A Critique of “Soft Skills”: Why Higher Education Must Claim Human Skills in the Age of AI

InnovationGlobal Education
Written By Blair Thomson

Welcome to The Brief by Global Edvocate. Twice a month, I share insights at the intersection of global education, law and policy, and innovation. I bring a sharp mind, a soft heart, and a quiet storm, speaking with intention on what is defining and redefining our field.

I have noticed a shift in sentiment around artificial intelligence in recent months. The early conversations, often steeped in suspicion or outright hostility, have given way to a quieter resignation. AI is not going away, requiring us to develop thoughtful strategies for integration rather than avoidance. At conferences and in classrooms, I still encounter the occasional skeptic who insists it is a passing fad or that it consumes too much energy to be ethically defensible, concerns rooted in genuine values even if increasingly difficult to maintain in practice. A colleague refuses to use AI and declines to establish any guardrails for their students who might use it. They believe that even touching it means contributing to environmental harm, yet they are grading papers likely created by AI, and they aren’t guiding their students on using it as a companion. Those voices remain, but they are increasingly isolated.

I sense a change in the topics of discussions. On task forces and in conversation, the primary topic all depends on what the individual envisions with respect to teaching, research, learning, and operations. More generally, beyond ethics and use cases which dominated the discussions at the beginning (I suppose depending on your own interests and silos), is a more fundamental, higher level shift. The discussion no longer centers only on whether AI is ethical, but rather on how we can teach students to use it effectively. Our students already employ AI in creative ways. Some use it to accelerate their thinking, while others use it for what scholars call “cognitive offload,” relying on the tool to shoulder tasks that free them for other work (or play). In either case, the conversations emerging in higher education today revolve around the balance: how do we teach students to pair AI tools with the skills that make them distinctively human?

This brings me to the term I want to challenge most directly: “soft skills.” Not to be dramatic, but I loathe it. Every time I hear it my eye twitches a little. The term “soft skills” diminishes the importance of the very skills that are most needed for being functioning, empathetic humans. These capabilities matter as much for building meaningful relationships, cross-cultural understanding, and community engagement as they do for career success.

We Need Better, Common Language

The phrase “soft skills” itself originated with the U.S. Army in the 1970s to distinguish technical proficiencies, those “hard skills” like operating machinery, from the interpersonal and managerial capacities needed to lead teams. They defined “soft skills” as “important job-related skills that involve little or no interaction with machines and whose application on the job is quite generalized” (Whitmore, 1974). The distinction stuck across industries, and “soft skills” became shorthand for communication, teamwork, adaptability, and emotional intelligence. The language carried baggage. Hard skills were assumed to be essential and measurable. Soft skills were perceived as secondary and somehow optional.

This framing is misleading. The skills labeled “soft” are in fact among the most essential skills for both work and civic life, but the term can be imprecise and devalued, even when employers consistently report that these skills are decisive for employability and long-term success.

I am not alone in wanting to rename these skills. Colleagues and practitioners use alternatives. I myself have used “critical skills, critical for the human experience” whenever I can. (I am reminded of Regina George: Stop trying to make critical skills happen.) Each has strengths but also weaknesses.

  • Foundational skills suggest they are the ground floor for everything else, but it could be misread as only applying at the beginning of education as basic or introductory skills rather than ones that need lifelong nurturing.

  • Essential skills are positioned as non-negotiable. The term carries weight in national policy frameworks, such as Canada’s Skills for Success, but risks sounding too generic in academic or global contexts.

  • Durable skills emphasize longevity but can feel commodified, treating these capacities as static assets to be maintained rather than dynamic qualities that develop through relationship and practice. While we should assess growth in human skills, we should also resist language that implies they operate like equipment with predictable lifespans.

  • Meta skills are already in use in Scotland’s Skills Development framework, stressing higher-order adaptability and systems thinking, yet the term may be unfamiliar outside policy circles, and in a wider cultural context “meta” is often associated with Facebook’s corporate rebrand or internet slang, which risks diluting its educational meaning.

