By Sergei Bazylik, PhD (University of Chicago)
When one imagines the future of education, they usually picture the integration of new technologies and digital tools. Now, schools and universities are evolving from loading knowledge and facts into students’ heads to teaching how to think, question, and change together with the world and the economy around them.
Learning That Never Ends
For much of the 20th century, education was a single chapter of life for most of the working population: they studied, earned a degree, and worked until retirement. That rhythm has vanished, potentially forever. The modern professional switches careers multiple times, and every transition requires new skills.
Artificial intelligence can dramatically reduce the cost of retraining. A chatbot can help you understand a policy, practice for an interview, or learn the basics of a new discipline in hours, or sometimes minutes, with explanations of above-average quality and expertise. Extended and formal programmes are gradually giving way to shorter learning loops integrated into daily work.
But as information becomes limitless, its interpretation becomes an even scarcer resource. Machines can generate answers and reports, but they are far less adept at providing contextual perspective. Fundamental disciplines such as logic, statistics, and history are returning to the centre of learning because they teach how to reason and synthesise. AI amplifies those who know how to learn and evaluate, and exposes those who wait for instructions.
From Fixed Roles to Fluid Skills
Universities once operated like production lines with students at the entrance and graduates on the exit, while diplomas virtually guaranteed employability. That industrial model no longer fits an economy built on constant change.
Routine work that follows clear rules has been automated first. What remains valuable are structural thinking, creativity, and the ability to connect causes to consequences. Fundamental sciences and knowledge regain importance not because they deliver immediate answers, but because they train people to build frameworks for solving unfamiliar problems and formulate key questions. The winners in tomorrow’s labor market will be those who can redefine questions faster than others can memorise answers.
How Businesses Learn to Learn
Corporate education is undergoing its own revolution. Early experiments added AI to existing training routines — automated tests, personalised quizzes, digital coaches. But the fundamental shift begins when learning becomes part of a firm’s operating system.
Some firms (e.g., management consulting firms) have already built private GPT models trained on internal data. Instead of generic advice, employees can ask, “How did we solve this issue before?” or “What lessons did we draw from past projects?” The role of the knowledge architect — someone who curates and structures institutional memory — is emerging fast. The businesses that outlast disruption aren’t the ones that plan best — they’re the ones that keep learning and iterating. AI can hold the data, but only people can make sense of it with intuition and context.
When Knowledge Has No Borders
Artificial intelligence is erasing the old geography of education. Any teenager in developing countries can follow MIT lectures in real time; a manager in Europe can study with a tutor in South America. Knowledge is becoming borderless and multilingual.
A new divide is emerging — not between those who have access to knowledge and those who don’t, but between those who are recognised for it and those who aren’t. Online certificates can build skills, yet they rarely build a reputation. Prestigious diplomas still act as signals of trust, networks, and credibility. And in a world full of AI-polished résumés, genuine human validation — a recommendation, a reputation earned through experience — matters more than ever.
Nevertheless, technology gives us a chance to narrow some of the old gaps. AI enables people from smaller economies to showcase their capabilities directly to employers and investors worldwide, without relying on intermediaries. Inequality won’t disappear, but it will have a different nature: it will depend on how quickly we learn, not where we happen to be born.
The Human Element Returns
AI is unlikely to completely replace teachers, but it will definitely change teachers’ work. Algorithms can check answers and summarise materials, but they are far less effective in detecting confusion in students’ eyes or sparking curiosity in an exhausted classroom. Teachers are becoming navigators — guiding students through a sea of information, helping them find meaning and personal relevance.
The most valuable classrooms, whether online or offline, will balance human warmth with a machine’s precision. Teachers will act as partners in the discovery journey; students as co-creators of knowledge. Algorithms will help handle repetition, leaving more space for reflection anddiscussion.
And in a world with access to instant answers, the valuable skill will be asking better questions. That’s what will keep learning alive, relevant, and efficient.
Education as a Living System
By the next decade, education will likely cease to be a self-contained sector. It will operate more and more as society’s nervous system, linking science, business, culture, and policy through a continuous feedback loop — to keep interpreting, adapting, and deciding what progress should mean in a world where machines can do almost everything else.
