Our every day world is changing fast, but the pace at which artificial intelligence (AI) is reshaping labor markets is on an entirely different - and unprecedented - level. What once took decades—global product launches, tech adoption, infrastructure shifts—is now happening in mere months. ChatGPT reached 100 million users faster than any product in history. AI assistants are running research reports, translating voices in real-time, and even managing kitchens at scale. And under the hood, the tech infrastructure to power all this is growing at breakneck speed, with the world’s largest companies investing billions. A new industrial revolution? Maybe. A transformation of work, talent, and competition? Definitely. So where are we now? Where are labor markets heading? Let’s break it down.
This article is based on Meeker's 2025 report "Trends - Artificial Intelligence".
The Big Picture: AI Is Not a Tool. It’s a Tectonic Shift - for Society and Labor Markets World Wide.
In May 2025, Mary Meeker, General Partner at venture firm BOND released a 300+ page report compiling data from hundreds of sources. The message is crystal clear: AI is not just a trend—it’s a fundamental reshaping of how things work.
(Only few of the many) Highlights from Meeker's 2025 report "Trends - Artificial Intelligence"
--> AI development is outpacing past innovations like the internet or smartphones.
--> ChatGPT now logs 800 million weekly active users.
--> AI compute and training costs are soaring—yet performance and adoption are rising even faster.
--> From Duolingo to JP Morgan, AI is already embedded in real-world workflows.
--> China is no longer just catching up—they’re competing head-to-head.
Companies, individuals, and institutions must adapt—or risk irrelevance.
A More Competitive Labor Market for Candidates
With the rise of AI, the number of active developers is skyrocketing - because it has become so much easier to code. As shown in Google’s own data, over 7 million developers are now building with Gemini, a fivefold increase in just one year. At the same time, ongoing layoffs, macroeconomic uncertainty, and potential trade disruptions (like tariffs on chips or cloud infrastructure) are intensifying competition amongst candidates. This rapid growth signals a broader trend: the talent pool is expanding fast, and the market for tech roles is getting more crowded - with each open role attracting more applicants than ever. For candidates, it means the bar is rising—and differentiation through real-world impact, adaptability, and abilities other than coding, namely domain knowledge, network and AI fluency are becoming more important than ever.
More AI Roles - with new required Skills
The number of AI-related job titles has surged by 200% between Q2 2022 and Q2 2024, according to ZoomInfo. Across industries, companies are redefining roles and creating new ones—from “AI Product Lead” to “Machine Learning Strategist.” This means more opportunity for candidates, especially those who can blend technical understanding with business context. As companies expand their hiring scope, expectations rise: real-world AI fluency, adaptability, and the ability to work across teams are becoming baseline, not bonus. To stand out, it’s not enough to know about AI—you have to show how you use it.
What You as a Candidate Should Take Away from the Meeker AI Report
The AI market isn’t just about hiring for “AI jobs.” It's about a shift in what skills matter across all roles. Whether you’re a marketer, analyst, designer, developer, or ops lead—AI is already reshaping the way work gets done. Here’s what the data shows, and what candidates should focus on:
1. AI skills are hot property
Whether it’s prompt engineering, automation, or tuning open-source models, hands-on AI knowledge is in high demand—across industries and seniority levels.
2. Agents are the new assistants
We’re moving beyond chatbots. AI agents now take actions, complete workflows, and make decisions. Candidates who know how to build, use, or integrate them will stand out.
3. Data fluency is a core skill
You don’t have to be a data scientist, but you do need to understand how data powers the tools you use. Knowing what tokens are, what makes a model “learn,” or how to structure input gives you an edge.
4. Open-source is changing the game
Proprietary models aren’t the only path. Open systems like LLaMA or Qwen are rising fast—and those who know how to adapt, deploy, or contribute to them are increasingly valuable.
5. AI touches every sector - hence your domain knowledge becomes key.
From finance and healthcare to logistics and education—no field is untouched. Understanding how AI is impacting your domain makes you a sharper candidate - and use your existing domain knowledge to your advantage. Domain knowledge now often beats programming knowledge.
6. Prompt Engineering is a new power
Clear, structured communication with AI tools is a skill in itself. Knowing how to get the right output is becoming as essential as writing a good email.
7. Multimodal fluency is the new 'Full Stack'
AI no longer just works with text. Tools now process voice, visuals, code, and more. Being comfortable creating and working across formats will be key going forward.
8. Measurable productivity wins jobs
Don’t just say you use AI—show the impact. If it helped you ship faster, make fewer errors, or serve more clients, that’s what hiring teams care about - be sure to mention those gains in your resume.
9. Security, Compliance-oriented and Ethics-savvy profiles stand out
The risks of AI—bias, misinformation, surveillance, security and compliance (e.g. EU AI Act) —are real. Candidates who can show awareness and responsibility will be trusted with bigger responsibilities.
