RestartCrewRestartCrew Team
A lot of career advice right now is either panic or hype. Here is our honest attempt at the middle: patterns that show up consistently across labor-market research and hiring data, written for people deciding what to do next. No guarantees exist — but these are reasonable bets, and for each one we include who it suits and a concrete first step.
1. AI IMPLEMENTATION AND WORKFLOW AUTOMATION
Every company adopting AI needs people who understand a real business domain AND can make the tools work in practice. This is less about coding and more about process thinking.
Suits: operations people, project managers, anyone who knows an industry from the inside.
First step: automate one real workflow from your current or former field using accessible tools, and document it. That single case study is your entry ticket.
2. DATA ANALYSIS
Still growing, still the most common bridge out of administrative and coordination roles. The path is learnable: spreadsheets, then SQL, then a visualization tool.
Suits: detail-oriented people who liked the reporting part of their old job.
First step: Kaggle Learn or freeCodeCamp's data analysis track, then one portfolio analysis of a public dataset from your old industry.
3. AI QUALITY, EVALUATION AND TRAINING WORK
AI systems need humans to evaluate outputs, write and test prompts, and check quality in specific domains. Domain experts (legal, medical, finance, language) are especially wanted.
Suits: people with deep subject expertise and a critical eye.
First step: search for "AI trainer", "data annotation" and "model evaluation" roles plus your domain — read three ads and note what they require.
4. CUSTOMER-FACING ROLES FOR TECHNICAL PRODUCTS
Sales engineering, customer success and support for software products reward people who can translate between technical and human — and industry experience from the customer side counts heavily.
Suits: communicators who know an industry's problems firsthand.
First step: list the software products your old industry buys, and look at the careers pages of those companies.
5. HEALTHCARE, SKILLED TRADES AND CARE WORK
Growing for demographic reasons regardless of AI, and hard to automate. Retraining takes longer, but demand is durable and geographically spread.
Suits: people who want work with visible, physical results — and stability.
First step: look up subsidized retraining programs in your country; many exist precisely for these fields.
6. GOVERNANCE, COMPLIANCE AND AI POLICY
Regulation of AI is expanding, and companies need people who can read rules and translate them into practice.
Suits: people from legal, HR, audit, finance or public-sector backgrounds.
First step: read your region's main AI regulation summary, then search "AI governance" + your background.
7. THE "AI PERSON" IN YOUR OWN PROFESSION
Often the most realistic move of all: same profession, new toolkit. The person on the team who actually masters the new tools tends to be the last one cut and the first one promoted.
Suits: anyone currently employed and worried.
First step: pick the most repetitive part of your job and become the person who automated it — visibly.
THE HONEST SUMMARY
Adjacent moves beat dramatic pivots for most people. Pick the option closest to what you already know, unless you want the distant one badly enough to fund the longer runway. And whichever you pick: start smaller than feels impressive, and start this week.
Which of these are you considering? Reply and we will dig into specifics.