Why version control is the basis for safe AI use and reliable decision-making

Why version control is more important than ever

Large amounts of documents circulate daily in every organization: policies, reports, forms, and technical descriptions that are constantly changing and used by multiple employees. Without proper version control, situations quickly arise where employees work with different versions of the same document, AI tools provide answers based on outdated information, and audits fail because it's not clear which version was valid. Processes can also backfire due to confusion about the current status of documents.

Clearly, version control is essential. Without a firm grip on file versions, control over quality, reliability, and consistency is lacking. A modern information management platform mitigates these risks by centrally organizing and automatically managing versions.

What good version management really means

Version control is much more than just saving new files. It is about control, transparency, and trust in information.

1. Checking in and out files

Employees can ‘check out’ a document to work on it. Others then see that the document is in use, or ‘locked’, and cannot edit and overwrite it at the same time. When the work is finished, the document is ‘checked in’ again and a new version is automatically created for others to view and, if necessary, modify.

2. Distinction between ‘latest version’ and ‘current version’

Not every new version of a document is immediately the official, valid version. Therefore, an information management platform distinguishes between:

• the latest version (the most recent change)
• the current version (the version used in processes and formally valid)

This prevents an untested or unconfirmed update from accidentally being used by the organization or by AI.

3. Understanding the full history

Every change is automatically logged:

• Who made what change?
• When did it happen?
• What exactly was changed?
• What was the reason for the change?
• Was the change approved?

As you can see, using automatic logging creates a complete audit trail.

4. Approval workflows

For important documents – such as policies, protocols, or manuals – version control is often linked to a specific workflow, dictating that new versions become current only after:

• Content experts have reviewed the update
• Compliance or legal teams have approved the new version
• Incorrect or incomplete changes have been reversed

5. Controlled publishing

The platform ensures that only the correct, up-to-date version is available to employees, customers, supply chain partners, and AI systems anytime, anywhere.

Why version control is crucial for AI

AI systems are increasingly taking on a role in information processing: they answer policy questions, support customer contact, or provide advice based on legal and technical documents. If these systems have access to old versions, they can easily draw wrong conclusions. Then, erroneous answers, wrong decisions, or reputational damage are real risks.

Version control prevents AI from using outdated information as a source. Only current versions are used for analysis and processing, while older versions are securely archived for reference or accountability.

Protection through proper version control

An organization with controlled version management prevents errors in processes, increases quality of service, and meets audits and compliance requirements more easily. Employees and AI work with reliable and up-to-date information. This limits risks in customer contact, legal proceedings, and public communication.

The Canada case – in which a government chatbot incorrectly informed citizens based on outdated policies – shows how a lack of version control can have severe consequences.

Version control as part of integrated information management

Version control works best in conjunction with other aspects of information management. For example classification, so that the system knows what type of document it is and which workflow applies to it. Protection and security also play a role, ensuring that draft versions are not accidentally made available to users or AI. Retention policies help to retain only relevant versions and securely delete outdated ones. And by anonymizing, you ensure that older versions also comply with privacy rules.

Together, these elements provide a solid foundation for reliable and future-proof information assurance.

Version management is the key to reliability

Version management is not a luxury, but a basic requirement. It enables correct decision-making, ensures secure deployment of AI, supports stable processes, and helps comply with laws and regulations. Moreover, it promotes consistent communication and strengthens trust, both internally and externally.

A modern information management platform keeps information current, reliable, secure and fully auditable – exactly what is needed in today's digital reality.