For the last 20 years, if a niece or nephew asked my opinion on what college major to pursue, I would steer them toward computer science — confident that it promised long-term job security. My sister-in-law, a tenured philosophy professor, often expressed caution to those curious about the humanities due to limited career opportunities.
But is AI about to flip that script?
As AI automates an increasing number of specialized, often white-collar tasks, we will witness a shift in the skills that employers value most. This moment could create a potential renaissance for humanities and social science education — a shift that K-12, higher education, and workforce leaders should be ready to address through curriculum design and training.
For decades, education leaders have focused on STEM — science, technology, engineering and mathematics. In a world that re-emphasizes the humanities, it could make more sense to orient education and training around “THESIS”: technology, humanities, engineering, science, innovation, and social sciences.
AI is disrupting the job market in real time and is absorbing many of the rote, pattern-driven job activities that historically comprised most entry-level white-collar work. Aneesh Raman, chief economic opportunity officer at LinkedIn, has said this automation of technical skills is “breaking first the bottom rung of the career ladder.” Among the newest cohort of college graduates, computer engineering and computer science have seen some of the highest unemployment rates: 7.5% and 6.1% according to the New York Federal Reserve. This is an early signal to education leaders that even technical degrees are no longer a safe bet.
For institutions to prepare students for this rapidly evolving job market, they need to understand the trajectory of AI capabilities and how that intersects with human skill sets. AI itself is constantly changing, but we can identify some trends that will allow education leaders to adjust effectively.
Before the rise of AI, hiring managers frequently listed durable skills like critical thinking, teamwork, and communication on job descriptions. However, these skills were often secondary considerations in actual hiring decisions — especially for technical roles. When choosing between two candidates, managers historically favored technical competence over those stronger in humanities skills. Education systems reflected this preference, often nudging learners to STEM-focused curricula over humanities in response to industry demand.
This hiring calculus is now flipping. Advanced AI tools, particularly agentic systems, can autonomously handle complex technical tasks that were previously the domain of entry-level hires. On the other hand, AI still struggles with novel situations, complex communication, causal reasoning, understanding human contexts and nuance, and the ethical implications of its outputs. There’s a clear takeaway: the human-centric skills once considered secondary must now be treated as core elements of education.
We may be approaching a convergence point where the skills historically emphasized in social sciences and humanities become as important as the technical skills traditionally associated with STEM degrees — giving equal weight to all of the letters in THESIS. On a longer timescale, there may even be a crossover point with humanities and social sciences surpassing STEM in relative importance.
Sherly Sandberg put it succinctly: “AI will require the collaboration of human creativity and machine learning to solve some of the world’s most pressing challenges.”
To be clear, demand for technical savvy is likely to continue apace. But as tools become more user-friendly and autonomous across a wide range of professional categories, purely technical skills will become more commoditized. The future will belong to professionals who are “bilingual” — conversant in the tools and technical underpinnings of AI, but also fluent in the human contexts and skills that AI can’t replicate. “Bilingual” employees will be able to unlock AI solutions in optimal ways and pick up where the tools stop.
As AI systems become more sophisticated, human work will likely shift toward higher-level management and areas requiring uniquely human capabilities. Several new essential skills will become more valuable — ones where humanities and social sciences provide a crucial foundation:
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Systems fluency: The ability to understand and manage interconnected (agentic) systems, especially when outcomes are emergent and unpredictable. This skill prepares individuals to navigate complexity, adapt strategies, and anticipate ripple effects.
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Metacognitive agility: The ability to reflect on and adapt one’s own thinking strategies in real time. As AI systems evolve rapidly, workers must evaluate when to trust a model, when to intervene, and how to recalibrate their problem-solving approach.
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Collaborative intelligence: The capacity to partner effectively with both AI systems and human teams to solve complex problems. Future professionals won’t just use AI but co-create with it.
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Radical creativity: The ability to generate novel ideas, concepts or forms of expression that extend beyond AI’s incremental innovation. Literature, philosophy, and even art and music train people to imagine new paradigms, break conventions, and express meaning in human ways — even in a highly automated world.
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Persuasive social insight: The ability to engage, motivate and inspire others by tapping into social and emotional drives like compassion, pride, and solidarity. While AI can passively assess someone’s emotional state, it struggles to activate these drives in persuasive, authentic ways. Humans are uniquely capable of rallying others around a cause or idea through storytelling, empathy and shared values.
Humanities and social sciences education provides an exceptionally strong foundation for developing these new essential skills. This doesn’t mean technical degrees lack value. Rather, it suggests that technical education at both the K-12 and college levels will need to incorporate more humanities and social science elements while these fields continue to develop technical literacy alongside their traditional strengths.
Throughout history, “platform shifts” have created entirely new professions: the steam engine brought locomotive engineers and factory supervisors; electricity created electricians and power plant operators; and the internet led to web developers and SEO specialists. The current AI platform shift will inevitably generate its own wave of new professions. The formation of these new professions — and the loss of others — will take place on a faster timescale, because the adoption curve of this cycle will be shorter. This behooves educators and workforce development leaders to anticipate these emerging roles and adjust curriculum and training priorities in real time.
Looking forward, we can envision a spectrum of new roles that emerge and accelerate as AI becomes more embedded in daily life. In the near term, those roles might include AI prompt engineers, bringing together technical understanding and the very human ability to communicate goals precisely and interpret responses critically; AI content integrity specialists, responsible for verifying authenticity, detecting manipulation, and ensuring ethical quality of AI-generated content that draws skills from journalism, media studies, philosophy, and ethics; or, in the same way smartphones created a new generation of video content creators, we may see AI unlock a wave of new entrepreneurs without product development experience that rely instead on “vibe coding” to launch startups where success depends less on coding mastery and more on ideation, storytelling and strategic planning.
Years in the future, we may see “foundation model expansionists” — responsible for actively pushing the boundaries of the creative and cognitive capacity of AI systems — and “empathy architects” — tasked with designing emotionally resonant AI interfaces for fields like caregiving and education. These jobs will be neither purely technical nor purely humanistic — integrating durable skills, critical thinking, creativity, systems design, with technical AI literacy.
The evolving timeline of AI capabilities suggests organizations will increasingly regard skills learned in humanities programs as “need-to-haves.” In the near term, there can be a “humanities reboot” in school and college curricula with particular emphasis on integrating durable skills like creativity and systems design with technical AI literacy.
But as AI capabilities advance, even these humanities-derived skills will need to evolve to incorporate newer skills like metacognitive agility, collaborative intelligence, and novel problem-solving. Educational curricula and workforce training programs must be continuously updated to integrate these emerging competencies. It also suggests the right course of action is a balanced approach: strengthening traditional humanities and social science education alongside technical understanding now while integrating newer essential skills as AI capabilities advance.
So the next time my nieces and nephews ask me what majors to pursue, I’ll finally be able to lock arms with my sister-in-law and encourage them to become fluent in both human and machine understanding. The world is going to need the combination of skills provided by a THESIS curriculum. Education leaders and workforce planners should encourage this kind of interdisciplinary learning to build a future-ready talent pipeline.
