Human-Centred AI and Future Skills
Abstract
This paper explores the linkages between human-centred artificial intelligence and future skills using a conceptual lens. It argues that equipping people for an AI-enabled society cannot simply involve imparting technical skills to enable them to utilise specific AI technologies. Future readiness involves an interplay of different competencies such as AI literacy, critical thinking, creativity, communication, ethical reasoning, collaboration, adaptability, and lifelong learning.
From a conceptually informed perspective, the paper investigates the changing nature of work, the role of AI literacy, the significance of human capabilities, and the roles of educational institutions, employers, and policymakers. A conceptual framework is proposed in which effective human-AI collaboration requires interaction among technological comprehension and cognitive, creative, social, ethical, and adaptive capacities. The paper will conclude in a way that the future depends on people trying to understand, evaluate, guide, and appropriately use AI technologies.
Keywords: artificial intelligence, human-centred AI, future skills, AI literacy, human-AI collaboration, workforce development.
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Introduction
AI applications now touch many parts of our social and professional lives, from searching for information and analyzing data to translating languages, creating content, helping with business decisions, supporting research, and automating everyday tasks. This brings up important questions, especially about jobs — people wonder if artificial intelligence will replace human workers. While that’s a common concern, it doesn’t tell the whole story.
According to the World Economic Forum (2025), employers project considerable changes to the required set of skills possessed by the workforce up to 2030, when “technological” skills are projected to grow at the same time as “creative thinking, resilience, flexibility, analytical thinking, leadership, and collaboration.” The organization further notes that “nearly 40% of workers’ core skills may change over the next decade”.
What does this mean for education? The OECD (2025) argues education systems must consider what knowledge, skills and attitudes our learners will need to thrive in an increasingly capable AI landscape. A more recent publication by the OECD and European Commission (2026) highlights “AI literacy” — being able to understand AI, critically evaluate its output and utilise it ethically and creatively.
In this context, I examine the role of AI and future skills from the perspective of human-centred AI, arguing that AI should be developed to augment human capability rather than the other way around. This means preparing ourselves not only for specific jobs but also with the capabilities needed to use technology effectively throughout life. As the nature of work changes, these capabilities include maintaining independence, being creative, ethical awareness, strong communication skills, and lifelong learning capabilities.
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Understanding Human-Centred AI
To support more human-centred AI development, various stakeholders have outlined guiding principles for developing trustworthy artificial intelligence systems — including the European Commission’s High-Level Expert Group on Artificial Intelligence (High-Level Expert Group on Artificial Intelligence, 2019). Their report identified “important elements,” which include human agency and oversight, technical robustness and safety, transparency, diversity and fairness, societal well-being and privacy, and accountability.
When looking at the impact of AI on our economy from an automation perspective, one might ask what kinds of tasks involving humans could potentially be offloaded to machines. In contrast, a human-centred approach would focus on identifying those areas where the combination of people and intelligent systems could lead to enhancement. AI is often most useful for processing large quantities of information faster than a person can, while human experts remain essential for understanding context, identifying real problems, communicating with others, considering competing values, and taking ultimate responsibility for decisions.
From an educational perspective, this highlights the importance of thinking through “future skills” in terms of developing competencies relevant for working well within the context of evolving technology, rather than merely focusing on tasks that are unable to be executed currently by AI.
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AI and the Transformation of Future Skills
The future workforce will require a combination of technological skills and distinctively human capabilities. According to the World Economic Forum’s 2025 report, some of the fastest-growing areas of skill demand include “AI and big data, networks and cybersecurity, and technological literacy.” But skills such as analytical thinking, creativity, resilience, flexibility, leadership, and collaboration are also needed. This suggests that while technical skills are increasingly important, human skills still play a key role and often work alongside them.
For example, think about employees who use AI systems within their business to analyze customer information. Knowing how to operate the AI system may be helpful, but it does not necessarily mean they will make good decisions. They’ll need to understand what information is relevant, spot when they’ve got an unusual result, challenge underlying assumptions, and consider what action makes sense for their organisation. Technical literacy gets you the tool — critical thinking tells you if you can trust its outputs.
Journalists could use AI to organize what they have learned about a topic more efficiently, but verifying facts, exercising context-specific judgment, and taking responsibility for reporting remain human responsibilities.
