | Applying AI without changing the purpose of Scrum events |
| Value and outcomes | Product Goal, Sprint Goal, stakeholder feedback, evidence-based adaptation | Using AI to support decisions without replacing inspection and adaptation |
| Hybrid or governed environments | Organizational controls, compliance, reporting, portfolio oversight | Protecting Scrum empiricism while satisfying valid governance needs |
Daily practice rhythm
Use this rhythm on most study days. Shorten or expand the time blocks based on your schedule.
| Block | 45-minute day | 90-minute day | 2-hour day |
|---|---|---|---|
| Recall warm-up | 5 min | 10 min | 10 min |
| Focused concept review | 10 min | 20 min | 25 min |
| Scenario practice | 20 min | 35 min | 50 min |
| AI-in-Scrum application drill | 5 min | 15 min | 20 min |
| Missed-question review | 5 min | 10 min | 15 min |
Daily checklist
Every study session should produce one useful artifact:
- A corrected missed-question log entry.
- A short rule such as “AI may summarize stakeholder feedback, but the Scrum Team still inspects and adapts.”
- A list of confused terms to revisit.
- A scenario pattern you can recognize faster next time.
- A timing note from a practice set.
If a study session ends with only reading and no practice, add at least 5 scenario questions before stopping.
Baseline diagnostic before choosing topics
Before starting a 14-day, 30-day, or 60/90-day path, run a diagnostic.
- Take a mixed practice set under a firm time limit.
- Do not pause to look up answers.
- Mark every question as:
- Confident
- Narrowed to two
- Guessed
- Review explanations before studying new material.
- Build your first gap list.
Diagnostic interpretation
| Result pattern | What it usually means | What to do next |
|---|---|---|
| You miss Scrum accountabilities and event purposes | Foundation is not stable enough | Review Scrum fundamentals before heavy AI practice |
| You choose AI automation too often | You may be replacing Scrum accountability with tooling | Practice responsible AI and human judgment scenarios |
| You miss questions involving transparency or inspection | Empiricism needs reinforcement | Review artifacts, commitments, Done, and evidence-based decisions |
| You miss stakeholder or governance questions | You may be treating Scrum as isolated from the organization | Practice stakeholder, risk, policy, and compliance scenarios |
| You know the concept but miss wording | You need slower reading and answer elimination | Review why each wrong option is wrong |
| Scores fluctuate widely | Knowledge is fragmented | Use smaller topic sets before full mocks |
7-day final review plan
Use this if your PSM-AI exam is within one week. The goal is not to learn everything. The goal is to stabilize judgment, remove common errors, and protect your final review time.
| Day | Main focus | Practice task | Review output |
|---|---|---|---|
| 7 | Diagnostic and gap map | Take one mixed timed practice set | Top 5 weak areas |
| 6 | Scrum foundation repair | Practice accountabilities, events, artifacts, commitments | One-page Scrum rules sheet |
| 5 | AI use cases in Scrum | Practice AI assistance scenarios across Scrum events | “AI can help / AI must not replace” list |
| 4 | Responsible AI risks | Practice privacy, security, bias, hallucination, policy, transparency | Risk-response table |
| 3 | Mixed scenario judgment | Take a larger timed mixed set | Missed-question log update |
| 2 | Final mock or timed rehearsal | Take one timed mock or two shorter timed sets | Last gap list only |
| 1 | Light review only | Review notes, wrong-answer patterns, exam logistics | Stop adding new material |
7-day rules
- Stop broad new learning by the end of Day 3.
- On Day 2, practice timing and decision discipline.
- On Day 1, review only your own notes, missed-question patterns, and core Scrum/AI principles.
- Do not spend the final day debating obscure topics unless they are repeatedly missed in practice.
- Sleep and pacing matter more than one more long question set.
14-day focused plan
Use this if you have two weeks and can study most days. This path is best for candidates who know Scrum basics but need stronger AI-related exam judgment.
