Human skills are highly relevant, but they remain invisible in most labour markets; according to the 2025 World Economic Forum (WEF) report on New Economy Skills, only 72% of US job postings explicitly mentioned at least one human-centric skill. The paradox is that though employers project human skills like empathy, critical thinking and resilience are critical for innovation, these skills are underrepresented in hiring criteria.
Current debates focus on the value of the humanities and social sciences; and on whether analytical skills will compete with AI capabilities. It is plausible that as AI and robotics increasingly intersect with various fields, an exclusive reliance on manual skills will leave individuals less adaptable, even in traditional manual professions such as surgery and medicine.
Instead of resisting AI training and development, the younger population must be able to interpret and integrate AI, as it is today a major skill in the job market. We know that most students use AI for homework, but institutions also need to develop students' cognitive capacity so they can work independently without relying on AI.
AI should be used as leverage, not as compensation for a lack of competencies. Higher Education must develop concrete measures, such as incorporating more written, oral exams and project-based assessments in which students perform without any external support or contributions. Connecting these two approaches will enable and empower students to use AI on their own terms, rather than being passive users.
The traditional categorisation of soft and hard skills is changing. Students must not be limited to one silo of skills; rather, they should focus on ability and creativity, which can be called intellectual ambition, centred on critical thinking and the capacity for intellectual effort.
AI must be used as a starting point, not a destination, for students. Methodology and rigour in thinking are very important. Also, moving forward, the ability to detect AI hallucinations, problems and biases will be a critical skill. Emerging meta skills are more methodological and cognitive in nature.
To remain relevant, students must interact with AI-generated information and data insights from AI agents and creatively connect information. Achieving depth of understanding, not just surface-level knowledge, is essential and challenging.
Systems thinking, understanding how systems operate, will be critical, such as when tackling climate change. The ability to navigate technical skills and different layers of reasoning is particularly pertinent in this context. Pedagogy can evolve through complex case studies to develop logical optimisation and systems thinking.
These shifts are not unprecedented. This is not the first revolution the world has experienced; we have had other transformations and societies have organised themselves around them and developed to their fullest potential. Looking ahead, new transformations will be complex and will produce winners and losers in the reorganisation of society.
Therefore, the full risks and the opportunities for transformation must be understood. Furthermore, the sciences will also undergo a drastic change. Usually, data is organised into quantitative and qualitative categories, but AI has the potential to blur the line between these categories and open a new field of research.
Problem-solving skills and corporate diplomacy are among the most demanded skill sets amidst evolving global geopolitical developments. Corporate diplomacy refers to how to tackle problems in uncertain and tough times.
It is important to focus on developing emotional quotient, cultural intelligence and empathy. Social and ethical skills, curiosity and perspectives are critical for problem-solving. AI complements human skills and humans still need training on human-based skills like resilience and adaptability.
Educational institutions can prepare students for their first job and equip them with long-term agility and diverse interdisciplinary knowledge, enabling them not only to be experts but also to connect across knowledge sets to solve problems in the context of the social, economic and geopolitical landscape. Moving forward, individuals must be primed to integrate human and AI capabilities for sustainable living.
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