  • Transferable skills emphasize usefulness across roles but feel transactional, as if the only reason to cultivate them is to move from one job to another.

  • Power skills carry a corporate gloss that feels more like marketing language than educational terminology.

  • Critical skills resonate with me most, but since critical thinking is itself a human skill, the overlap creates redundancy.

Ultimately, I find human skills most compelling. These are the skills that define us as people: the ability to collaborate, empathize, adapt, and lead with integrity. They are not “soft.” They are the hardest to teach, the most essential to practice, and the most irreplaceable in a world increasingly saturated by technology.

AI Makes Human Skills More Urgent

Artificial intelligence is amplifying the need for human skills rather than erasing it. Yes, AI can produce text, analyze data, and even approximate creativity, but it cannot replicate empathy, ethical judgment, intercultural understanding, or the ability to resolve conflict in real time.

This shift toward human skills isn't happening in isolation. My colleague Girish Ballolla, founder and CEO of Gen Next Education, recently spoke about the “Human Advantage Economy.” His keynote at the Summer Institute on International Education Japan offers inspiration for anyone navigating this space.

If students rely exclusively on AI without developing their human skills, they risk becoming passive operators of tools rather than active shapers of their own futures. The danger is not that AI will replace them but that they will allow themselves to be diminished by it.

International education makes this particularly clear. AI can translate words, but it cannot translate meaning across cultures. It can summarize an argument, but it cannot sense when tone, context, or relational trust are at stake. When students travel abroad or engage in intercultural learning, they discover that success is rarely about technical precision alone. It is about navigating ambiguity, listening with empathy, and adapting in ways that honor human dignity. They are not interchangeable behaviors that machines can reproduce. They are situated, relational, and deeply human.

Human Skills and the Future of Higher Education

Employers have been consistent. According to McGunagle & Zizka (2020), the five highest-ranking skills were being a team player, self-motivation, verbal communication, problem-solving, and being proactive. These are foundational, especially in a world where AI can handle much of the “hard” or technical output.

In international education, the evidence is equally strong. Research shows that students who participate in study abroad and other global learning experiences gain the human skills that employers value: resilience, adaptability, and problem-solving across contexts (Jones, 2013). The irony is that while employers keep emphasizing these skills, higher education has too often relegated them to co-curricular programming or left them unassessed. McGunagle & Zizka (2020) describe a similar gap: though STEM educational programs include many technical and discipline specific outcomes, human-oriented competencies like teamwork, verbal communication, self-motivation, and problem-solving frequently top the list of what employers report as lacking.

Holmes, Bialik, and Fadel (2019) suggest that education should adapt by embedding “skills, character, and meta learning into the knowledge domains.” This is precisely what universities must do: stop treating human skills as optional extras and start embedding them in the curriculum, assessment frameworks, and international learning outcomes.

Hurrell, Scholarios, and Thompson (2013) emphasize that the meaning and application of soft skills are shaped by context and job type, which reinforces the need for higher education to teach them through experiential and global learning rather than assume they will develop automatically.

If AI accelerates technical productivity, then higher education must accelerate what it means to be human. That requires a deliberate effort to reframe, teach, and assess human skills as core to the mission of universities.

Solutions by Role

How do we move from critique to action? We need to think about what faculty, advisors, administrators, and even ourselves can do differently.

Faculty and the Classroom

  • Integrate AI with critique: Design assignments where students use AI to generate drafts or summaries but must then analyze bias, cultural framing, or ethical gaps.

  • Assess collaboration and adaptability: Group work should not be an afterthought. Grade students on how they resolve differences, adapt to challenges, and lead with empathy. Being a team player was the top skill rated by employers in the McGunagle & Zizka (2020) study; verbal communication, problem-solving, and being proactive also ranked very highly. If faculty do not design assignments and assessment that give students feedback on these, graduates may be underprepared despite strong technical skills. Design comprehensive human skills assessment by creating rubrics for collaboration, empathy, adaptability, and cultural sensitivity in both group and individual assignments. Train students to give peer feedback on communication and teamwork, making these skills visible and improvable across all coursework.