Week 1: rebuild the base and identify gaps
| Day | Study focus | Practice focus |
|---|---|---|
| 1 | Baseline diagnostic | Mixed practice set and gap tagging |
| 2 | Scrum accountabilities | Questions on Scrum Master, Product Owner, Developers, self-management |
| 3 | Events and artifacts | Sprint Planning, Daily Scrum, Sprint Review, Retrospective, Product Backlog, Sprint Backlog, Increment |
| 4 | Empiricism and Scrum Values | Transparency, inspection, adaptation, commitment, focus, openness, respect, courage |
| 5 | AI fundamentals for Scrum Masters | AI capabilities, limitations, verification, human accountability |
| 6 | Responsible AI | Privacy, security, bias, hallucination, organizational policy, stakeholder transparency |
| 7 | Mixed review | Timed mixed set and explanation review |
Week 2: scenario judgment and exam readiness
| Day | Study focus | Practice focus |
|---|---|---|
| 8 | AI in Sprint Planning and refinement | AI-assisted analysis, forecasting support, backlog clarity, goal alignment |
| 9 | AI in Daily Scrum and delivery | Transparency, impediments, team ownership, avoiding surveillance misuse |
| 10 | AI in Sprint Review and stakeholder feedback | Summaries, insights, product decisions, evidence over opinion |
| 11 | AI in Retrospectives and team learning | Facilitation support, psychological safety, improvement experiments |
| 12 | Governance, risk, and change | Policy constraints, compliance needs, hybrid environments, responsible adoption |
| 13 | Timed mock | Full timed rehearsal using your practice tool’s limits |
| 14 | Final explanation review | Review missed questions, rules sheet, and pacing strategy |
14-day checkpoint
By the end of Day 10, you should be able to explain:
- Why AI does not own Scrum accountabilities.
- Why AI output must be inspected before use.
- How AI can support transparency without becoming surveillance.
- How a Scrum Master should respond when AI use creates risk, confusion, or false certainty.
- Why Scrum events retain their purposes even when AI tools are introduced.
30-day balanced plan
Use this if you want a complete but efficient schedule. This is the best default path for most candidates preparing for Scrum.org Professional Scrum Master - AI Essentials (PSM-AI).
30-day overview
| Week | Goal | Main activities | End-of-week check |
|---|---|---|---|
| 1 | Establish Scrum and diagnostic baseline | Scrum foundation review, baseline practice, gap log | Can explain events, artifacts, accountabilities without notes |
| 2 | Build AI-in-Scrum understanding | Responsible AI, AI support patterns, limitations, verification | Can choose safe AI use in Scrum scenarios |
| 3 | Convert knowledge into scenario judgment | Mixed practice, stakeholder/risk/change scenarios, timed sets | Missed questions are mostly narrow, not foundational |
| 4 | Mock, repair, and finalize | Timed mocks, explanation review, final notes | Stable performance and clear pacing strategy |
Week 1: Scrum foundation and diagnostic
| Day | Focus | Task |
|---|---|---|
| 1 | Baseline diagnostic | Mixed set, timed, no notes |
| 2 | Scrum accountabilities | Review who is accountable for what; practice role-confusion questions |
| 3 | Events | Review event purposes, participants, outcomes, and anti-patterns |
| 4 | Artifacts and commitments | Product Backlog/Product Goal, Sprint Backlog/Sprint Goal, Increment/Definition of Done |
| 5 | Empiricism | Practice transparency, inspection, adaptation scenarios |
| 6 | Scrum Values and team behavior | Practice coaching and facilitation questions |
| 7 | Weekly review | Retake weak topics, update missed-question log |
Week 2: AI essentials in the Scrum Master context
| Day | Focus | Task |
|---|---|---|
| 8 | AI capabilities and limits | Identify what AI can draft, summarize, analyze, or suggest |
| 9 | Human accountability | Practice questions where AI output tempts the team to skip inspection |
