Data Governance in ITIL v5 Explained

Data Governance is one of the concepts formally elevated in ITIL v5 — while data-related concerns existed conceptually in earlier versions, v5 names and defines it explicitly as an area of focus tied to the growing role of data (and by extension, AI) in modern digital products and services.

Data Governance is the system of decision rights and accountabilities for an organisation's data assets — determining who can take what action, with which data, under what circumstances, and using what methods. It covers the full lifecycle of data: how it is created, stored, used, shared, and eventually retired.

A useful way to separate Data Governance from adjacent concepts: Data Governance is about the rules and accountability structure surrounding data — who owns it, who can access it, what quality standards it must meet. Information Security is about protecting that data from unauthorised access or harm. The two overlap and depend on each other, but Data Governance is broader — it also covers things like data quality, ownership, and usability that have nothing to do with security specifically.

This topic has become especially relevant because AI systems are only as good as the data feeding them — the Curation capability in the AI Capability Model depends directly on strong Data Governance being in place. Poor data governance leads directly to poor AI outcomes, which is part of why v5 elevated this topic alongside the AI content.

For exam purposes, expect scenario questions that describe a data-related problem — inconsistent data quality across departments, unclear ownership of a dataset, unauthorised use of customer data for a new purpose — and ask which practice or concept is responsible for addressing it. If the scenario is about the rules, ownership, and accountability for data itself, the answer points to Data Governance; if it's specifically about protecting data from a security threat, it points toward Information Security Management instead.