Mapping Your Learning Priorities
Understanding which AI skills to prioritize is crucial for effective learning. Rather than trying to learn everything at once, you need a structured approach that aligns with your professional goals and immediate needs.
When prioritizing your AI learning, consider:
Immediate Job Impact: Which skills will have the most immediate positive effect on your work?
Future Career Goals: What skills align with your long-term career trajectory?
Industry Trends: Which AI capabilities are becoming standard in your field?
Learning Dependencies: What foundational knowledge do you need before advancing to more complex topics?
Also, if you've been following along with this series, now is a great time to revisit the results from your AI Readiness Assessment!
Instructions
In this exercise, you'll create a structured framework to prioritize your AI learning journey. Rather than attempting to learn everything at once, this matrix will help you identify which skills deserve your immediate attention and which can be developed over time. The goal is to create a clear, actionable roadmap that aligns with both your current role's demands and your future career aspirations. This isn't about learning AI for AI's sake – it's about developing the specific capabilities that will drive your professional growth and impact.
You'll evaluate each potential skill through two lenses: its importance to your role and the urgency of acquiring it. By multiplying these factors, you'll get a clear priority score that helps you make informed decisions about where to focus your learning efforts.
This exercise typically takes about 45 minutes to complete thoroughly, and you'll want to revisit and adjust it quarterly as your needs and industry demands evolve.
I've created a priority matrix for you to leverage to complete this exercise. You can download the priority matrix here: Priority Matrix
AI Skills
AI skills generally fall into three categories:
Foundational Knowledge - Understanding basic AI concepts, terminology, and principles
Technical Skills - Practical abilities like prompt engineering, tool usage, and workflow integration
Strategic Skills - Evaluation, implementation planning, and business case development
For the AI Skills column, list the AI Skills that are relevant based on the following:
Your job description
Industry job postings
Skills mentioned in professional publications
Skills your colleagues are developing
Skill Importance
Rate each skill’s importance on a scale of 1-5, based on the following:
5: Critical for current role
4: Very important for near future
3: Moderately important
2: Somewhat important
1: Nice to have
Skill Urgency
Rate the urgency of needing to acquire each skill on a scale of 1-5, based on the following:
5: Needed immediately
4: Needed within 3 months
3: Needed within 6 months
2: Needed within 9 months
1: Needed within 12 months
Priority Score
After you’ve rated both the importance and urgency for your listed AI skills, calculate the priority score by multiplying Importance x Urgency.
Group skills into learning phases
Whether you're scheduling your learning journey across a few days, a few months, or over the course of a year, it's helpful to group your learning priorities across phases. Grouping into phases aids in helping you balance the ideal and/or proper time to narrow in on a subject.
You’ll now map your listed AI skills to a learning phase based on the AI skill’s priority score. The example provided below is based on a 1-year learning period. You're encouraged to adjust the timeframe to better suit your needs.
Map high-priority skills to the next 3 months
Plan medium-priority skills for months 4-6
Schedule low-priority skills for months 7-12
Once you have your learning phases in mind, you can better schedule your time for learning.
Assess your priorities
Your completed priority matrix is more than just a list – it's your strategic guide for AI skill development. Take a moment to review your results and consider how they align with your initial expectations. You may be surprised to find that some skills you thought were urgent actually scored lower in the matrix, or vice versa. This is valuable insight.
Use this matrix as a living document; revisit it monthly to track your progress and quarterly to reassess priorities as your role and industry evolve. Remember that the highest-scoring skills aren't necessarily the ones you need to tackle first – consider any dependencies between skills and adjust your learning sequence accordingly.
Most importantly, let this prioritized roadmap guide your daily and weekly learning decisions, helping you stay focused on what matters most for your professional growth in AI.
More about the series
This article is part of the Resolution Proof Your Career: Thriving in the AI Workplace series - a 6-week career transformation series designed for professionals who want to turn their 2025 AI career resolutions into reality - starting now, not January. It’s not too late to join! Subscribe to the Millennial Workweek newsletter to get the next exercise in the series and visit the Millennial Workweek website to get caught up!
