The New AI Skill Path for Every Professional
A few years ago, I was sitting in a meeting with a senior leader who said something that stayed with me forever:
“Technology waves come and go, but careers only grow when people grow with the wave.”
At that moment, I remembered my own journey from traditional enterprise technology to the cloud, then to AI, and now to Generative AI.
Every shift felt uncomfortable at first.
But each shift also opened the next big door in my career.
Today, I’m seeing the same pattern again, this time, much faster, and it is so widespread that everyone is part of it.
Every week, I meet professionals who tell me:
- I want to start with AI, but I don’t know how.
- I feel like AI is moving faster than my skills (this is also my thought)
- I don’t know what to learn first.
I have been exactly where you are.
And that’s why I thought to share my thoughts, maybe it will help you get some clarity.
The 4 Stages of AI Career Growth
Think of this as your roadmap, not to become an “AI expert,” but to grow steadily.
1 - Awareness “I know AI can help me.”
This is where everyone begins.
Your only goal here is to understand what’s happening in the world.
Nothing more.
- Read 2 newsletters per week.
- Watch real demos, not hype.
- Try small prompts daily (nowadays, every organization has started introducing their own private LLMs access, so you can also use it with your organization's data)
2 - Application “I can use AI in my own work.”
This is where the initial actions happen. You build one workflow that saves time or improves your output.
Turn customer complaints into themes & solutions. “Analyze these 50 customer messages and group them into themes with recommended actions.”
Summarize a 20-page document into a 1-page executive brief. “Summarize this into a 1-page brief with: context, key insights, risks, opportunities, and actions.”
3 - Integration “AI is part of my system.”
Linking AI to your tools, data, and workflows. It is challenging until the required IT ecosystem is in place; however, we are starting to see it in action at several organizations.
Few examples:
You build a central, searchable Q&A Assistant (your own “Enterprise ChatGPT”) trained on:
- policies
- documentation
- product manuals
- FAQs
- operational knowledge
Employees get answers instantly.
Document-to-Decision Pipeline, You upload RFPs, contracts, or 40-page documents, Gen AI extracts:
- key risks
- required actions
- dependencies
- financial points
- red flags
This becomes part of a workflow.
4 - Leadership “I help others understand AI.”
At this stage, you are not just using AI, you’re turning your experience into value for others.
- Sharing your lessons
- Guiding your team
- Showing real examples
- Becoming the “AI champion” in your circle
- They’re made through consistent action.
The 3-Hour Rule (That Changed My Life)
I have followed this simple rule for the past three years:
Spend 3 hours per week on AI.
- 1 hour learning
- 1 hour experimenting
- 1 hour documenting + sharing
Do this for 8 weeks…and you won’t recognize your workflow anymore.
What You Should Do This Week
Pick one task and ask:
“How can I do this faster, smarter, or better using AI?”
Then share your learning. That one post may open a door you didn’t expect.
Coming Next Week: AI Career Pathway (Notion Template)
I’m building a practical, simple AI career planning system you can use to track:
- skills
- habits
- projects
- examples
- achievements
Reply YES if you want early access. Your career doesn’t grow by chance.
It grows by clarity, repetition, and small wins.
Let this be your compass.
