Imagine that today, in 2026, we were tasked with creating the first college or university. Knowing all modern achievements in technology, human cognition, and rapidly changing labor market demands, would we build it as it looks now? The author believes this would not have happened.
Education has always evolved through significant breakthroughs, such as the invention of the printing press or the advent of the internet. However, the emergence of artificial intelligence (AI) represents something fundamentally different—it is a structural transformation.
This forces education leaders to ask a profound question: how do we ensure success for every student, given that each student arrives with unique experiences, varying learning speeds, and different baseline levels of confidence?
To answer this question, we must rethink the very architecture of higher education and skills development.
Currently, the skills gap in South Africa is not just an industry problem but also an inherent educational challenge. Employers are actively demanding dynamic competencies such as critical thinking, digital literacy, complex problem-solving, and adaptability.
Nevertheless, traditional education systems face a serious temporal misalignment. Industrial changes occur over months, whereas updating curricula takes years to develop, approve, and implement. By the time a curriculum reaches the classroom, the market has often moved on.
When analyzing problems within institutions, one undeniable fact must be emphasized: teachers are not failing. Rather, the traditional education system places impossible tasks before them. They are expected to teach huge classes, constantly develop changing programs, grade endless amounts of work, support struggling students, and fulfill numerous administrative duties, all while adhering to strict accreditation requirements and conducting research. How can one person provide meaningful, individualized attention to every student under the pressure of the traditional model? The reality is that this is impossible.
For decades, the system required students to adapt to the rigid structure of education. It offered a uniform pace, a single explanation, a singular method of assessment, and one path to success. However, reality dictates the opposite: every student arrives differently, possessing varying levels of language proficiency, prior knowledge, and digital skills. The fundamental shift is that education must adapt to the learner.
To achieve this goal, we must stop measuring mere 'activity.' Traditional systems largely rely on tracking attendance, assignment completion, and module finishing as substitutes for the learning process. But completion does not equal understanding. In the current paradigm, we often learn that a student has not grasped the core material only weeks after final grades have been issued.
What if we could detect confusion the moment it arises? This can be achieved by implementing an advanced, AI-driven adaptive platform for conceptual skill tracking. When learning and assessment occur at a granular conceptual level, rather than at the end of a rigid multi-week module, AI can instantly identify a specific student misconception. It can seamlessly offer diverse explanations, alternative examples, and varying levels of complexity, allowing diverse learners to follow different paths toward the same successful outcome.
This is where the true operational power of AI in education manifests. AI does not replace educators; on the contrary, it equips them with superpowers. By freeing teachers from administrative and routine burdens, AI allows them to focus their limited time on what they do best: human-led teaching, mentoring on complex problems, and empathy.
Consider how AI takes on the heavy lifting to enable this human-centered approach:
However, these technological advancements cannot simply be imported from Silicon Valley and applied in our institutions. They must be developed in South Africa, created by South Africans, and specifically adapted to local realities. An effective AI-based education ecosystem must closely align with our local learning requirements, be securely built around the realities of the National Qualifications Framework (NQF) and the Quality Council for Trades and Occupations (QCTO). It must be designed from scratch to meet the diverse needs of our learners, acknowledging our unique socio-economic constraints and opportunities.
Furthermore, it is important to remember that education does not end with graduation; it concludes with real impact. We must shift our institutions' focus to preparing graduates ready for the future who directly address actual industry needs. To ensure such alignment, institutions and corporate partners must rely on a data-driven impact assessment system that tracks real employment and graduate outcomes. By measuring apprenticeship success, internship performance, and actual post-graduation employment results, we move beyond intellectual learning to measurable, sustainable economic impact.
We stand at the threshold of a new era. We finally have the technological tools to create a continuous, personalized, and evidence-based system that is entirely learner-centric, heavily supported by AI, yet deeply and beautifully managed by humans.
The author leaves all institutions, TVET colleges, and higher education leaders with this challenge: instead of asking how to seamlessly integrate AI into existing outdated systems, ask yourselves: if we were designing education from scratch today, knowing what is possible with AI, would we build it the same way?
Artificial intelligence (AI) is often viewed in extreme terms: either as a threat that will replace workers or as a tool that facilitates the next wave of growth and productivity. However, the actual picture is likely to be more complex. The potential impact in South Africa will probably differ from what is observed in economies like the US, although developments there may offer some clues about what to expect locally.
Studies by the International Monetary Fund show that about 40% of global employment is somehow affected by AI. In developed countries, this figure rises to approximately 60%. Goldman Sachs predicts that over the next decade, AI will affect around 300 million jobs worldwide.
Interestingly, we are not currently seeing mass job losses. Instead, AI appears to be transforming how people enter the labor market and advance their careers. The greatest pressure is felt in the service sector and at entry-level positions, where companies may be more cautious about creating new roles than before.
The impact also depends on the composition of the workforce. Positions that are highly administrative, repetitive, routine, and process-based are most at risk. Conversely, higher-level positions seem more protected. These include jobs where experience, judgment, and oversight are important, especially those related to evaluating AI-generated results and determining their accuracy and relevance.
There is also the argument that while AI may eliminate some jobs, the technology will likely create new ones. Roles such as programmers, engineers, and process developers may benefit from these changes.
In the US, graduate absorption has slowed down as companies have been less active in creating new vacancies than before. A study by IESE Business School showed that the wages of junior employees in companies affected by AI decreased after the launch of ChatGPT. Even for those who find jobs, wage growth has been unfavorable.
In a country like South Africa, where the economy already faces a significant youth unemployment problem, many graduates are already struggling to find meaningful first opportunities. If AI reduces the need for entry-level positions or slows their creation, it could further complicate the transition from education to work.
This is both a social and a business issue. Many organizations naturally invest in technology to improve margins, but they also need to look beyond short-term efficiency. Succession planning, knowledge transfer, and capacity building remain critical. If businesses stop attracting and developing young talent internally, they risk weakening the very pipeline that will provide future leaders and oversee increasingly complex systems.
The same applies to how AI is beginning to merge with robotics. In manufacturing, the future is not just robotics, but the integration of robotics and AI. This shift may increase the demand for highly skilled technical oversight while reducing the number of routine positions. For a country already grappling with inequality, the issue shifts from jobs displaced by technology to how workers prepare and equip themselves for the roles that technology creates.
For workers, AI technical literacy is important, but human capabilities that are harder to automate—including judgment, relationship building, accountability, and the ability to interpret results in context—are equally vital.
From an investment perspective, it is important to seek out companies that do not focus solely on margin expansion. There is a natural limit to cost savings, whereas growth is less constrained. AI strategies should increasingly be evaluated based on their contribution to revenue growth. The winners will not be the companies that automate the most, but those that use AI for growth while maintaining judgment, accountability, and the talent pipeline that sustains the business over time.
The Vice Presidency for Science, Technology, and Knowledge-Based Economy emphasized the need for a comprehensive strategy to expand artificial intelligence (AI) education from the school level to universities. According to Emaddin Fatemizadeh, head of the Secretariat of the Headquarters for AI Development and Application, the future of the global economy and technology will be deeply shaped by AI.
Within these goals, the headquarters has defined priorities, including supporting AI training programs, strengthening cooperation with universities, and developing domestic educational content. The Ministry of Education began AI training for 200,000 students in March after developing the Iran Digital national program. Furthermore, the Ministry of Science, Research, and Technology completed the AI action plan in collaboration with the Vice Presidency for Science, Technology, and Knowledge-Based Economy.
