Why a new version

Version 4 of the syllabus, from July 2026, explained Scrum as we knew it: the cycle, its roles, artifacts and events, and the principles and values that support them. That framework still holds. What has changed is the setting in which most teams now work.

Since 2022, generative AI has entered almost every knowledge job, and since 2024 agents that carry out complete tasks have spread. DORA's 2025 report, with about 5,000 software professionals, put AI use at 90% and concluded that it acts as an amplifier: it accelerates teams with good practices and worsens the problems of those with fragile processes. And the feeling of going faster is not always real: in a METR experimental study from 2025, expert developers took 19% longer with AI while believing they had gone 20% faster.

The mechanisms that let you see early what is happening and correct it in time are precisely those of Scrum. That is why this version does not replace the framework. It goes through all of it, asking what changes with AI and what stays the same.

What is new

The syllabus keeps its architecture and goes from two parts to three, with shorter and more focused chapters.

• Introduction: agility, the Agile Manifesto and its twelve principles, the origin of Scrum and, as a novelty, AI in knowledge work and what changes and what remains.
• Part I, the Scrum cycle: a chapter per role, artifact and event, with new topics such as empiricism, the Scrum Team and AI, the Definition of Done, the Definition of Ready and planning with AI in the team.
• Part II, principles and values: the eight principles and the six values, each with what AI changes in its application, people over roles, and work methods for quality.
• Part III, new, the craft of the Scrum Master in teams with AI: facilitating the work system between people and AI, the AI working agreements, AI literacy, quality versus workslop, new impediments, people's learning, psychological safety, antipatterns, and Scrum with AI outside software.
• A glossary in the appendix.

The examples no longer come only from software development: there are teams in marketing, human resources, legal advice, education or operations. Some sections include a box marked Consolidating trend or Emerging trend: they report practices that are not yet general and do not form part of the assessment.

The version also includes the content of the skill "Scrum in Teams with AI", which will no longer be offered as an independent skill.

Three ideas the new version puts in the spotlight

The bottleneck shifts. Throughout the history of agile management, the narrow point of the work has been execution. When execution becomes cheaper, the bottleneck moves to deciding what deserves to be done, reviewing what has been produced, and validating that it solves a real problem. A marketing team can generate twenty variants of a campaign in an afternoon, but someone has to choose which ones fit the brand. That is why review is planned as work, and the capacity to review sets a limit on the pace.

AI is a team capability, not a member. It expands what the team can do, like any powerful tool, but it does not hold a role or answer for anything. The Product Owner, the Scrum Master and the developers are always people, and they answer for the result, whoever or whatever produced it. How AI is integrated into the work is part of the team's self-management, which decides it explicitly and reviews it in the Sprint Retrospective.

Looking finished is not being finished. AI easily produces well-written reports or code that works on a first test. Work that looks good but does not move the task forward has been called workslop, and its cost is paid not by who produces it but by who receives it. Prevention uses practices we already know: a Definition of Done that requires human review, acceptance criteria with examples, and visible provenance of the work.

Who it is for and what it certifies

It is the update exam for those who already hold the Scrum Master certification from Scrum Manager and want to keep it current: Scrum Masters, Product Owners, team leads and any professional who works with Scrum, in software or outside it. Aspects that the syllabus only summarizes are developed in other Scrum Manager syllabi: the craft of deciding what to build, in Product Owner, and the fundamentals of agile management in the AI era, in Agile Bedrock. For the practical use of AI in any agile role, there is the skill AI Applied to Agile Work.

The update diploma certifies that its holder keeps current and up to date their command of agile management with Scrum: agility and the Agile Manifesto, the Scrum cycle and empiricism, artifacts and events, progress measurement and estimation, the principles and values of Scrum, and the craft of the Scrum Master in teams working with artificial intelligence. The training and assessment question banks have been fully regenerated from the new syllabus, at two difficulty levels.

The new version is available in Spanish and in English.

How to access it

The syllabus and the training and assessment platform are on the topic page on Skill Arena: Scrum Master.

Read, train and tell us what you think. Every contribution, criticism or suggestion helps us prepare the next version.