    • I, for one, have created a rubric for our study abroad faculty to integrate into their syllabus and guide them on outcomes and assessment for their faculty-led programs.

  • Teach reflection explicitly: Encourage students to articulate how they grew in resilience or intercultural competence, not just what content they mastered.

  • Use "AI + human" project structures: Have students complete a technical task with AI, then present findings to a diverse audience requiring cultural translation and empathy.

Advisors

  • Help students craft growth narratives: Use frameworks like “When I encountered X challenge, I developed Y skill by Z approach” and guide perspective-taking exercises about their impact on host communities.

  • Model empathetic advising: Advising itself is a human skill laboratory. Active listening, reframing, and guiding students to their own agency models what they must practice in the workforce.

  • Contextualize AI as a collaborator: Reinforce that AI is a tool that still requires judgment, relational nuance, and ethical boundaries.

  • Practice "perspective-taking exercises": In advising sessions, ask students to consider how their experiences, either at home or abroad, looked from their community or host community’s perspective.

  • Create "human skills portfolios": Help students document specific examples of cross-cultural problem-solving, conflict resolution, and adaptive leadership.

Administrators

  • Reframe outcomes: Shift program metrics from transactional outputs (numbers enrolled, visas processed, partnerships signed) to human outcomes (growth in intercultural competence, communication, and collaboration).

  • Provide professional development: Train staff and faculty to integrate AI thoughtfully while still centering human skills.

  • Embed global competencies: Internationalization strategies should highlight not just mobility, but the cultivation of human skills as a core graduate attribute.

  • Redesign program evaluations: Move beyond satisfaction surveys to assess growth in specific human competencies before, during, and after programs.

  • Establish "human skills mentorship networks": Connect students with alumni who can speak to how they use these capabilities in their careers.

  • Partner with employers for "human skills internships": Create placements specifically designed to develop and assess collaboration, cultural intelligence, and ethical reasoning.

Holmes, Bialik, and Fadel (2019) note that much of AI in education “has been designed (whether intentionally or not) to supplant teachers or to reduce them to a functional role, and not to assist them to teach more effectively.” Administrators must resist this drift. AI should not flatten education into automation; it must amplify the relational and human aspects of teaching and advising.

Daily Life - For Students and For Ourselves

  • Encourage reflective practice: Journaling, storytelling, and structured dialogue help students internalize human skills.

  • Model compassion in community: Students and staff can embody empathy and ethical interaction in day-to-day decisions.

  • Teach students to pause: Before hitting “submit” on AI-generated work, ask whether it builds trust, clarity, and connection.

  • Institute "reflection rituals": Weekly 10-minute discussions where students share one moment they navigated cultural difference or interpersonal challenge.

  • Practice "empathy mapping": When conflicts arise, guide students through exercises to understand multiple perspectives before problem-solving.

The Power of Precise Language

Language shapes reality. When we call the most essential human skills “soft,” we signal that they are secondary. In the age of AI, nothing could be further from the truth. These skills are critical, foundational, and deeply human. They are the competencies that employers value, that international education uniquely cultivates, and that no machine can replace.

Higher education must stop treating them as optional extras or assuming students will develop them automatically through exposure. Our tasks are to teach students how to use AI effectively and, most importantly, to ensure they remain fully human in the process. The future will belong not to those who rely on machines, but to those who pair technology with empathy, judgment, and the relational capacity to build a more just and connected world.

I’m curious about your experience. Do you cringe when you hear “soft skills”? How are you teaching or modeling human skills in your role? What language do you use on your campus or in your workplace, and does it matter?

References (please no comments on my citations - I’m trained in Bluebook):

Blair Thomson https://www.abthomson.com/
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