| 10 | Prompting and verification | Practice writing clear prompts and checking outputs against Scrum intent |
| 11 | Privacy and security | Practice scenarios involving sensitive data, policies, and tool restrictions |
| 12 | Bias and hallucination | Practice detecting unsupported or misleading AI output |
| 13 | AI across Scrum events | Map useful and unsafe AI use in each event |
| 14 | Timed mixed set | Review explanations deeply |
Week 3: scenario judgment
| Day | Focus | Task |
|---|---|---|
| 15 | Sprint Planning scenarios | Goal, scope, capacity, Product Backlog clarity, AI-assisted analysis |
| 16 | Daily Scrum and delivery scenarios | Transparency, progress, impediments, team ownership |
| 17 | Sprint Review scenarios | Stakeholder feedback, evidence, product adaptation |
| 18 | Retrospective scenarios | Team improvement, safety, facilitation, AI-generated insights |
| 19 | Stakeholders, governance, and risk | Hybrid controls, reporting needs, policy constraints, change impact |
| 20 | Mixed timed practice | Practice pacing and answer elimination |
| 21 | Recovery and repair | Re-study only your weakest three tags |
Week 4: mock exams and final review
| Day | Focus | Task |
|---|---|---|
| 22 | Timed mock 1 | Take a full timed practice exam or equivalent set |
| 23 | Explanation review | Review every missed, guessed, and slow question |
| 24 | Targeted repair | Drill the two weakest topic areas |
| 25 | Timed mock 2 | Use different questions if available |
| 26 | Final knowledge sheet | Reduce notes to one or two pages |
| 27 | Final mixed set | Shorter timed set focused on accuracy |
| 28 | Stop broad new material | Review missed-question log and rules |
| 29 | Light final review | Read notes, rehearse pacing, rest |
| 30 | Exam day or final readiness day | Execute calmly; do not cram |
60/90-day full preparation path
Use this if you are starting early, returning to Scrum after time away, or want deeper confidence before the PSM-AI exam.
How to choose 60 vs. 90 days
| Path | Best for | Weekly study time | How to use it |
|---|---|---|---|
| 60 days | You know Scrum but need structure and AI practice | 4-6 hours | Use each phase once, with shorter reviews |
| 90 days | You are newer to Scrum.org exams or want deeper reinforcement | 3-5 hours | Stretch each phase and add more scenario practice |
Phase plan
| Phase | 60-day timing | 90-day timing | Goal |
|---|---|---|---|
| 1. Scrum foundation | Days 1-14 | Days 1-21 | Make Scrum terms, events, accountabilities, and empiricism automatic |
| 2. AI essentials | Days 15-28 | Days 22-42 | Understand responsible AI use in Scrum Master work |
| 3. Applied scenarios | Days 29-42 | Days 43-63 | Practice judgment across Scrum events, stakeholder issues, risks, and change |
| 4. Timed practice | Days 43-52 | Days 64-78 | Build speed and accuracy under exam-like constraints |
| 5. Final review | Days 53-60 | Days 79-90 | Repair weak areas and stop adding new material |
Phase 1: Scrum foundation
Focus on:
- Scrum accountabilities and boundaries.
- Event purpose and event anti-patterns.
- Artifact transparency and commitments.
- Definition of Done and Increment quality.
- Product Goal and Sprint Goal.
- Empiricism and Scrum Values.
- Scrum Master service to the Scrum Team, Product Owner, and organization.
Practice pattern:
| Study action | Frequency |
|---|---|
| Read/review Scrum concepts | 3 sessions per week |
| Scenario questions | 2-3 sessions per week |
| Missed-question review | Every practice session |
| Short recall quiz | Daily or near-daily |
Phase 2: AI essentials for PSM-AI
Focus on:
- AI as an assistant, not an accountable Scrum role.
- AI-generated summaries, drafts, insights, and suggestions.
- Verification of AI output before use.
- Privacy and sensitive information.
- Bias, hallucination, and unsupported conclusions.
- Transparency about AI use when it affects decisions or stakeholders.
- Organizational policy and governance constraints.
- Ethical and professional judgment.