Future skills can therefore be grouped into several connected areas:
Skill Dimension
Main Purpose
Key Competencies / Examples
AI & Digital Literacy
Understand, use, and critically assess digital technologies
AI literacy, data literacy, digital awareness, technology evaluation
Cognitive Capability
Evaluate information and make sound decisions
Critical thinking, reasoning, analysis, problem-solving
Creative Capability
Generate and develop original and valuable ideas
Creativity, innovation, design thinking, ideation
Social Capability
Work effectively with individuals and groups
Communication, collaboration, leadership, negotiation
Ethical Capability
Make responsible judgments about technology and its consequences
Ethical reasoning, accountability, privacy awareness, responsible innovation
Adaptive Capability
Respond effectively to continuous technological and occupational change
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Flexibility, resilience, lifelong learning, upskilling, reskilling
These categories should not be treated as separate subjects. A future-ready worker may need all of them simultaneously. For instance, responsible use of an AI tool requires technical understanding, critical evaluation, ethical awareness, and communication.
The central skill, therefore, may not be knowing one particular AI application. It may be the ability to learn how to use new technologies without losing the ability to think independently.
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AI Literacy as a Foundational Future Skill
However, AI literacy should not be confused with learning how to program or training to become an AI engineer. Instead, we can take guidance from the Organisation for Economic Co-operation and Development (OECD) and the European Commission (2026), who define AI literacy as “knowledge, skills and attitudes enabling learners to understand AI systems, critically assess their outputs and apply them ethically and creatively.” One of the first things students need to learn about AI is how to distinguish between an AI-generated response and verified knowledge. Students should learn to question the source and evidence behind AI outputs, identify missing context, independently verify information, and consider ethical and privacy concerns.”
Most importantly, students should understand that their learning must continue to develop despite the presence of AI. If students begin to use AI as a substitute for their own thinking, writing, research, or problem-solving, this could inhibit the development of these important capacities. UNESCO (2023) emphasizes a human-centred approach, arguing that generative AI in education should support human capacity rather than be treated as a solution to the fundamental challenges of education. ___________________________________________________________________________
Methodology
The methodology used here was based on a conceptual approach by reviewing and synthesizing relevant literature and authoritative reports from institutions.
In addition, publications that address human-centric AI, AI literacy, future skills, education, workforce transformation, and ethical AI were taken into consideration. These publications spanned various organizations including UNESCO, OECD, the European Commission, and WEF (World Economic Forum), as well as academic literature on AI literacy and human-centric AI.
Thematic analysis was conducted on selected literature for identifying commonalities with respect to competences and challenges relating to human-AI collaborations. ___________________________________________________________________________
Human Capabilities in an AI-Enabled World
These changes may develop in many ways, but one implication is clear: rather than simply diminishing the importance of human labour, artificial intelligence may enhance some aspects of human capability. Critical thinking skills will likely be more valuable as we have more access to information generated by AI systems. Creativity, too, has proven to be an important skill even with generative AI systems now able to create text, images, designs, and more.
Communication and collaboration also remain essential human capabilities. Organizations require more than just information; they also need trust, negotiation, leadership, teamwork, and relationships. While AI can support various aspects of communication, these human interactions still require understanding, compromise, and empathy.
Therefore, while AI may offer assistance, it cannot eliminate the need for effective collaboration. Ethical reasoning is another crucial capability, especially as the world becomes increasingly complex. There is not always a single right answer to complex problems, particularly when social contexts and ethical dilemmas are involved. This means human judgement must continue to be at the forefront of decision-making as artificial intelligence systems become more pervasive. Even if an algorithm does find a way to optimize outcomes from past patterns (which could happen), how can anyone know what’s truly fair, appropriate, or socially acceptable? Ultimately, such judgments require human responsibility and reflection. So rather than trying to train employees to outperform artificial intelligence on tasks, perhaps now would be a good time to teach them how to set direction, analyze output, and assume full accountability.
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Education for Human-AI Collaboration
Education is essential for preparing learners with future skills. Schools and universities have an urgent responsibility to equip learners for the future, as these skills cannot be developed only after employment begins.
