I add AI skills to a resume only when I can explain the tool, task, judgment, and result. Writing “AI expert” after occasional chatbot use creates more questions than credibility.
I name the actual capability
I distinguish prompt design, workflow automation, data labeling, model evaluation, coding assistance, content review, or a specific platform. I use product names only when relevant and current.
I place the skill inside work evidence
Instead of listing “Generative AI,” I might write: “Built a reviewed AI-assisted workflow to categorize customer feedback, reducing weekly manual sorting time while requiring human approval for final themes.”
I explain safeguards where they matter
I mention verification, privacy, quality checks, or human review when those controls were part of responsible implementation. This shows judgment beyond tool access.
I avoid inflated proficiency labels
I do not rate myself as advanced without a meaningful standard. I describe what I have built, tested, or improved and allow the evidence to show depth.
I keep the skill current
Tools change quickly. I review whether the named platform and workflow still represent my ability and whether the role actually values them.
Examples of honest phrasing
- Designed reusable prompts and review criteria for first-draft support documentation.
- Used Python and an LLM API to classify non-sensitive survey comments, with manual validation.
- Created an AI-assisted research workflow that required source verification before publication.
- Trained teammates on safe use rules for approved generative AI tools.
I want an interviewer to be able to ask “How did that work?” and receive a concrete answer. That is the standard I use before adding any AI claim.