Over just a couple of years, the simple equation of a science, technology, engineering, or math (STEM) programme = best chance at a well-paying and secure job is becoming more complex. This is because of increasingly sophisticated artificial intelligence (AI) in the workplace and the profound worry among young adults that AI could jeopardise their career prospects. “Future proofing” (for the impact of AI) may end up being the Oxford Word of the Year.

This is radically changing the way students decide what to study, and it is prompting institutions to review their programming, curricula, and marketing. Educational agents, too, are noticing the shift. They are directly in touch with students in local markets who now consider an AI-resistant – or AI compatible – career to be essential.

In the 2010s, the big disruption for higher education was MOOCs (Massive Open Online Courses). In the 2020s, it is most definitely AI.

How international students choose programmes

For international students, a strong return on investment (ROI) from higher education is crucial. Often, they pay more in tuition than domestic students do; have significant travel costs; and must navigate visa settings that affect their ability to work in host country. They are taking an even bigger risk by pursuing higher education than domestic students are.

They choose STEM programmes not just out of interest, but also because host countries tend to have more favourable visa policies for STEM graduates than graduates from other fields. For example, the STEM extension of Optional Practical Training (OPT) in the US provides three years of work experience rather than one with regular OPT. In Germany, international STEM graduates can more easily be hired through the EU Blue Card system than other international graduates because employers do not have to prove an EU professional could just as easily fill the position.

STEM students are also more likely to find a scholarship than students choosing other programmes. In the US, for example, SEO firm has found that 17% of STEM-interested students receive scholarships compared to 12% of non-STEM-interested students. Across major destinations, there are dozens of major STEM scholarships – often fully funded – offered to international students by governments and private organisations.

These advantages are huge for international students. Consider that:

• , 30% of international students choose STEM programmes compared to 19% of domestic students.
• In the US, were in STEM fields in 2025.
• of all Canadian programme searches by international students on the ApplyBoard platform in 2025 were for STEM fields.
• In Australia, emerges with a STEM degree.

Why is decision-making changing?

STEM graduates have historically experienced stronger employment outcomes and higher earnings compared to non-STEM majors, but recent data reveals important variations within STEM fields. For example, the analysed 70 popular majors in 2025 and found that the unemployment rate for recent graduates with physics and computer engineering degrees was 7.8% and 7.5%, respectively, compared to an all-major average of 3.9%. Only anthropology graduates fared worse (9.4% unemployment).

As an article in puts it:

“Cracks in STEM supremacy were beginning to emerge [in 2024]. And now, in a stark reversal [the Federal Reserve Bank of New York research] found that art history grads are far more likely to be employed than computer-engineering, mathematics, chemistry, industrial-engineering and physics majors.”

While some STEM graduates still earn far more than other graduates, says the article, the trend is not as broad-based as it used to be: “It’s starting to look like some letters in STEM are more valuable than others.”

Similarly, National College of Colleges and Employers show that in 2014, only about 6% of engineering graduates were unemployed six months after completing their degree. In 2023, that proportion more than doubled to 14%. And in 2024, bachelor’s-level engineering and computer sciences were among the disciplines that lost the most ground in terms of employment outcomes for graduates.

Statistics like these are circulating among students choosing majors, and they are adding anxiety to the process. A by the Institute of Politics at the Harvard Kennedy School found that 7 in 10 college students see AI as a threat to their job prospects.

As an article in notes: “Today’s college students say that picking a major that’s ‘AI-proof’ feels like shooting at a moving target as they prepare for a job market that could be fundamentally different by the time they graduate.”

Where are students pivoting?

Because technology is arguably the area where most AI automation of formerly human tasks is happening, many students are looking into programmes – both STEM and non-STEM – that emphasise “human skills.” They are interested in interpersonal/relationship‑heavy roles that seem most immune to automation. And there is a distinct trend of students already more than a year into their current programme switching it for AI-proofing reasons.

interviewed Josephine Timperman, a student at Miami University in Ohio, who said:

“You don’t just want to be able to code. You want to be able to have a conversation, form relationships and be able to think critically, because at the end of the day, that’s the thing that AI can’t replace.”

