A former student emailed me last month. She’d been job hunting for six months, getting interviews but no offers. Talented, qualified, checking all the boxes. Then she tried something different. Instead of highlighting her skills, she explained how she worked. The problems she naturally noticed. The way she processed information. Her operating system, not her resume.

She received three offers in two weeks.

This isn’t luck. This is what happens when someone understands the basis of value in the economy we’re actually living in versus the one we’re still preparing people for.

The big picture: we’re in the middle of an economic reorganization, and most people haven’t noticed yet. For decades, economic value came from what you could do. Your skills, credentials, ability to execute tasks. The information economy rewarded people who could access, process, and apply knowledge efficiently.

That era just ended.

When AI can execute any task you can describe, access information instantly, and process it faster than any human, “knowing how to do things” stops being the basis of economic value. The World Economic Forum projects that 85 million jobs will be displaced by AI by 2025 (World Economic Forum Future of Jobs Report 2025), while companies using AI report that 44% expect employees will be laid off due to artificial intelligence (Resume Builder, 2024). Already, 76,440 workers have lost their jobs to AI automation in 2025 alone (Josephine Nartey, AI Job Displacement Analysis 2025-2030), and 40% of employers are aiming to reduce their workforce where AI can automate tasks (World Economic Forum, 2025).

What becomes valuable is the thing AI fundamentally cannot replicate: your work identity.

Work identity is the stable pattern of how you naturally work: how you process information, what problems you naturally notice, how you make decisions, what conditions you need to perform, and where your specific way of thinking creates unique value. It’s not about executing predefined tasks. It’s about knowing which skills to develop and how to apply them in ways that align with how you naturally work.

Who are you, and how do you work when you strip away job titles and skills?

The Shift Nobody’s Preparing For

Every major economic transition reorganizes around a new basis of value.

Agricultural economy: Value came from land and labor. Economic organization: who owns the land, who works it.

Industrial economy: Value came from capital and production capacity. Economic organization: factories, assembly lines, standardized processes.

Information economy: Value came from accessing and processing information. Economic organization: education credentials, specialized knowledge, information flows.

Identity economy: Value comes from understanding your work identity and using that self-knowledge to guide which skills you develop and how you apply them. Economic organization: TBD, because we haven’t built it yet.

That’s the problem.

We’re watching the basis of economic value shift in real-time, but our entire infrastructure—how we educate people, how we hire them, how we organize teams, how we measure contribution—is still built for the information economy. Education still teaches skills first and hopes students figure out their identity later. Hiring still evaluates credentials without asking whether those skills align with how someone naturally works. Teams still organize around roles and functions rather than understanding how different operating systems complement each other. Performance reviews still measure task completion rather than whether people are developing and applying skills in ways that match their work identity.

This isn’t just outdated. It’s fundamentally misaligned with where value is moving.

What the Identity Economy Actually Looks Like

In an identity-based economy, the question isn’t “what can you do?” It’s “how do you naturally work, and which skills should you develop based on that understanding?”

Skills still matter. They’ll always matter. But the identity economy changes everything about how we think about skill acquisition and application.

Because when AI handles routine execution, humans provide three things:

Judgment under uncertainty. Recognizing patterns, making decisions when there’s no clear answer, understanding context that can’t be codified. Bloomberg research reveals that while AI could replace 53% of market research analyst tasks and 67% of sales representative tasks, managerial roles face only 9-21% automation risk precisely because they require judgment (Bloomberg, 2024). The difference isn’t the skills—it’s knowing which situations require your specific way of processing information.

Direction-setting. Deciding what problems to solve, what opportunities to pursue, what trade-offs matter. Workers aged 18-24 are 129% more likely than those over 65 to worry AI will make their job obsolete (National University AI Job Statistics, 2025), but the jobs least likely to be affected by AI—those involving teaching, caring, coaching, or physical tasks, account for 23% of workers (DemandSage AI Job Replacement Stats, 2025). These roles all require human direction-setting, which comes from understanding how you naturally see opportunities and navigate complexity.

Identity-aligned skill application. Two people with identical skill sets will create completely different value based on their work identity. One might excel at rapid iteration and experimentation. Another might create value through deep, systematic analysis. Same skills. Different operating systems. Different contributions.

The gap isn’t that people lack skills. It’s that most people don’t understand their work identity well enough to know which skills to develop or how to apply them effectively.

