Using AI to Boost Productivity
Where AI helps
Drafting replies and documentation, summarizing long tickets or logs, brainstorming causes, explaining error messages, generating command lines or scripts to review, and translating jargon for users. Speed comes from iteration, not from one perfect prompt.
Prompting that works
Give role, context, task, constraints, and output format. For example: 'You are a help-desk technician. A Windows 11 user gets error 0x80070005 while installing an app. List the three most likely causes, a check for each, and a one-line user-facing explanation. Avoid registry edits.' Add examples when format matters, and ask the model to state its assumptions.
Verify, verify
AI can hallucinate confidently. Treat output as a draft from a knowledgeable but unverified colleague: check commands before running them, confirm facts in official documentation, and test in a safe environment.
Data and ethics
Never paste credentials, personal data, or confidential company data into tools you are not authorized to use. Respect licensing and disclosure rules, and keep a human in the loop for decisions affecting people, such as hiring, discipline, or security incidents. Disclose AI use where required.
Traps
- Running generated commands without review.
- Trusting a confident but wrong answer.
- Feeding customer data into a public chatbot.
- Assuming the AI has live access to your systems.
- Using AI as the only source for a security decision.
Rule of thumb
Use AI to draft and summarize, not to authorize. Nothing generated should reach a user or a production system until a human has checked it.