Another interviewee for the piece was Courtney Brown, a vice president at Lumina, an education nonprofit that encourages high-school students to progress to higher education. Ms Brown said:

“We see students all the time change majors. That’s not new or different. But it’s usually for a ton of different reasons. The fact that so many students say it’s because of AI — that is startling.”

Hiring trends are reinforcing the shift

In the first six months of 2025, AI job postings on LinkedIn from employers around the world more than doubled over the same period in 2024 (+110%). And in April 2026, global show that workers with AI expertise earn about 56% more on average than other workers, and job postings that mention AI pay roughly 28% more than similar postings without AI requirements.

The LinkedIn data is only one indication of the trend; other surveys and anecdotal evidence point to the real urgency felt both by job candidates and employers about the need for AI skills.

Does that mean everyone should pursue AI-specific degrees?

The short answer is: no. Rather, AI capability is fast becoming a core employability advantage rather than an optional skill, and this is happening across business, health, engineering, social sciences, and more. Across sectors, there is growing demand for professionals who can manage, direct, or complement AI systems.

Global learning organisation says: “[What we] are navigating now is a labour market where the rules have changed at the role level, the skill level, and the career pathway level simultaneously.”

Further:

“Across enterprise learner data covering millions of professionals, the fastest-growing skill among people actively building AI capability is Content Creation. AI skill demand runs across every function. The assumption that AI upskilling is an IT or engineering priority leaves the majority of your workforce behind.”

Many non-technical roles, for example in marketing or HR, increasingly need “AI translators”: professionals who can integrate AI copilots into workflows and design prompts, and who can evaluate AI output. Titles for these roles include Citizen Data Scientist, or AI Business Analyst. Essentially, the work is cognitive, strategic, and creative – but it requires a capacity to work with and alongside AI.

Higher education is moving slower than the jobs market

by Pearson and Amazon Web Services with over 2,000 students, higher education leaders, and employers found a serious discrepancy between what employers need and what higher education institutions are delivering:

• More than half (53%) of employer respondents said that finding AI-ready graduates is their main challenge.
• Over three-quarters (78%) of university respondents said they thought their programmes were meeting employer expectations.
• And only 28% of employers believed that universities are keeping pace with AI-driven change.

The study report says:

“AI readiness does not falter at the point of intention. It falters at the points of alignment and execution, where what institutions deliver and employers require are not synchronised, and where learning is expected to translate into applied capability at work.”

Of course, some institutions are ahead of the pack and rethinking how they provide value to students. They are not making vague promises about being able to provide students with AI readiness; they are showing concrete evidence such as AI‑specific course requirements, work‑integrated learning with AI tools, and graduate outcomes linked to AI skills. And they are running these themes through all programmes: not just STEM. The screen shot below is an Instagram post by Elmhurst University’s admissions department announcing its English department’s technology-focused coursework for the September 2026 intake.

In an era where youth are increasingly cautious about where and what to study, institutions that recognise intense interest in AI skills are the ones that have the best chance of converting students – and of ensuring graduates can compete for desirable jobs. Today’s students – international and domestic alike – expect nothing less than an education that is relevant for the AI present … and future.

For additional background, please see:

• “A common challenge: Strengthening student confidence in the ROI of study abroad“
• “How is the rapid adoption of AI affecting international students’ career and programme planning?“

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AI is not arriving into a clean, joined-up recruitment function. It is landing in environments where systems do not talk to each other, ownership is fragmented, and key information lives in a mix of CRM notes, web pages, PDFs, team inboxes and locally managed spreadsheets. That matters, because AI does not solve complexity. It scales it.

The sector is at risk of repeating a familiar pattern: investing in new tools while leaving the foundations untouched. AI then becomes another layer sitting on top of the same friction points – just with quicker outputs and higher expectations.

