How to use AI

The ways in which AI is used at Tampere Universities can be broadly grouped into the following categories:

Read-made solutions – AI assistants

• Typical features: These tools do not make independent decisions or interact with back-end systems. They support users in understanding and producing texts.
• Based on: Summarising, generating and editing content.
• Examples:
  • drafting meeting minutes
  • multilingual translations
  • automatic retrieval of instructions
  • rewriting texts
  • such as: Microsoft Copilot (M365)

Lightweight agents

• Typical features: Chatbots with a clearly defined role that do not perform extensive multi-step workflows.
• Based on: A limited range of functions relating to a specific role or task, information retrieval, summarising. 
• Examples:
  • search and support chatbot
  • service and support agent
  • simple categorisation tasks
  • agent that proposes appropriate actions
  • course search agent
  • records management agent

Advanced agents and GenAI solutions

• Typical features: Multi-step process, several agents, complex context, multiple back-end systems.
• Based on: Decision-making, system prompts, instructions and workflows.
• Examples:
  • multi-stage service agent
  • project support agent
  • agent network supporting IT services

Traditional AI

The AI model often remains invisible to the user, as is the case with statistical models.

• Typical features: Non-generative, structured and data-driven tasks.
• Based on: Machine learning, document recognition, image recognition.
• Examples:
  • automated invoice recognition
  • anomaly forecasting
  • numerical data modelling
  • clustering of research data

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