Over the past few weeks, Dr. Donald Patrick Lim delivered three commencement speeches — and each time, he found himself confronted with the same uncomfortable question: should he congratulate the graduates, or apologize to them?

Writing in BusinessWorld, Lim acknowledges that the Class of 2026 deserves congratulations. Finishing college remains a major accomplishment, “particularly in a country where families make tremendous sacrifices to put their children through school.” But, he adds, “I also could not shake the feeling that we had prepared these young people for a world that was already changing before they could fully enter it.”

The apprenticeship that built a profession

For generations, Lim observes, there was a fairly predictable path into professional life: study hard, earn a degree, find an entry-level job, and gradually learn the profession. Junior accountants prepared reports and reconciliations, young lawyers did research and reviewed documents, new marketers prepared presentations and wrote first drafts, analysts gathered information and worked on spreadsheets, and young programmers wrote basic code.

These jobs were sometimes repetitive and boring, but they served an important purpose: “They were how we learned.” Most senior executives today probably remember early-career work they would never want to do again, Lim writes, yet those experiences taught them how organizations actually worked — observing bosses, learning from experienced colleagues, making mistakes while the consequences were still manageable, and gradually developing the judgment needed to take on greater responsibility.

Artificial intelligence, he argues, is beginning to disrupt that apprenticeship model. Many tasks traditionally assigned to young employees — research, summaries, basic analysis, presentations, first drafts, routine coding, and administrative work — are precisely the tasks AI can now perform remarkably well, increasingly completed in minutes. For companies under pressure to improve productivity, the attraction is obvious, but Lim points to an unintended consequence that deserves more attention.

“If we automate too much of the work traditionally performed by junior employees, where will they acquire the experience necessary to become senior employees?” he asks. If companies need fewer junior accountants today, where will tomorrow’s finance leaders come from? If young creatives no longer struggle through first drafts, how will they develop the instincts required to become creative directors? And if junior analysts increasingly outsource analysis to machines, how will they develop the judgment expected of senior executives?

“We could become more productive today while inadvertently weakening our leadership pipeline for tomorrow,” he warns.

Lim’s warning echoes a debate now unfolding well beyond the Philippines. The International Monetary Fund estimated in 2024 that almost 40 percent of global employment is exposed to AI, and a 2025 analysis of U.S. employment data by researchers at Stanford’s Digital Economy Lab found that employment among workers in their early twenties had declined relative to older workers in the occupations most exposed to AI — including software development and customer service, precisely the entry-level territory Lim describes.

AI as a human capital issue

Boards and CEOs, Lim writes, need to look at AI not simply as a technology or productivity issue but also as a human capital issue. The discussion cannot only be about how many processes can be automated or how much cost can be removed; companies should also be asking who they are developing to lead their organizations 10 or 20 years from now.

The usual response — that workers simply need to “upskill” — is used too casually, he argues. “Upskill into what?” Telling a 21-year-old graduate to learn AI is not particularly helpful when the technology itself is evolving so quickly.

Instead, Lim believes young people need three capabilities: AI literacy; human skills such as communication, creativity, critical thinking, leadership, and judgment; and, most importantly, deep expertise in a particular field. The future will not necessarily belong to the person who knows AI best. It may belong to the accountant who uses AI better than other accountants, the doctor who uses AI better than other doctors, or the marketer who understands both marketing and AI better than other marketers.

“AI is ultimately a multiplier of capability. What it multiplies still matters,” he writes.

Lim also worries about a new kind of digital divide. The old divide separated those who had access to technology from those who did not; the emerging divide may separate those who are augmented by AI from those who are displaced by it. Someone with strong education, professional experience, and access to technology can use AI to become dramatically more productive, while someone entering the workforce without those foundations may find himself competing not only against other graduates but against experienced professionals empowered by increasingly capable machines.

MAP’s education-to-employment push

The column also highlights work Lim has been advocating through the Management Association of the Philippines (MAP). From the perspective of the MAP Education Committee, employability should become a shared national outcome of the Department of Education, the Technical Education and Skills Development Authority (TESDA), and the Commission on Higher Education (CHED), moving beyond curriculum alone toward a much more seamless education-to-employment pipeline. The urgency is particularly sharp in a country whose IT-BPM sector — one of the largest employers of fresh graduates, directly providing work to more than a million Filipinos — has itself been assessing how AI will reshape customer service, back-office processing, and other services long staffed by entry-level hires.

One promising reform, he writes, is structured, long-duration workplace immersion before graduation. MAP has been working with educational institutions and companies on structured internships in which industry becomes not merely the eventual employer but a co-educator. The principle is simple: “instead of studying first and learning how to work later, students should increasingly learn while working and work while learning.”

A structured internship, potentially lasting as long as one year, lets students experience how organizations actually operate before they graduate — encountering real deadlines, real customers, real bosses, and real problems while developing technical competence alongside professional habits such as teamwork, communication, problem-solving, and workplace judgment.

This becomes even more important in the age of AI, Lim argues: if technology is eliminating some of the traditional entry-level tasks through which generations learned their professions, new opportunities must be created for young people to acquire experience earlier, with the goal of diminishing the gap between school and industry.

Imagine, he writes, if Filipino students graduated not only with a diploma but with substantial professional experience. By the time they enter the labor market, they would already understand workplace culture, have worked alongside professionals, used AI in actual business environments, and demonstrated their ability to contribute. “They would not simply be graduates looking for their first opportunity. They would already be young professionals.”

Responsibilities of universities and business

Universities, Lim cautions, must recognize that putting ChatGPT into classrooms does not make students AI-ready. Students need to know how to use AI — but also how to question it, verify what it produces, recognize when it is wrong, and know when human judgment should override the machine.

Businesses have an equally important responsibility, he adds: “If AI removes some of the first rungs of the corporate ladder, companies cannot simply tell young people to jump higher. Industry must help build a new ladder.”

The graduates Lim addressed are entering one of the most uncertain labor markets in generations: some jobs will disappear, many will change significantly, and new professions will emerge that cannot even be named today. His advice to them is not to compete with artificial intelligence, nor merely to become good users of AI. “Become very good at something and then use AI to multiply that capability,” he writes.

Those who lead businesses, universities, and public institutions carry their own responsibility, Lim continues: “We are the ones introducing these technologies and pursuing the productivity gains they promise. We cannot celebrate those gains while leaving the next generation to deal with the consequences.”

So yes — congratulations to the Class of 2026, he concludes, and perhaps an apology as well: “We prepared them for a world that changed before they could fully enter it.” But an apology is not enough. If AI is removing the first few rungs of the ladder that his generation climbed, then education, government, and industry must work together to build a new one.

“The graduates are ready to climb. Our responsibility is to make sure there is still a ladder,” Lim writes.

About the author

Dr. Donald Patrick Lim is the founding president of the Global AI Council Philippines and the Blockchain Council of the Philippines, and the founding chair of the Cybersecurity Council, whose mission is to advocate the right use of emerging technologies to propel business organizations forward. He is currently the president and COO of DITO CME Holdings Corp.