AI in recruitment is less “wow” than it sounds – and that’s a good thing

The public conversation often gravitates towards chatbots. They are visible, easy to demo and appealing for 24/7 coverage. But the most valuable AI use cases in recruitment are rarely headline-grabbing. They are operational.

AI earns its place when it does one of three things:

• reduces response time without losing quality
• improves relevance by matching students to the right information faster
• removes admin drag so staff spend more time on high-value conversations

That can mean intelligent enquiry triage, appointment scheduling, follow-up prompts, application workflow support, and content personalisation based on what a prospect has actually engaged with. In a competitive international environment, these are not “nice to haves”. They directly influence whether a student stays in the funnel.

And it is worth saying explicitly: the goal is not to replace people. The best-performing model is “human + machine” – AI provides speed and consistency; staff provide judgement, reassurance and nuance.

The uncomfortable truth: AI exposes what institutions have tolerated for years

Where AI is introduced, it tends to shine a light on issues that were previously manageable because humans quietly compensated for them.

• Inconsistent information: entry requirements differ by page; fees are updated in one place but not another; scholarship details live on in a PDF long after the policy has changed.
• Fragmented journeys: marketing owns one part, admissions owns another, faculties own programme content, student services owns “experience” messaging – and the student experiences it as one journey anyway.
• Siloed data: multiple CRMs, multiple lead sources, inconsistent definitions of “enquiry” and “qualified”, and limited integration between systems.

AI can help, but only if the institution is prepared to treat these issues as structural – not cosmetic.

This is where many implementations falter. AI tools are purchased as point solutions, deployed by one team, and expected to perform magic in an ecosystem that is not ready to support them. The result is predictable: patchy adoption, uneven quality, and a lingering sense that “AI didn’t work for us”.

Often, the tool is not the problem. The conditions are.

Readiness is not a slogan

Before investing further, institutions benefit from stepping back and asking four simple questions. They are simple to ask, harder to answer honestly:

• Will this improve outcomes that matter?‹Response time, conversion, quality of guidance, staff workload – and how those will be measured.
• Is it easy enough to use in the real world?‹During peak cycle, with staff turnover, shifting priorities, and competing demands.
• Is there clear support and ownership?‹Not just “buy-in”, but named accountability across marketing, admissions, IT/data and governance.
• Are the foundations in place?‹Clean data, accurate content, integration capability, and governance that is operational, not theoretical.

When AI adoption stalls, it is usually because the last question is answered with a quiet “not really”.

What changes when universities use AI (and students still use it too)

Two things happen at once.

First, student expectations rise. If AI can answer instantly, waiting two days for a response feels outdated. Prospects still want humans – but they want humans at the right moment, with continuity and context.

Second, measurement becomes harder. As more decisions happen inside AI tools, fewer people follow a neat trail from ad to website to enquiry form. That does not mean marketing is failing. It means the web is no longer the only (or even primary) interface between student and institution.

In this environment, accuracy becomes strategic. AI will surface what it can find, whether it is current or not. The institutions that win attention will often be those with fewer contradictions, clearer ownership of content, and consistent signals across the web – not necessarily those with the biggest budgets.

A pragmatic way forward: start small, fix foundations, scale carefully

A full “AI transformation” is not required to make progress. But a full commitment to foundations is.

Three moves tend to deliver genuine momentum:

1) Treat the data layer as recruitment infrastructure‹Integration and data hygiene are not “IT projects”. They are recruitment capability. In practice, this means ensuring that core recruitment and admissions information — prospect records, programme data, entry requirements, fees, communications history, and application status — is accurate, up to date, and connected across systems. Where this is weak, staff compensate manually, and AI tools inherit and scale the same inconsistencies. Where it is strong, institutions can respond faster, personalise more effectively, reduce duplication, improve measurement, and give students more consistent guidance. Modest progress here often unlocks disproportionate benefits elsewhere.