Practice pattern:
| Scenario type | Example study question to ask yourself |
|---|---|
| AI output quality | What evidence would the Scrum Team need before using this output? |
| AI and accountability | Who remains accountable for the decision? |
| AI and transparency | Does this use of AI improve or reduce shared understanding? |
| AI and privacy | Is the data appropriate to enter into the tool? |
| AI and Scrum events | Does the AI use support the event purpose or distract from it? |
Phase 3: applied scenario judgment
Work through scenarios where several answers seem reasonable. Prioritize the answer that best preserves Scrum, responsible AI use, and empirical decision-making.
| Scenario theme | What strong answers usually protect |
|---|---|
| Sprint Planning with AI estimates or analysis | Team ownership, Sprint Goal, realistic planning, transparency |
| Daily Scrum with AI-generated progress reports | Developers’ inspection and adaptation, not status theater |
| Sprint Review with AI-summarized feedback | Stakeholder collaboration, evidence, product adaptation |
| Retrospective with AI-generated improvement ideas | Team safety, ownership, actionable experiments |
| Product Backlog analysis | Product Owner accountability, value focus, clear ordering rationale |
| Governance or compliance pressure | Valid constraints plus empirical Scrum delivery |
| Risk and change | Early transparency, inspection, adaptation, responsible escalation |
Phase 4: timed practice
Use timed practice after you have covered the major content. Timed mocks are most useful when you can review them carefully afterward.
| Timing milestone | What to do |
|---|---|
| First timed set | Take it to measure pacing, not to prove readiness |
| Mid-phase timed set | Compare errors with your earlier diagnostic |
| Final full mock | Simulate exam conditions as closely as your practice tool allows |
| Post-mock review | Spend at least as long reviewing as you spent answering |
Phase 5: final review
In the final phase:
- Stop collecting new resources.
- Reduce notes to recurring decision rules.
- Review every missed-question tag.
- Retake only weak areas and mixed sets.
- Rehearse pacing.
- Rest before exam day.
Missed-question review method
Do not just mark answers right or wrong. The value is in understanding why your reasoning failed.
Use a missed-question log
| Field | What to record |
|---|---|
| Date | When you missed it |
| Topic | Scrum foundation, AI risk, event purpose, accountability, stakeholder, governance, etc. |
| Question type | Definition, scenario, multi-step judgment, wording trap |
| Your error | Misread, guessed, over-automated, role confusion, ignored policy, weak Scrum concept |
| Correct principle | The rule that would have led to the right answer |
| Retest date | When you will practice the topic again |
Error tags and repair actions
| Error tag | What it means | Repair action |
|---|---|---|
| Accountability confusion | You assigned Product Owner, Developers, Scrum Master, or AI the wrong responsibility | Rebuild a one-page accountability map |
| Event purpose confusion | You chose an action that changes why a Scrum event exists | Review the purpose and outcome of each event |
| AI overreach | You let AI decide, commit, judge, or own work | Practice “AI assists; humans remain accountable” scenarios |
| Privacy or policy miss | You ignored sensitive data or organizational constraints | Create a checklist before using AI in scenarios |
| Hallucination or bias miss | You accepted AI output without verification | Practice evidence and validation questions |
| Governance overcorrection | You abandoned Scrum to satisfy reporting or control needs | Practice balancing governance with empiricism |
| Reading error | You missed words like “best,” “first,” “most appropriate,” or “should” | Slow down and eliminate answers deliberately |
What to practice next
Use this table after every practice set.
| If your latest practice shows… | Practice next |
|---|---|
| Low confidence on Scrum basics | Accountabilities, events, artifacts, commitments |
| Strong Scrum but weak AI judgment | AI risks, verification, privacy, transparency |
| You choose tool-based answers too often | Scrum Master stance and human accountability |
| You miss stakeholder scenarios | Sprint Review, feedback loops, value, governance |
| You miss risk or change scenarios | Transparency, inspection, adaptation, escalation |
| You run out of time | Short timed sets with strict review |
| You finish fast but miss easy questions | Slow reading and answer elimination |
| You miss the same tag repeatedly | Stop mixed practice and drill that topic |
When to use timed mock exams
Timed mocks are useful, but only after you have enough foundation to learn from them.
| Preparation stage | Mock use |
|---|---|
| First 20% of study time | Avoid full mocks unless doing a diagnostic |
| Middle of study plan | Use shorter timed sets to build pacing |
| Final third | Use full timed rehearsals or equivalent mixed sets |
| Last 48 hours | Avoid exhausting mock marathons; review explanations instead |
Mock exam review rules
After each mock:
- Review missed questions first.
