Create a personal AI capability roadmap for my role
A staged plan to grow from occasional AI user to someone who builds and directs AI workflows in your job.
The prompt
Create an AI capability roadmap for me, specific to my role.
My role and main deliverables: [DETAILS - e.g. "HR business partner: policies, employee cases, workforce reports"]
AI tools I have access to at work: [e.g. Copilot, ChatGPT Enterprise, Gemini, none yet]
How I use AI today: [e.g. "occasional email drafts"]
Company rules on AI use: [WHAT IS ALLOWED, DATA RESTRICTIONS - or "not sure"]
Time per week I can invest: [HOURS]
Use these stages and place me in one:
1. Occasional user - ad hoc questions and drafts.
2. Reliable user - reusable prompts for my recurring tasks, consistent checking habits.
3. Workflow designer - multi-step workflows, templates, and shared prompts for my team.
4. AI director - delegating whole tasks to AI or agents with clear specs, review gates, and measured quality.
For each stage from where I am now, give:
- 3-5 capabilities to build, tied to my real deliverables.
- One practice task using my actual work.
- The evidence that I have reached the stage (e.g. "cut report prep from 6 hours to 2 with no quality complaints").
- Risks to manage at this stage (data privacy, errors, over-reliance).
Return:
1. My current stage and why.
2. The roadmap as a table: Quarter | Stage | Capabilities | Practice task | Evidence.
3. The first 2 weeks in detail.
Keep every step within my company's AI rules. If I did not share them, remind me to check before using AI with confidential or personal data.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Working with AI prompts
What to fill in
- e.g. Copilot, ChatGPT Enterprise, Gemini, none yet
- e.g. "occasional email drafts"
- WHAT IS ALLOWED, DATA RESTRICTIONS - or "not sure"
- HOURS
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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