Briefing
Building a playbook for data-ready success
Stories from the 2026 QS EduData Summit
The 2026 QS EduData Summit explored how universities can build a playbook for data-ready success. These are the key stories and insights from the event.
By Anton John Crace
18 June 2026
Reinventing education for the AI era: An interview with Charlie Ang
Charlie Ang is a corporate futurist, AI strategist, and future of work expert who helps organizations and leaders navigate the intelligence-abundant world. For over 15 years, he has been analysing how emerging technologies and global trends are reconfiguring business, industries, and the nature of work.
QS Insights sat down with him on the eve of his keynote no Reinventing education for the AI era to unpack his predictions on the future of education, universities, skills and employment.
What can we look forward to in your keynote?
In the keynote, I will provide my take on reimagining education for the AI era. To offer an outsider's perspective on what's good and stays, what's becoming obsolete and needs to go and how education can be fit-for-the-AI-future.
I will use the First Principles to dissect and deep dive into the fundamentals of education; the same approach I use to reimagine other industries and professions for the age of AI.
There’s a lot of concern around the future of the workforce and future of education, primarily the importance of education, as we move through AI, automation and other, monumental changes. Do you see higher education surviving the next 10 years?
Higher education will hit a crisis point, if it stays largely the same in 10 years’ time. It will be impacted on both ends, from the supply and demand sides.
On the supply side of talent, would the youth still see formal higher education as the choice ticket for entry into the workforce? Or would more fit-for-purpose and cost-effective options, such as youth entrepreneurship, private AI-native schools or corporate universities, emerge as viable alternatives?
On the demand side of talent, will companies still view degrees and diplomas as credible signals for employment and selection?
Institutes of Higher Learning must urgently reinvent how they educate and rethink what they educate for. The world, that is rapidly accelerated by AI, will look dramatically different in ten years, so there is no time to waste. By then, I expect many new types of higher value jobs but a good portion of them will be unfilled due to the lack of suitable talent.
On the other hand, a significant percentage of the jobs we educate students for today will no longer exist. We face the risk of lost generations and opportunities if tertiary educations fail to transform in time.
What does the future of education look like more broadly?
This is the first time in human history that we will be competing and collaborating with a form of intelligence that equals or, even, exceeds ours. This puts tremendous pressure on educational systems not only to change but to reinvent.
Broadly speaking, we know that higher order capabilities such as agency, creativity, judgment, synthesis and adaptability are essential to thrive alongside intelligent machines. But at a much higher bar beyond today's levels.
I believe that, moving forward, these competencies should be the core, and not incidental, outcomes of education. They should be at the centre, and not on the edges, of how we design, assess and deliver education. The challenge is how we can nurture these advanced skills at speed and scale.
In addition, AI collapses the cost of instruction and assessment, enabling more personalised, accelerated and creative pathways for learners.
We must utilise the new possibilities enabled by AI in education to counter the rising challenges and demands created by AI at the workplace.
You also work across organisations, from leaders to employees. What are some of the disconnects you see between priorities on AI and education?
By and large, what I hear is that schools are producing graduates who mirror, instead of complement, the capabilities of AI. Very often, the output of what they can delivered can be matched by AI, if not now, then in the near future. This, therefore, dilutes the attraction of hiring young graduates. This drives the urgency for universities to adapt much faster to cope with the increasing rate of change AI is unleashing in the workplace.
Unis should build students’ instincts
Universities provide the foundation for knowledge acquisition but should do more to assist them develop their ability to help, according to the opening keynote speaker of the 2026 QS EduData Summit in Singapore.
Eve Ang, Founder and CEO of Immunova AI, told delegates that as students face an uncertain future due to AI disruption, developing students’ instincts to identify and address societal challenges was vital.
“One capability that can still outrank [uncertainty] in the current age of AI, is the instinct to find a problem worth solving in our communities,” she said.
Ang, who is 18 years old, developed Immunova AI, an open-source AI framework to determine which treatments cancer patients would best respond to, after identifying data gaps in oncological predictions after her mother was diagnosed with breast cancer.
“Education gave me the research and scientific foundation for me to even spot this gap and the execution to make it a reality,” she told delegates.
“What made me different was the fact that I was able to spot this and make an impact out of it, and that instinct to not only see the gap but see how I could make a difference within that gap is something that I really truly believe is the defining characteristic for youth in this next generation.”