Research shows that core self-evaluation, understanding who you are, positively impacts job search outcomes through career exploration and career adaptability (The Influence of College Students’ Core Self-evaluation on Job Search Outcomes, PMC, 2021). Studies of over 1,000 college students demonstrate that career exploration and self-reflection positively predict career adaptability and subjective well-being, with career calling having a significant mediating effect (Linking Career Exploration, Self-Reflection, Career Calling, Career Adaptability and Subjective Well-Being, PMC, 2023).

In the information economy, you could get by without deep self-knowledge as long as you had the right credentials and could execute tasks. You learned skills first, applied them generically, and maybe figured out your identity later if you were lucky.

In the identity economy, that’s backwards. Work identity becomes the foundation that guides everything else, which skills you develop, how you apply them, where you create unique value.

The Infrastructure We Need

Economic reorganizations require new infrastructure.

The shift from agriculture to industry required railroads, factories, supply chains, and new forms of capital organization. The shift from industry to information required computers, telecommunications networks, the internet, and new educational systems focused on knowledge transfer.

The shift from information to identity requires infrastructure we haven’t built yet:

Educational systems that start with work identity, then build skills around that foundation. Right now, students who develop career identity in line with their studies show increased well-being, motivation, and mindfulness, creating a virtuous circle that influences development of knowledge and skills (Psychological resources, satisfaction, and career identity in the work transition, PMC, 2018). But most students never get this foundation. They learn skills without understanding how they naturally work, which means they can’t strategically develop the capabilities that will create the most value for them.

Hiring processes that evaluate how someone works, not just what they know. The standard framework optimizes for credentials on paper. It can’t tell you whether someone’s skill set aligns with their operating system—whether they’ll apply those skills in ways that create sustainable value or burn out trying to work against their natural patterns.

Team composition strategies that understand how different operating systems complement each other. When you organize around identity, you don’t just look for people with the right skills—you look for people whose operating systems create cognitive diversity. The same skill applied by different identities produces different contributions. That’s the source of innovation.

Performance frameworks that measure whether people are developing and applying skills in alignment with their work identity. Two people might complete the same tasks, but one is building capabilities that compound while the other is grinding against their natural patterns. Traditional metrics can’t see the difference.

Career navigation tools that help people recognize which skills to develop based on their work identity. Gen Z’s average tenure in the first five years of their career is just 1.1 years, compared to Millennials at 1.8 years, Gen X at 2.8 years, and Baby Boomers at 2.9 years (Randstad Gen Z Workplace Blueprint, 2025). They’re not job-hopping because they lack skills—22% of Gen Z have already left a job, nearly double that of Millennials (Randstad, 2025), because they’re growth-hunting without a framework for understanding which skills will actually create value given how they naturally work.

We don’t have any of this yet.

Instead, we’re still running on information economy infrastructure while the basis of value shifts underneath us. And we wonder why talented people struggle, why 65% of Gen Z talent quits within 12 months of employment (Abode HR Gen Z Recruitment Report), why someone can have all the right skills and still not find their fit.

It’s not that people aren’t capable. It’s that they’re trying to develop and apply skills without the foundation of self-knowledge that makes those skills effective.

Why This Starts With Students

If the economy is reorganizing around identity as the foundation for skill development, the smartest move is to capture the entry point.

Students entering the workforce today will spend their entire careers in the identity economy. But they’re being prepared for the information economy that’s already ending. Entry-level job postings have dropped 15% year over year (DemandSage, 2025), while employers referencing “AI” in job descriptions have surged by 400% over the past two years (DemandSage, 2025). Big Tech companies reduced new graduate hiring by 25% in 2024 compared to 2023 (SignalFire via Final Round AI, 2025). These aren’t just hiring slowdowns—these are positions that no longer exist because AI can handle the generic skill application that used to be entry-level work.

Students graduate knowing what they studied. They don’t know how they work. They can list skills and credentials. They can’t articulate their work identity or explain why those specific skills will create value given how they naturally process information. They’ve spent 16 years learning to execute within external structure. They haven’t learned to recognize their own internal patterns or use that self-knowledge to guide which capabilities they develop.

That’s not their fault. That’s the infrastructure gap.

But it means they enter the workforce without the foundation the identity economy requires. Then they struggle, blame themselves, and spend years trying to figure out through trial and error what should have been taught deliberately. Nearly half (49%) of Gen Z job seekers believe AI has reduced the value of their college education (National University, 2025)—not because education is worthless, but because they learned skills without the self-knowledge to apply them strategically. Meanwhile, 40% of Gen Z employees report wanting to leave their job in the next two years (Korn Ferry Institute, 2025), and when 52% of early-career employees say their turnover could have been prevented (Abode HR), it’s a signal that we’re failing at the foundational level.