As stated by the Organisation for Economic Co-operation and Development (OECD), “the expanding capacities of AI will necessitate rethinking what competencies are necessary for life and work” (2025). Education should adopt a more balanced approach, because foundational knowledge becomes even more important when assessing AI-generated information. While AI is most commonly associated with computer science, its impact spans many other domains such as law, business, medicine, journalism, education, environmental management, design, and public policy.
One way to do this is through project-based learning, in which students use AI tools to address a real-world issue and then compare AI-generated suggestions with findings from independent research. This approach can show students how to apply these technologies without allowing them to replace independent thinking.
___________________________________________________________________________Reskilling, Upskilling, and Lifelong Learning
So far we’ve talked about future skills being relevant to students, but what about current workers? Are there any other changes taking place with regard to their tasks? According to the OECD (2025a), AI is leading to increased demand for both specialists in AI and people who understand its overall application. However, upskilling and reskilling will be essential to enabling these workers to embrace the opportunities arising from AI’s adoption.
Upskilling enables a worker to develop greater capabilities in his or her current job, whereas reskilling is more likely to lead to a change in role. Both could prove important as organisations redesign roles to accommodate AI.
According to the World Economic Forum (2025), 59 out of 100 workers will need reskilling/upskilling by 2030. Of these, only 11 will get the support they need, showing the limitations when tackling this issue individually.
It’s safe to assume lifelong learning will take on even greater importance moving forward, with the real skill becoming about knowing where to look and feeling confident enough to go there, rather than having knowledge of everything at any particular moment in time.
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A Conceptual Framework for Human-Centred AI and Future Skills
This brings us back to our conceptual framework that consists of 5 interconnected elements as depicted hereafter. First, we have an element of human agency — we want to make sure people have the ability to be able to make meaningful decisions.
Secondly, the notion of AI literacy comes into play because you need to ensure people understand the technology they’re working with; otherwise, they tend to fall into two categories: either distrusting AI or over-relying on it.
The social and ethical capacities help us think about how our technology choices affect others as we interact with organisations and communities. Given that AI technologies will continue to evolve, our ability to keep learning will be key to our future-readiness.
Figure 1: Conceptual Framework for Human-Centred AI and Future Skills
Human Agency + AI Literacy + Cognitive & Creative Capabilities + Social & Ethical Capabilities + Adaptability → Effective Human-AI Collaboration → Human Development and Future-Ready Work
While AI literacy will be necessary for all humans in our increasingly AI-enabled world, we believe this framework shows that simply having technical skills won’t be sufficient if people aren’t equipped to critically evaluate information. __________________________________________________________________________
Challenges and Implications
Firstly, there are problems of unequal access — students and workers do not start out equal in device ownership, connectivity, or skills such as working effectively with AI, nor will they have access to high-quality AI systems. Thus, if AI literacy becomes an essential skill required by our educational system and employers, we need to make sure that everyone has equal access to these resources;
Secondly, the danger of over-dependence looms large, given how easy AI is getting to become ‘smart’. As people get more reliant on AI tools, they risk becoming disengaged from complex thinking processes. Our task is to ensure that learners understand when to use AI as support for their own learning rather than simply letting it act as a substitute.
Organizational Responsibility — If employers are thinking of AI as simply a way of improving their own productivity, then they’re missing out on the opportunity to help their employees grow into better workers by helping them develop skills related to working alongside AI technologies. This includes things like considering how well jobs match with this sort of transformation, how much autonomy should be given to workers when using these tools, and what kinds of transitions might occur within employment roles.
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Conclusion
The artificial intelligence revolution will change our relationships with each other, with knowledge, with education and with our jobs. This is one of those times where we need to think about ‘what matters’.
We believe the greatest impact of artificial intelligence is likely to be the shifting value of different human attributes. A human-centred approach allows us to see all sorts of ways forward that focus on making the best out of things rather than seeing an inevitable conflict between human beings and machines.
Future skills involve more than just understanding technology — they require critical thinking, creativity, communication, ethics and teamwork as well as technical capability. Human-centred AI enables us to enhance our abilities in learning, creating, solving problems, collaborating, and making informed decisions. This is why education, business, and policy must play their part in ensuring this becomes a deliberate outcome.