During her keynote, Ang also highlighted five other young people from India, Portugal, Mexico, Kenya and the United States who were also developing socially focussed projects.
Projects included a robot to plant trees in isolated and dangerous areas, AI translation services that are culturally sensitive, and developing low-emission cooking stones.
Ang added that universities should consider how to set up ecosystems that push students to apply knowledge beyond its discipline.
“How do you shape your institutions, the policies, your lessons, your lectures, your degrees, so that the students feel empowered to have this instinct that they can spot [challenges],” she said.
“Let's imagine what else we can do to build this.”.
“Productive friction” imperative to education relevancy
As AI usage among students and academics continues to ramp up, universities must ensure they are building in “productive friction” to avoid AI systems that completely remove cognitive load, according to experts at the QS EduData Summit.
Speaking on the panel, “The State of Data in Higher Ed (What Does Readiness Look Like?),” experts warned that overreliance on AI could see knowledge acquisition and critical thinking ability diminish.
“You get a lot of these tools that students are using, academics are using, and they are driven mainly by the data,” said Dr Chan Taizan, Chief Data Officer at the National University of Singapore.
“Because the data, the knowledge, is so readily accessible and it is presented in such a nice, concise, digestible form, that makes us potentially lose the skills [we’ve mastered over years]”.
To combat this, Dr Maria Spies, Chief Innovation Officer at QS Quacquarelli Symonds, highlighted recent papers on “productive friction”, the creation and use of AI models that build in difficulty, rather than simply providing answers outright.
She added that this followed previous understandings on the zone of proximal development, the gap between what learners can do without assistance and what they can do with assistance. She added that universities need to be at the forefront of their development.
“I think that's where things are heading if the higher education community worldwide, and academics particularly, engage, because big tech giants don't have to do it. It's going to be us that has to do it,” she said.
Director of Strategic Insights at RMIT University in Australia, Angel Calderon, meanwhile said that academics and students must be “ready with judgment” when it comes to AI.
“AI is an enabler, not a decision maker,” said Calderon.
“AI should inform the decisions, not replace the human judgment, and that's the critical thing.”
Shared language and currency key to addressing skills gap
Universities can use Singapore as an example of success in addressing the skills gap, delegates heard at the 2026 QS EduData Summit.
Hosted in Singapore and themed “Build your playbook for data-driven success”, the event attracted over 350 delegates to work through challenges using data.
On the panel, From Data to Policy: The Singapore Model, experts used the host country as a case study for good data usage in addressing the skills gap. Among the examples discussed were a shared language of skills and up-to-date data.
“We have a common skills language and skills taxonomy,” said Chelvin Loh, Director of Skills Intelligence and Planning Division at SkillsFuture Singapore.
“That allows both employers, training providers, institutions for higher learning, and individuals to speak the same language. Using the same language, you can then tell, for example, when an individual signals that they have this skill, the employer understands what the skill means.”
A governmental body under the Ministry of Education, SkillsFuture Singapore has been a global pioneer in rolling out lifelong learning to Singaporean citizens.
Loh, however, warned that a shared language can also be a double-edged sword if not effectively kept current.
“If the common language is not updated, then you start to train based on skills that are not relevant anymore, so there is also a lot of challenge to see how we can constantly stay ahead,” she said.
Likewise, data currency is also key for ensuring that skills development remains aligned with skills needs..
“We started to buy job posting data, and today we buy those on a monthly basis. We also buy overseas job posting data,” she said.
“Can the overseas job posting give us a glimpse of what are the skill sets we might need tomorrow?”
Associate Director, Office of Impact at Singapore Management University, Dr Han Ei Chew, meanwhile said that while much of the software and hardware within Singapore was easy to replicate, the underlying culture was the largest challenge for other countries.
“What the policymakers do quite a lot is to engage the academics and industry in conversations,” he said. However, he noted that this collaboration was successful when developed over time and with consistency, warning that urgent problems were far more challenging to address collaboratively.
MEET THE AUTHOR
Anton John Crace is Editor in Chief of QS Insights. He has been writing on the international higher ed sector for over a decade. His recognitions include the Universities Australia Higher Education Journalist of the Year at the National Press Club of Australia, and the International Education Association of Australia award for Excellence in Professional Commentary.