We can change that.

Making work identity foundational, not something people stumble into after struggling, creates a generation that enters the workforce already understanding how to think about skill development strategically. Research demonstrates that students with positive career identity show higher career success, affective commitment, and work satisfaction (PMC, 2018). Those who develop this “internal compass” face the university-to-work transition with significantly less difficulty because they know which skills to develop and how to apply them in ways that align with their work identity (PMC, 2018).

That’s not just better career readiness. That’s building the infrastructure for the economic reorganization that’s already happening.

The Transition Is Inevitable. The Infrastructure Isn’t.

Here’s what I’m certain about: the economy is reorganizing around work identity as the foundation for skill development and application. AI forces it. By 2030, 30% of current U.S. jobs could be fully automated, while 60% will see significant task-level changes due to AI integration (National University AI Job Statistics, 2025). When machines handle routine skill application, human value shifts to understanding your work identity and using that knowledge to guide which capabilities you develop and how you deploy them. That’s not a prediction—it’s already visible in how value is created and where it’s moving.

Here’s what I’m less certain about: whether we build the infrastructure for that transition intentionally or let it emerge chaotically.

Right now, we’re on track for chaos. Students graduating with skills but no self-knowledge to guide their application. Organizations hiring for credentials while value shifts to identity-aligned capability development. Teams organized around functions while contribution comes from understanding how different operating systems work together. Three-quarters (74%) of Gen Z workers are engaged at work and motivated to go above and beyond, yet only 40% plan to stay with their current company for three or more years, at least 20 points lower than any other generation (Qualtrics Employee Experience Research, 2023). That’s not disengagement. That’s misalignment between how people naturally work and how organizations ask them to apply their skills.

The people who excel will be the ones who figure it out despite the system. The people who struggle will be the talented ones with strong skill sets trying to create value without understanding which capabilities align with their work identity. When 77% of new AI jobs require master’s degrees and 18% require doctoral degrees (AI Job Loss Statistics, SQ Magazine, 2025), the skills gap becomes insurmountable for those without the foundation of self-knowledge to guide strategic capability development.

We can do better than that.

We can build infrastructure that makes work identity awareness foundational, the organizing principle for all skill development. That helps people understand how they naturally work before they start acquiring capabilities. That teaches them to think strategically about which skills will create the most value given their work identity.

That’s what I’m building with Cgility. Not just a better way to prepare students for work. The infrastructure for how people think about skill acquisition and application in an identity-based economy.

Starting with the entry point, students who need to understand their work identity before they start developing the capabilities that will define their careers.

Because economic reorganizations don’t wait for permission, they happen whether we’re ready or not. By 2030, McKinsey projects that 30% of work hours could be automated, with 800 million jobs potentially displaced globally (McKinsey, 2024). The timeline isn’t someday. It’s this quarter. The companies aren’t planning—they’re executing.

The only question is whether we build the infrastructure to support the transition or spend decades watching talented people with strong skill sets struggle because they never learned to think about capability development through the lens of work identity.

I’m choosing infrastructure.

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Ready to understand your work identity so you can develop skills strategically? Get the free guide with 5 Questions Every Student Should Answer Before Graduation

Sources

• World Economic Forum. (2025). Future of Jobs Report 2025.
• Resume Builder. (2024). AI and Employment Survey.
• Nartey, J. (2025). AI Job Displacement Analysis (2025-2030).
• Bloomberg. (2024). AI Task Replacement Analysis.
• National University. (2025). AI Job Statistics: Future of U.S. Jobs.
• DemandSage. (2025). 73 AI Job Replacement Statistics.
• The Influence of College Students’ Core Self-evaluation on Job Search Outcomes: Chain Mediating Effect of Career Exploration and Career Adaptability. PMC. (2021).
• Linking Career Exploration, Self-Reflection, Career Calling, Career Adaptability and Subjective Well-Being: A Self-Regulation Theory Perspective. PMC. (2023).
• Psychological resources, satisfaction, and career identity in the work transition: an outlook on Sicilian college students. PMC. (2018).
• Randstad. (2025). Gen Z Workplace Blueprint.
• Abode HR. Gen Z Recruitment and Retention Report.
• SignalFire via Final Round AI. (2025). AI Job Displacement 2025.
• Korn Ferry Institute. (2025). Who Is Gen Z: The Restless Generation?
• Qualtrics. (2023). Despite Low Retention Scores, Gen Z Are Engaged at Work.
• SQ Magazine. (2025). AI Job Loss Statistics 2025.
• McKinsey. (2024). Automation and the Future of Work Report.