2) Choose one high-impact journey point.‹Enquiry response, programme matching, international applicant support during peak periods – pick one, do it properly, and learn fast. For example, Georgia State University’s “Pounce” chatbot focused on a single high-friction point – the pre-enrolment period between admission and arrival – helping admitted students complete required tasks and get answers quickly; Georgia State reports this contributed to a significant reduction in “”. A non-chatbot example can be seen in European qualification recognition workflows, where ENIC-NARIC centres in France and Norway have explored AI/RPA (Artificial Intelligence/Robotic Process Automation) ) for rather than broad front-end deployment. The common lesson is the same: define the bottleneck, improve it step by step and use the learning to build up capability.

3) Put governance in writing and into practice.‹Define what AI can and cannot do, when humans must review, how escalation works, and how bias and data protection risks are handled. Governance should enable adoption – not suffocate it.

In short

Students using AI for search is only half the story. The other half is whether universities are ready to use AI to recruit responsibly and effectively.

The competitive advantage will not come from buying the newest tool. It will come from doing the basics exceptionally well: accurate content, joined-up data, clear ownership, and an operating model built around the student journey – with AI used to scale what already works.

For additional background, please see:

• “AI tools in action for international student recruitment“
• “AI is changing how students search: What it means for marketing and recruitment“
• “The ChatGPT Generation: How AI Is quietly rewriting the global student search experience”Ìę
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It isn’t just computer sciences feeling the impact of students’ jitters about AI. Across the board, universities are moving to position their programmes as relevant to students intent on “future proofing” their study choices.

The disruptive effect of new technologies

Between 2005 and 2023, the number of students graduating with computer science degrees in the US quadrupled. These degrees remain very popular among international students: as we speak, 1 in 5 international students in the US is enrolled in computer sciences.

Enrolments in the field first spiked in tandem with rapid Internet adoption, driving a ballooning of job openings in tech companies in the US and around the world. Coders, programmers, designers, etc. enjoyed a heyday of intense competition for their skills. But now that AI can fulfill some coding tasks and lighten the workload of programmers and designers, there is deep concern among students and workers about whether they should begin or continue a career in computer sciences.

As Boston College Professor has written, of all study fields, computer science is “the most likely to be impacted by artificial intelligence, which uniquely targets high-wage cognitive tasks, unlike past technological revolutions that automated physical labor.”

Worries about the extent of AI’s erosion of computing-related jobs is already manifesting in enrolment data. According to the Computing Research Association, a nonprofit that gathers annual data from about 200 US universities, 62% of computing programmes recorded . What’s more, 66% of respondents said that their students graduating with computing majors were struggling to land jobs.

Writing in about computer sciences enrolments declining at Duke, Stanford, and Princeton, Rose Horowitch said:

“If the decline is surprising, the reason for it is fairly straightforward: Young people are responding to a grim job outlook for entry-level coders. In recent years, the tech industry has been roiled by layoffs and hiring freezes. The leading culprit for the slowdown is technology itself. Artificial intelligence has proved to be even more valuable as a writer of computer code than as a writer of words. This means it is ideally suited to replacing the very type of person who built it. A recent Pew study found that Americans think software engineers will be most affected by generative AI. Many young people aren’t waiting to find out whether that’s true.”

Reason for optimism

Rather than panic, says Tom Griffiths, director of the Princeton Laboratory for Artificial Intelligence, students should consider that technology jobs will not disappear, but rather change. He acknowledges that there will be a decrease in so-called cognitive jobs because of AI, but he predicts an increase in “metacognitive jobs, such as knowing enough about software engineering to instruct automated software engineers and systems.” In an interview with the , Mr Griffiths said:

“I can understand why students are trying to model out what the job market is going to look like in a few years when they finish their degrees. But I also think there’s going to be all sorts of things that surprise us in terms of the kinds of jobs that become possible with particular skill sets.”

