Silicon Valley GirlLinkedIn CEO: These 3 Jobs Will Explode in the Next 5 Years | Ryan Roslansky
CHAPTERS
- 0:00 – 2:10
LinkedIn’s view of the labor market: sluggish hiring, but not because of AI
Ryan frames LinkedIn as a real-time lens on the global job market and explains why hiring feels slow right now. He argues the drag is macroeconomic (rates, investment pullback), while AI is simultaneously creating new roles.
- •LinkedIn as a “definitive labor market platform” with global hiring insight
- •Sluggish hiring attributed to interest rates and macro conditions, not AI
- •AI’s impact looks additive in LinkedIn data
- •Sets up the episode’s core tension: fear vs. data-driven reality
- 2:10 – 3:15
AI job creation is already measurable: new roles and infrastructure demand
Ryan cites LinkedIn data showing significant net-new AI jobs, pointing to specific categories that are growing rapidly. He highlights both digital and physical infrastructure work needed to power AI adoption.
- •1.3M net-new AI jobs on LinkedIn (as cited)
- •Emerging roles like data annotators
- •Over 600K new data center jobs (as cited)
- •AI-related growth spans technical, trade, and operations work
- 3:15 – 3:48
What’s happening with entry-level hiring—and why it isn’t uniquely worse
Marina presses on entry-level opportunities, and Ryan explains that entry-level hiring is down but broadly in line with the overall market decline. He then pivots to what early-career workers are doing instead.
- •Entry-level hiring down ~12% globally (as cited)
- •Decline mirrors broader hiring slowdown, not an entry-level-only collapse
- •Macro conditions driving contraction more than automation
- •Question shifts from diagnosis to individual strategy
- 3:48 – 4:36
Two alternative paths gaining momentum: creators and trade roles
Ryan describes two trends that rise when traditional pipelines weaken: micro-entrepreneurship/creator work and increased interest in trade jobs. He notes Gen Z views trades as more resilient in an AI-driven economy.
- •Rise of micro-entrepreneurship and “taking your career into your own hands”
- •Gen Z affinity toward trade/first-line roles
- •Trades perceived as more resilient to AI displacement
- •Creator economy becomes a legitimate, recognized sector
- 4:36 – 5:00
Creator economy scale on LinkedIn: titles, identity, and opportunity
They quantify how many people identify as creators on LinkedIn and discuss what that means culturally and economically. The conversation reinforces content as a professional signal—not just marketing.
- •75M members mention “creator” somewhere on their profile (as cited)
- •4M list “creator” as their full-time job title (as cited)
- •Creators’ growing legitimacy (even at Davos)
- •Professional identity increasingly shaped by content and visibility
- 5:00 – 6:36
‘Career paths are dead’: navigating non-linear careers and rapid skill change
Ryan explains why linear ladders don’t show up in LinkedIn data and why workers must actively steer their careers. He emphasizes the accelerating rate of skill change—projecting major disruption by 2030.
- •No consistent linear career path appears in the data
- •Individuals must proactively manage their career direction
- •Role skill requirements have changed >25% in recent years (as cited)
- •Expected ~70% skill change by 2030, heavily influenced by AI (as cited)
- 6:36 – 9:29
Top skills for 2026: combine AI literacy with irreplaceable human strengths
Ryan outlines the “both/and” approach: learn AI tools while doubling down on human skills that drive collaboration and leadership. He argues “soft skills” are mislabeled and increasingly decisive.
- •AI literacy as a baseline investment across professions
- •Human skills: curiosity, creativity, courage, communication, compassion
- •Success requires collaboration, conversation, and influence—not just tools
- •Reframing “soft skills” as mission-critical strengths
- 9:29 – 12:51
How to use LinkedIn to get hired: demonstrate expertise through posting
Marina shares her hiring method—evaluating candidates by what they post—while Ryan reinforces LinkedIn’s intent as an opportunity platform. They discuss authenticity, audience quality, and using content to show what you know.
- •Hiring managers use posts to assess depth, thinking, and fit
- •LinkedIn profile extends beyond credentials into demonstrated knowledge
- •LinkedIn’s feed aims to create economic opportunity (not pure entertainment)
- •Personal stories and perspective can strengthen professional identity
- 12:51 – 15:12
Is college still worth it? Education’s changing role in hiring
Ryan addresses the value of college amid underemployment and debt pressures, arguing the system isn’t working well for many. He still values college for social development and networking, while noting hiring is shifting toward skills and demonstrated ability.
- •50% of US grads unemployed or underemployed (as cited)
- •Student loan debt outpacing credit card debt (as cited)
- •College still valuable for growth, relationships, and communication skills
- •Recruiting focus shifting from school name to skills and signals (like posts)
- 15:12 – 16:55
‘Open to Work’: a guide to building a career in an AI-first world
Ryan introduces his book as a practical framework for navigating uncertainty rather than a prediction engine. He describes how it blends LinkedIn market insights with guidance on aligning human strengths and AI capabilities.
- •Book aims to reduce fear and clarify career planning in AI era
- •Explains what AI can do vs. what it can’t
- •Encourages combining technical adaptation with human capability-building
- •Uses labor-market signals to support smarter decisions
- 16:55 – 19:39
The ‘5 Cs’ AI can’t replace—and how to develop them
Ryan shares the book’s core principle: investing heavily in five human capabilities that will differentiate professionals. He argues these traits can be taught and practiced like any other skill.
- •Five Cs: curiosity, courage, creativity, compassion, communication
- •Risk of over-indexing on technical skills while neglecting human ones
- •Soft skills are learnable and practice-based
- •LinkedIn Learning positioned as one avenue to build these capabilities
- 19:39 – 22:23
Top jobs poised to explode: data annotators, data centers, forward-deployed engineers (and creators)
Ryan names the fastest-growing roles he expects to surge over the next 3–5 years, explaining what each does and why demand is rising. He also adds creators as an important adjacent “fourth” path.
- •Data annotators: experts paid to evaluate/improve model outputs
- •Data center buildout: infrastructure roles across trade and technical work
- •Forward-deployed engineers: bridge business needs with AI implementation
- •Creators as a growing professional category and opportunity vector
- 22:23 – 23:37
Jobs that will disappear: think in tasks, then automate-proof your skill set
Ryan avoids a simple list and offers a framework: decompose any job into tasks and assess which are automatable. He flags summarizing, rewriting, and translating as areas AI already does well and urges skill expansion to stay resilient.
- •Jobs are bundles of tasks; automation risk depends on task mix
- •AI is strong at summarizing, rewriting, translating
- •Workers should add complementary skills to “future-proof” roles
- •LinkedIn data can guide which skills to build next