- Review guessed questions even if correct.
- Review slow questions.
- Write one correction rule per recurring error.
- Re-practice the weakest topics within 48 hours.
- Do not take another mock until you have reviewed the previous one.
PSM-AI scenario judgment rules
Use these rules when two answers look plausible.
| Scenario clue | Prefer the answer that… |
|---|---|
| AI gives a confident recommendation | Verifies evidence and keeps humans accountable |
| A team wants AI to replace discussion | Preserves collaboration, transparency, and shared understanding |
| Stakeholders receive AI-generated output | Ensures accuracy, context, and appropriate transparency |
| Sensitive information is involved | Follows policy and protects privacy/security |
| A Scrum event is being automated | Keeps the event’s purpose intact |
| Management wants AI status reporting | Avoids surveillance and supports empirical transparency |
| The Product Backlog is analyzed by AI | Supports Product Owner accountability and value-based decisions |
| The team disagrees with AI output | Inspects the evidence and adapts based on learning |
| A hybrid or governed environment adds constraints | Meets valid constraints without weakening Scrum principles |
Safe use of AI while studying
AI tools can help you study, but use them carefully.
Good uses:
- Ask for scenario practice on a topic you are reviewing.
- Ask for alternative explanations of Scrum concepts.
- Generate examples of AI use in Sprint Planning, Sprint Review, or Retrospectives.
- Ask for a comparison between two plausible answers.
- Ask for flashcards from your own notes.
Avoid:
- Treating AI-generated explanations as authoritative without checking.
- Pasting confidential employer, client, or exam content into a tool.
- Memorizing AI-generated answer lists or unverified answers.
- Letting AI replace your own explanation practice.
- Learning terminology that conflicts with Scrum.org’s Scrum language.
A useful prompt format:
Create 5 PSM-AI-style practice scenarios about responsible AI use in Scrum.
For each scenario, provide four answer choices.
After I answer, explain why each option is right or wrong.
Focus on Scrum Master judgment, empiricism, accountability, and AI risk.
Final-week rules
In the final week, switch from learning mode to exam-readiness mode.
Do
- Review your missed-question log daily.
- Practice mixed questions under time pressure.
- Rehearse answer elimination.
- Review Scrum accountabilities, events, artifacts, commitments, and empiricism.
- Review AI risk themes: privacy, bias, hallucination, transparency, verification, and policy.
- Sleep normally and reduce late-night cramming.
Do not
- Add new study resources in the final 48 hours.
- Take repeated mocks without reviewing explanations.
- Memorize isolated wording without understanding the scenario.
- Assume AI is the best answer just because the exam involves AI.
- Replace Scrum principles with generic project-management habits.
Exam-readiness checks
You are likely ready when you can do most of the following without notes:
| Readiness check | Yes/No |
|---|---|
| I can explain each Scrum accountability and what it does not own. | |
| I can explain the purpose of each Scrum event. | |
| I can connect each artifact to its commitment. | |
| I can identify when AI supports transparency and when it reduces it. | |
| I can explain why AI output must be verified before use. | |
| I can handle privacy, security, policy, bias, and hallucination scenarios. | |
| I can answer mixed practice questions under time pressure. | |
| I can explain why my chosen answer is better than the second-best answer. | |
| I no longer miss the same topic repeatedly. | |
| I have a calm plan for pacing, review, and final submission. |
If several checks are still “No,” delay full mocks and spend one or two sessions repairing those areas.
Practical next step
Choose your timeline, take a baseline mixed practice set, and build a missed-question log before studying more content. For PSM-AI, the fastest improvement usually comes from reviewing explanations carefully and practicing scenarios where Scrum Master judgment and responsible AI use intersect.