Similarly, Harvard Business School Professor Suraj Srinivasan has that found that new jobs are emerging as well as becoming scarcer as a result of AI. He found that after the public launch of Chat GPT in 2022, job postings involving “structured and repetitive tasks, likely replaceable by generative AI,” decreased by -13%. At the same time, employer demand for jobs that require more analytical, technical, or creative work – potentially enhanced by AI – grew +20%.” Professor Srinivasan says: “Rather than solely eliminating jobs, generative AI creates new demand in augmentation-prone roles, suggesting that human-AI collaboration is a key driver of labour market transformation.”

Universities are beginning to create new programmes with this human–AI dynamic in mind. For example, in 2025, the University of South Florida in Tampa attracted more than 3,000 students to its new Artificial Intelligence, Cybersecurity and Computing College. The State University of New York at Buffalo (UB) received US$5 million in funding from New York State Governor Kathy Hochul to launch a standalone Department of AI and Society that offers seven interdisciplinary AI degrees.

The interdisciplinary structure has merit: asking for candidates with AI skills – and these listings span a multitude of sectors (e.g., tourism, communications, healthcare).

Future proofing

The spectre of AI disrupting the labour force was already on students’ minds in 2024, at a time when the use of generative AI had just hit the mainstream. In a survey conducted in 2024 among more than 1,000 college students , almost two-thirds (64%) of students belonging to the class of 2027 (i.e., graduating that year) said AI had at least somewhat impacted their academic plans.

Knowing how quickly AI is changing the workforce, students are considering the future as much as the present when considering course options. For example, Travis White, an AI and Responsible Communication major at UB, explained the rationale for his choice of programme on : “My thought was that adding this new major would set me apart from the competition and give me some skills that could get me a niche, higher-paying job that may not even exist yet.”

Students are also looking outside of computing and AI

Some students are considering “interpersonal and hands-on” jobs that seem less likely – at least in the near term – to be jeopardised by AI. This trend is underlined by labour market data, as noted in a February 2026 :

“While AI is still just one factor among many that are leading to layoffs, ADP, the largest payroll company in the US, found that professional and business services roles, alongside information services jobs in media, telecom and IT, collectively lost 41,000 jobs in December 2025. In that same month, employment grew in healthcare, education and hospitality, per the firm’s data.”

The Guardian interviewed Jasmine Escalera, a career development expert at professional development firm Zety. Ms Escalera spoke to research by the firm that found that “close to half (43%) of Gen Z workers who are anxious about AI are moving away from entry-level corporate and administrative roles and toward careers that rely on ‘human skills’ including creativity, interpersonal connection and hands-on expertise.”

Study after study shows that employers remain interested in hiring people with strong “soft skills” (e.g., empathy, teamwork, communication, and creative problem-solving) – and it may be that the rise of AI will increase this demand. Fields such as the humanities and social sciences – which have been losing enrolments for years – are the very ones that cultivate soft skills, and some universities in the US are leaning into this in their marketing and programme design. They are boldly countering the narrative that the humanities are useless with an assertion that the very reverse is true. As reported in in 2025:

“The number of undergraduates majoring in the humanities at the University of Arizona has increased 76 percent since 2018, when it introduced a bachelor’s degree in applied humanities that connects the humanities with programs in business, engineering, medicine and other fields. It also hired a humanities recruitment director and marketing team and started training faculty members to enlist students in the major with the promise that an education in the humanities leads to jobs.”

Similarly, notes the Report, “Georgia Institute of Technology has also started drawing a connection between the humanities and good jobs 
 which has helped boost undergraduate and graduate enrolment in Georgia Tech’s Ivan Allen College of Liberal Arts by 58 percent since 2019.”

The Report cites a real-life example of a student who achieved the ROI she was looking for through a humanities programme: “Olivia Howe was hesitant at first to add French to her major in finance at the University of Arizona, fearing that it wouldn’t be very useful in the labor market. Then her language skills helped her land a job at the multinational technology company Siemens, which will be waiting for her when she graduates this spring.”

