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Blog Artikel
01.06.2026
2 min read

Microsoft 365 Copilot used responsibly – 5 tips from Baggenstos

Symbolic image: handshake between a white robotic hand and a human hand against a purple background.

Das Wichtigste in Kürze

  • 5 tips for an AI strategy: human-in-the-loop, transparency, data protection and security, bias reduction and employee training
  • The risk of shadow AI: employees may only use the official company AI, and model security must additionally be safeguarded against theft and manipulated inputs

Introducing artificial intelligence into an organisation is, first and foremost, an organisational challenge: using AI effectively and responsibly is a skill that needs to be learned. AI should work seamlessly alongside employees and deliver defined goals reliably – without causing unintended side effects.

«this must be governed and implemented within a clear AI strategy,»,

says Sven Heeb, Team Lead Project Manager.

He recommends that companies follow five key principles. In Baggenstos workshops, these are adapted to the specific conditions of each organisation.

Human-in-the-Loop

Clear accountability is essential: decisions are made by people, not by AI. Systems must be continuously monitored and fine-tuned. If they fail or deliver incorrect results, a human must always be able to step in and override the AI.

Transparency

The purpose of the AI must be clearly defined and communicated. All employees should understand what the AI does, what data it uses, and which decisions it makes. An AI policy is needed to regulate its use and set boundaries.

Data Protection and Security

With Microsoft 365 Copilot and web search disabled, the legal framework is straightforward: the AI only uses data stored within the company context. Nevertheless, organisations must carefully consider which data the AI should not process and put appropriate safeguards in place. Access to training data and models must be restricted, and highly sensitive data must never be exposed via AI. Unauthorised “shadow AI” poses a major risk, so employees should only use the company’s official AI. In addition, model security must be strengthened – protecting against model theft and adversarial inputs.

Detecting and Minimising Bias

An AI is only as good as the data it is trained on – and that data may contain bias, such as systematic distortions, prejudice, or discriminatory patterns that can lead to ethical challenges. Train AI on balanced datasets and regularly check outputs for bias. Discriminatory or manipulative AI applications must be explicitly prohibited by the company’s AI policy.

Training Employees and Raising AI Awareness

Employees must be made aware of both the potential and the limitations of AI. Only those who understand how systems work can use them effectively and ethically. AI competence needs to be embedded within the organisation and actively promoted by senior leadership.

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Zwei Mitarbeiter im Gespräch am Tisch, einer lächelt im Vordergrund

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