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IT Support AI Alumni Course

Course description

This course effectively integrates AI tools into IT support processes. Learners will develop proficiency in using AI assistance throughout the incident management lifecycle, from initial triage to final documentation. Emphasis is placed on the ethical and responsible use of AI, including verifying AI suggestions, ensuring data privacy, and maintaining high standards of customer support. Practical scenarios and role-plays ensure learners can apply AI-supported workflows confidently and responsibly.

Tools you will explore

  • ChatGPT
  • Chatbase
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Modules

➤ Introducing: Artificial Intelligence in the IT World (0.5 hours)

  • Understand the basics of artificial intelligence and its key concepts
  • Distinguish between the different types of artificial intelligence, such as chatbots and agentic AI
  • Test previous knowledge of AI concepts to identify knowledge gaps

➤ Analytical Thinking & Productivity in the Age of AI (~0.75 hours)

  • Understand the structure of the analytical thinking process
  • Identify how AI can be used at various stages of the analytical thinking process
  • Understand the use of AI in IT roles to increase productivity
  • Evaluate the appropriateness of AI tools for solving specific problems

➤ Communicating with AI (~0.75 hours)

  • Recognise the limitations and risks of AI use in professional settings
  • Evaluate examples of ethical vs non-ethical use of AI in professional settings
  • Explore different approaches to prompting to communicate effectively with AI
  • Practise drafting a README file with the help of AI

➤ Receive and Triage (~1.5 hours)

  • Identify how AI tools can capture incidents from various channels (phone, email, chat, social media)
  • Categorize and prioritize tickets based on impact/urgency
  • Simulate AI-powered triage by adjusting AI-generated classifications
  • Compare AI vs. manual triage to recognize strengths and limitations

➤ Authenticate the Customer (~1.25 hours)

  • Understand company policy and procedures to verify customer identity/account
  • Practice building AI prompts or guidelines to confirm identity without exposing personal info
  • Explore how to handle potential compliance/privacy concerns with AI

➤ Diagnose the Incident (~1.5 hours)

  • Ask open‐ended, probing questions to discover root causes
  • Compare current incident with known issues in the Knowledge Base (KB) or Known Error Database
  • (KeDB)
  • Practice refining AI prompts to ensure correct/complete diagnostic suggestions

➤ Troubleshot and Resolve (~1.5 hours)

  • Develop a systematic troubleshooting approach, leveraging AI to suggest likely causes/fixes
  • Decide on the best solution to rectify the problem
  • Know when and how to escalate or transfer incidents that require advanced help

➤ Close the Incident (~1 hour)

  • Follow through with the customer to confirm the fix worked and they are satisfied
  • Summarize the final resolution clearly
  • Know best practices for verifying resolution before formally closing the incident

➤ Document the Incident (~1 hour)

  • Record relevant notes, resolution steps, and references to knowledge base articles with the help of AI
  • Use AI to summarize or rephrase complex notes, ensuring accuracy and clarity
  • Understand how thorough documentation aids future first‐call resolution

➤ Real-world Practice and Reflection (~1.25 hours)

  • Apply all six ticket management steps in a real-world scenario
  • Demonstrate how and when AI is used at each step
  • Reflect on how AI affected efficiency, accuracy, and customer satisfaction
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