Student Focus Prompt Pack

Purpose: This pack responds to the pre-workshop questionnaire. Students are already familiar with AI assistants, but they want more practical, ethical, industry-relevant examples of AI in HRM. Use these prompts during the workshop or as optional practice after the session.

Safety rule: Use only fictional organizations, fictional employees, fictional candidates, and synthetic data. Do not paste real CVs, student IDs, employee records, salary information, medical data, disciplinary data, or confidential university/company information.

How to use these prompts

1. Choose one fictional Sri Lankan organization from the scenario cards.
2. Copy one prompt.
3. Replace bracketed text such as [sector] or [role].
4. Review the AI output for accuracy, fairness, privacy, tone, and human oversight.
5. Improve the prompt and rerun it.
6. Record what changed and why.

Prompt 1 — Practical AI use map for HRM

Act as a Digital HRM advisor for undergraduate HRM students in Sri Lanka.

Create a practical AI use-case map for a fictional [sector] organization called [organization name].

Cover these HRM areas:
1. Recruitment
2. Onboarding
3. Learning and development
4. Employee engagement
5. Performance support
6. HR operations
7. People analytics

For each area, provide:
- One realistic AI use case
- A sample AI output
- A benefit for HR
- A benefit for employees or applicants
- One risk
- One human oversight point

Keep the examples suitable for a classroom workshop using synthetic data only.

Prompt 2 — Recruitment communication without bias

Act as a responsible HR communication specialist.

Draft a recruitment message for final-year university students in Sri Lanka applying for a fictional management trainee role at [organization name].

Requirements:
- Be inclusive and respectful
- Avoid unrealistic promises
- Avoid gender, region, language, or socioeconomic bias
- Encourage applicants from Colombo and outside Colombo
- Include eligibility, learning opportunities, application steps, and deadline
- Add a note that all applications will be reviewed using structured criteria

Then provide a short bias and fairness review of your own message.

Prompt 3 — Structured interview guide

Act as an HR selection specialist.

Create a structured interview guide for a fictional [role] in a Sri Lankan [sector] organization.

Include:
- 5 competencies
- 2 behavioral questions per competency
- A 1–5 scoring rubric
- Red flags that require human discussion, not automatic rejection
- Candidate-friendly explanation of the process
- A fairness note for interviewers

Do not include questions about protected or sensitive personal characteristics.

Prompt 4 — Onboarding message for human review

Act as an onboarding coordinator.

Write a warm first-day welcome message for new employees at a fictional Sri Lankan organization called [organization name].

Audience: [new management trainees / hotel staff / BPO associates / hospital admin staff]

Include:
- Welcome message
- First-day expectations
- Who to contact for help
- A reminder that AI tools may support learning but human HR support is available
- A respectful and inclusive tone

After the message, list 5 things HR should verify before sending it.

Prompt 5 — Employee engagement pulse survey summary

Act as a people analytics assistant.

I will paste synthetic pulse survey comments from a fictional Sri Lankan organization. Summarize them into themes.

Rules:
- Do not identify individuals
- Do not infer sensitive traits
- Do not overstate conclusions
- Separate evidence from interpretation
- Provide 3 recommended HR actions
- Provide 3 questions HR should ask before taking action

Synthetic comments:
[paste synthetic comments]

Prompt 6 — Performance feedback improvement

Act as an HR coach helping a manager write better performance feedback.

Improve the following rough manager note into constructive, evidence-based feedback.

Rules:
- Do not exaggerate
- Do not use personal attacks
- Keep the tone respectful
- Include observable behavior, impact, and next step
- Add a human manager conversation prompt
- Add a fairness check

Rough note:
[paste fictional note]

Prompt 7 — Learning path for AI-ready HR skills

Act as an HR learning designer.

Create a 4-week learning path for a fictional HR assistant in Sri Lanka who wants to become AI-ready.

Include:
- Weekly learning goals
- Practical activities
- AI tools to try
- Reflection questions
- Micro-assessment
- Responsible AI reminder

Focus on HRM students and early-career HR professionals, not software engineers.

Prompt 8 — Employer branding campaign

Act as an employer branding strategist.

Create a 5-post social media campaign for a fictional Sri Lankan [sector] organization hiring [role].

Platforms: LinkedIn and Instagram
Audience: final-year university students in Sri Lanka

For each post include:
- Post title
- Caption
- Visual concept
- Hashtags
- What makes it inclusive
- What claim should be avoided

End with a checklist for responsible employer branding.

Prompt 9 — Vibe-coding idea refinement

Act as a product designer for HRM students.

Help me turn this HR problem into a safe micro-app prototype.

HR problem: [describe problem]
Target user: [student / applicant / new employee / HR officer / manager]
Workshop context: classroom prototype using synthetic data only

First ask me 5 clarifying questions.
Then propose:
- App name
- User journey
- 3 safe features
- 3 features to exclude
- Data required
- Data prohibited
- Human support point
- Simple page structure
- Prompt I can use in a vibe-coding tool

Prompt 10 — AI media campaign with disclosure

Act as an HR creative director.

Design an AI-generated media campaign for a fictional Sri Lankan university career center.

Topic: AI skills for future HR professionals
Outputs:
1. Poster concept
2. 5-slide carousel outline
3. 30-second voiceover script
4. 45-second avatar video script
5. AI disclosure note

Constraints:
- Do not use real student faces or voices
- Avoid misleading claims
- Use inclusive language
- Make it suitable for university HRM students

Prompt 11 — Responsible AI risk review

Act as a responsible AI reviewer for HRM.

Review this AI-enabled HR idea:
[paste idea]

Score it from 1 to 5 for:
- Privacy risk
- Bias/fairness risk
- Transparency risk
- Employee dignity risk
- Legal/governance risk
- Practical value

Then classify it as:
- Safe classroom prototype
- Needs restrictions
- Not appropriate for the workshop

Explain your reasoning and suggest a safer redesign.

Prompt 12 — Final 60-second pitch builder

Help my student team prepare a 60-second pitch for our AI-Digital HRM prototype.

Our fictional organization: [name]
HR problem: [problem]
Our solution: [solution]
Tools used or proposed: [tools]
Main benefit: [benefit]
Main risk: [risk]
Safeguard: [safeguard]

Create a concise pitch with:
- Opening hook
- Problem
- Solution
- HR value
- Responsible AI safeguard
- Closing line

Keep it clear and professional for a Sri Lankan university workshop.

Prompt 13 — People analytics insight memo

Act as a people analytics translator.

Using the synthetic HR data summary below, write a short insight memo for HR leaders.

Synthetic data summary:
[paste fictional statistics]

Memo structure:
1. What is happening?
2. What might be causing it?
3. What should HR investigate before deciding?
4. What are two responsible AI or data risks?
5. What practical next step should HR take?

Do not claim causation unless the data supports it.

Prompt 14 — Ethical chatbot boundary setting

Act as an HR service design specialist.

Design boundaries for an onboarding chatbot for a fictional Sri Lankan organization.

The chatbot may answer:
- First-week schedule
- Training links
- Basic policy summaries
- HR contact information

The chatbot must not:
- Give legal advice
- Decide leave, salary, discipline, or complaints
- Collect sensitive personal data
- Replace human HR support

Create:
- 10 allowed questions
- 10 questions to escalate to HR
- 5 refusal messages
- 5 transparency statements

Suggested use during the workshop

Reflection question

After using any prompt, students should answer:

What did AI help with, what did it miss, and what must a human HR professional still decide?