10. AI isn’t replacing you—it’s amplifying you. Learn how to use it.
The most successful candidates are those using AI as leverage, not seeing it as competition. Those who take courses, continuously expand their skills and adapt now won’t just keep up—they’ll lead.
If you want to dive deeper into how AI affects the market for candidates and companies, we explored this question deeper together with Stephan Lendi, Dalith Steiger-Gablinger and Klaus L. Fuchs in the podcast the AI Talk Podcast – The Swiss AI Landscape.
Listen on Spotify: https://lnkd.in/dvammQVx
Or on Apple Podcasts: https://lnkd.in/d9s5-dez
The Recipe for Success in the AI Labor Market: How to secure your dream role in Tech?
The shift is real, and the pressure is rising. But the good news? You don’t need to be an AI engineer to thrive—you just need a smart plan. Here’s your step-by-step recipe for staying ahead in a market shaped by automation, agents, and accelerated expectations:
--> Step 1: Leverage AI to Find Jobs for you
Stop wasting time with scrolling and searching. In addition to job boards that often require you to actively browse, use email alerts (e.g. Linkedin, X), scraping and AI tools like ScrapeGraph, Firecrawl, ChatGPT, Claude, or Gemini to generate job search strategies, refine search terms, and even automate your weekly job discovery routine. For example, use AI to be alerted about funding news in a field of your interest. Add yourself to job alerts and have AI go through your inbox and identify matching jobs within the plethora of mails. Block time to build your long-list of potential employers and make sure to be alerted of new openings there.
--> Step 2: Tailor Your CV with AI Support
Stop sending the same CV everywhere. Use AI to match your wording to job descriptions, rewrite bullet points for impact, and highlight your most relevant skills for each role. Read this useful guide on how to write the perfect CV. Make sure to use an updated design and check the machine-readability of your CV with AI tools.
--> Step 3: Learn Faster with a Strategy
Courses alone won’t set you apart—but smart, focused learning strategies will. Nanodegrees beat individual certificates. Don't forget about domain-specific trainings and certifications. Use platforms like Coursera, Udacity, Khan Academy, or LinkedIn Learning to upskill on AI tools, data basics, and prompt writing—and let AI help you build a learning plan. In terms of upskilling, also consider AI deficits like bias, misinformation, surveillance, security and compliance (e.g. EU AI Act, GDPR).
--> Step 4: Build real-world AI Projects
Building an AI MVP is easy. Bringing AI intro production with real-world adoption is a different animal. Pick 1–2 real world use cases you can solve with AI (e.g. writing, analysis, reporting, automation), within a domain that you are comfortable in - and build it out regularly, e.g. weekly. Bring such real-world AI implemenation examples from your job or private context into interviews or your (Github) portfolio - and mention them or link them on your Linkedin.
--> Step 5: Expand Your Network online, but especialy offline - via Meetups, Conferences and Events.
Work on your networking game. A lot of roles are never published, or candidates hear about them too late. Make sure to network online (e.g. Linkedin) but also offline. For Linkedin, use tools to validate the content of your profile against what ATS tools are looking for. You should attend conferences, workshops, meetups to network and hear about companies that are hiring and be known to decision makers before new roles are even published.
--> Step 6: Use Referrals and Introductions
Working together requires trust - and we trust humans that we already know or who are recommended by people we trust. A warm intro still beats a cold application, and especially one-Click applications on Linkedin. Let your network work for you—and use AI to help identify shared connections or past collaborators who can make that first move easier. Check in with the recruiters if they have questions on your dossier, or what the next steps could be.
--> Step 7: Keep Track of your Application Processes and your AI wins
Track your applications, interview invites and successes in a spreadsheet. It's normal to send 50-100 applications within a competitive labor market. It's hence key to keep an overview, e.g. in a Google Sheet, Notion or Excel. Whether you used AI to save time, improve results, or build something new—track it. Share it. Own it. These stories make you stand out when hiring teams compare candidates.
--> Step 8: Target in-demand industries and regulated areas
Target in-demand fields and industries. Each industry differs in hiring demand. To navigate a competitive labor market, go into in-demand industries which could be Defense, Healthcare, Banking, Blockchain - or AI in general if you see yourself working at companies like OpenAI, Perplexity, etc. Especially in regulated domains, such as insurances, healthcare or the military domain, local companies have an edge over foreign AI products.
--> Step 9: Stay Agile
The current job market is in flux. There is a high chance that job titles are changing. Today you might be a Full Stack Engineer, soon you might be an AI Engineer and in the future, you might become a Quantum AI Inference Compliance Engineer. React to trends, stay hungry and curious.
--> Step 10: Partner with Recruiters Who Get AI
Work together with recruiters who are specialized on your nieche. Generalist recruiters won’t cut it anymore. The AI job market is fast-moving, hybrid, and filled with nuance. Work with recruiters who understand emerging roles, know what companies actually need, and can help position you where your skills matter most. The right recruiter isn’t just a middleman—they’re your shortcut to the right opportunities.
