Campus-Management

EU AI Act from 2 August 2026: What Universities Need to Know

Claudia

From 2 August 2026, further key provisions of the EU AI Act apply. Does this affect us as a university? Do we now need to have our AI tools reviewed? What happens if we do nothing? The short answer: it very much depends on what you do with AI. The longer answer is here.

Lecturer and student looking at digital AI icons with EU map in the background – EU AI Act and universities
Illustration: AI-generated image (Dr. Maex / TraiNex) – EU AI Act and universities in the digital age

What Applies from 2 August 2026?

Anyone who interacts with an AI system must in principle be able to recognise that they are dealing with AI. A chatbot for students or a digital assistant should therefore identify itself clearly as an AI system at the latest at the beginning of the conversation – unless this is already obvious.

For universities, this means above all:

  • Clearly label AI chatbots,
  • Do not present AI-generated media as authentic recordings,
  • Define responsibilities for AI systems in use,
  • Document AI deployment in a traceable manner.

AI Literacy Remains Mandatory

Since February 2025, institutions have been required to offer measures to promote the AI competence of their staff. From August 2026, compliance with this obligation can be more strictly monitored.

A specific certificate is not required. However, the following are advisable:

  • Internal rules for ChatGPT and other AI tools,
  • Training on data protection, hallucinations and confidential data,
  • Special briefings for sensitive areas such as the examinations office, admissions and HR,
  • Documentation of the measures offered.
  • TraiNex supports you with the e-tutorial “AI at the University in 10 Chapters”. You can store this directly in TraiNex for teaching staff and administrative employees, have them complete it and automatically document the evidence. Contact us.

Are Students Affected?

When using generally available AI tools privately, students are normally neither providers nor operators within the meaning of the AI Act. They are, however, protected as data subjects. If a university uses AI for admissions, examination assessment or examination monitoring, obligations arise for the university.

What Applies to Teaching Staff?

Teaching staff are likewise neither providers nor operators within the meaning of the AI Act. However, they must comply with the university’s requirements, data protection law, copyright law and examination regulations. In order to assess the use of AI in these areas, participation in further training is necessary.

How TraiNex Classifies AI Functions

At TraiNex, we assess every AI function based on its specific purpose and impact.

AI-supported search functions, text suggestions, summaries and general chatbots assist users without themselves making decisions about admissions, grades or sanctions. These risk classes are largely permitted without issue.

The picture may look different when an AI result is used directly for consequential decisions. An automatic evaluation of attendance data, for example, is to be assessed differently if examination eligibility is derived from it without further review.

That is why we specifically examine:

  • Purpose and data used,
  • Impact on students and staff,
  • Degree of automation,
  • Human control options,
  • Logging and traceability,
  • Data protection and IT security.

What Applies to AI Agents?

AI agents do not form a separate risk category in the AI Act. Here too, what matters is which tasks they take on.

An agent that prepares documents, transfers information or proposes changes for approval is to be assessed differently from an agent that independently rejects admissions, changes grades or sanctions individuals. The latter would be too autonomous and too risky under the AI Act. To achieve an acceptable and permitted risk class, at minimum human approval would be mandatory.

At TraiNex AI agents, we therefore rely on:

  • clearly defined areas of responsibility,
  • graduated access rights,
  • complete logging,
  • human approvals for consequential actions,
  • the ability to stop or reverse actions,
  • restriction of AI autonomy.
    See waas.campus-management-system.de

What Universities Should Do Now

Universities and educational institutions should now:

  1. Record the AI systems they use,
  2. Document their specific purposes of use,
  3. Correctly label AI chatbots and generated content,
  4. Offer staff appropriate training and guidelines,
  5. Particularly scrutinise applications that influence admissions, examinations or HR decisions.

Conclusion

From 2 August 2026, transparency, labelling and documented accountability will become more important for universities above all. Next milestone: the comprehensive high-risk requirements for the education sector apply from 2 December 2027.

AI Agents in Campus Management: Autonomous Digital Employees?

Claudia

AI agents are more than just smart chatbots. In May 2026, the Hochschulforum Digitalisierung published a widely discussed paper on “Agentic AI in the Higher Education System” — and it hits on what many university administrators already sense: the next wave of AI integration is not about interactively answering questions in a chat, but about goal-oriented execution of tasks using available tools. Predefined AI workflows are helpful here, but even without them, the agent searches for a solution, monitors states, acts autonomously, and triggers actions in campus management. This will affect administrative processes more than students directly. What does this mean for campus management?

AI agents and humans working together as a team with TraiNex
AI agents in campus management — click to enlarge

Chatbot vs. Agent: A Fundamental Difference

A chatbot responds. An AI assistant follows a workflow. And an AI agent? An AI agent acts. That sounds simple, but it is the crucial difference. While a chatbot reacts to a question and then waits, an AI agent can receive a task, independently plan and execute multiple steps — and in doing so, access data, systems, tools, and other agents. It operates essentially like an employee.

Concretely: A chatbot says “Your exam registration deadline is March 15.” An AI agent independently checks whether all prerequisites are met, enters the registration, sends a confirmation, and notifies the examination office — without a human having to trigger each step.

What Does This Mean for Campus Management?

In university operations, there are many processes that still run manually or semi-automatically today — processes that are perfectly suited for AI agents:

  • Exam registration with prerequisite checking: The agent independently verifies whether participation requirements are met, and automatically registers the student — or escalates borderline cases to a human administrator.
  • Document management: Incoming applications are classified, routed, and — where possible — directly processed, before a human provides final approval.
  • Timetable optimization: Based on room availability, lecturer schedules, and student numbers, the agent generates planning proposals or directly reassigns rooms.
  • Student support tasks: Early warning system for declining attendance or impending exam failures — including automatic notification to programme directors.
  • FAQ and service communication: Frequently asked questions are answered fully and in context, without tying up secretariat capacity.
  • Programme setup: Module handbooks are reviewed and transferred into campus management including schedules and lecturers, who are informed and contacted as needed.
  • General press monitoring: Search for interesting topics for our social media presence, send us 3 proposals each week and draft text and image for Instagram — posting after approval.

Crucially: the agent acts within clearly defined boundaries and with human oversight. It is not merely a responder or assistant — the agent is a decision-maker. And every decision must be traceable after the fact (Explainable AI).

TraiNex and AI Agents: WAAS — Workforce as a Service

At TraiNex, we are developing this approach further under the concept of WAAS — Workforce as a Service. The idea: AI agents receive onboarding, a workplace, computer and email address, as well as a TraiNex account with assigned permissions. The TraiNex AI agent takes on defined task packages in campus management, acting in its own name on behalf of the institution — documented, traceable, and compliant.

Initial real-world tests have been very successful. TraiNex AI agents respond to emails, read attachments, enter data, or check lists — typically overnight, either automatically or on demand. The TraiNex AI agents know TraiNex’s functions inside and out. There is a team of AI agents guided by an AI team leader, who also assigns tasks to humans when necessary — for example, to make a phone call. Curious? More at waas.ki-campus.eu

Conclusion

AI agents are no longer a science-fiction concept. They will fundamentally transform campus management systems in the coming months — as digital employees who initially take over routine tasks. Universities that engage with this now and test legally compliant use cases will be well positioned in the competition.

→ Full paper by Hochschulforum Digitalisierung (PDF)