AI is a tool — one of many available for solving problems. Using it thoughtfully means starting with the problem, not the technology.
Identify the Actual Problem First
Before choosing AI, define the problem you are trying to solve. Ask:
- What specific outcome do I need?
- What information or process is currently inadequate?
- How will I know if the solution is working?
A clearly defined problem makes it easier to evaluate whether AI is the right tool — or whether a simpler approach would work better.
Could a Simpler Tool Solve This?
Before reaching for AI, consider whether the problem can be solved with:
- A spreadsheet formula or filter
- A database query
- A clearer process or checklist
- Better documentation
- A conversation with the right person
The simplest reliable approach that solves the actual problem is usually the best one. Complexity adds cost, maintenance burden, and new failure modes.
Low-Risk and Higher-Risk Uses
Not all AI uses carry the same risk. Lower-risk uses include drafting text that will be reviewed, brainstorming ideas, summarizing documents for internal use, and explaining concepts. Higher-risk uses include decisions affecting individuals (hiring, benefits, services), medical or legal advice, public communications, and any use where errors could cause significant harm.
Validating Outputs
For any AI output that will be acted upon:
- Verify factual claims independently
- Have a qualified person review outputs in specialized domains
- Test the output against known examples before relying on it
Protecting Information
Apply data minimization principles. Share only what is necessary. Do not use external AI services to process personal or confidential information without appropriate authorization and privacy assessment.
Documenting Material Uses
When AI is used in ways that affect decisions, services, or communications, document what system was used, what it was used for, and how outputs were reviewed. This supports accountability and auditability. Related learning: Audit Trail, Data Governance 101.
Starting Small and Reversibly
When exploring AI for a new use case, start with a small, low-stakes experiment. Evaluate the results before expanding. Make it easy to stop or reverse if the approach does not work.
Use the simplest reliable approach that solves the actual problem. AI is one possible tool, not the automatic answer to every problem.
You now understand what AI is, how machine learning and generative AI work, how LLMs differ from search engines, how to prompt effectively, why errors occur, and how to use AI responsibly. Continue with the AI Learning Centre or explore the AI Glossary.
- responsible AI use guidelines
- AI risk assessment
- when to use AI
- AI governance framework
- AI policy for organizations