Ms Howe commented: “The reason I got the job is because of my French. I didn’t see it as a practical choice, but now I do. The humanities taught me I could do it.”

Quick thinking

The increasing use of AI in workplaces does not mean that human skills are becoming obsolete. Smart universities are setting their students up to work alongside AI and/or in jobs that remain high-touch and hands-on. They are reviewing programme design, positioning, and career services to align with the most important theme in higher education: career outcomes are the top driver of student choice and student satisfaction.

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Our hosts are then joined by Tim O’Brien –ÌęSenior Vice President of New Partner Development with – and Education marketing coach and author for a featured discussion on how AI-based search is affecting international student recruitment.

Today’s students are moving away from scrolling through pages of search results and are instead heading straight to generative AI for answers. Tools like ChatGPT and Gemini are no longer just homework helpers, they are becoming early stage advisors for a new generation of prospective international students.

You can listen right now in the player below, and we encourage you to subscribe via your favourite podcast app in order to receive future episodes automatically.

For additional background, please see:

• “AI is changing how students search: What it means for marketing and recruitment“
• “The ChatGPT Generation: How AI Is quietly rewriting the global student search experience“
• “șÚÁÏčÙÍű Podcast: Stop losing applicants: How qualification recognition drives seamless international enrolment“

The post șÚÁÏčÙÍű Podcast: Students are switching to AI for search. Are you ready? appeared first on șÚÁÏčÙÍű Monitor - Market intelligence for international student recruitment.

The findings rely in part on a recent Sinorbis survey of a small sample of international students at Australian institutions, but they are backed by a wider field of evidence from the latest edition of Edified’s ongoing Enquiry Experience Tracker study.

One in three students responding to the survey said they abandoned an application to a prospective university because of communication issues.

The challenge begins with responsiveness. Seven in ten students said they expect a response from an institution within a couple of days, but only about a third (34%) actually received a reply within that window.

That gap alone carries a significant cost. Nearly six in ten respondents (59%) reported disengaging from a university because communication felt “slow or difficult.”

An even greater proportion (71%) said the quality of communication played either a major or moderate role in their final decision on where to study, and 66% said that “response speed genuinely matters when choosing a university.”

Those expectations loom even larger given the increasingly competitive marketplace for student recruitment. Nearly all survey respondents (94%) said that their shortlist included five or fewer universities, and the findings make it clear otherwise that a delayed or ineffective response can be enough to shift a student’s attention to another institution.

“The enquiry stage is an incredibly influential moment in a student’s journey,” notes Elissa Newall, senior partner at Edified. “When a prospective student reaches out for the first time, it gives them a glimpse of what it might feel like to be part of an institution’s community. A clear, responsive experience builds trust; a poor experience simply pushes them away”.

The study report adds, “Student expectations are changing at a much faster rate than many institutional processes. While universities have expanded their recruitment activity and added some new communication channels, students are now judging their experiences against a much higher standard
For university marketing and recruitment teams, this creates some very real pressure. Students are engaging across more channels, expecting faster responses, and comparing experiences more closely than ever before. Yet many institutions are still operating with engagement models that were designed for a different era.

Although email remains central, as student preferences shift toward messaging, new channels are added, but systems, resourcing, and processes often struggle to keep pace. The result is a growing disconnect. Enquiries go unanswered or are answered too late. Conversations break across channels. Students are asked to repeat information, and what should feel like guidance instead ends up feeling transactional.”

Introducing the omnichannel

In part, those findings reflect a growing student preference to communicate outside of email, and especially via messaging apps such as WhatsApp or WeChat. The issue for recruiters is not only managing communications with students across a widening array of channels, but that that ideal channel mix varies by market as well.

Even so, there is no mistaking the shift. As the study report explains, “Email once the default channel for formal interaction, is no longer the main reference point for many prospective students. Instead, expectations are now increasingly shaped by the messaging platforms that students are using every day. These more modern environments have the benefits of being immediate, conversational, and perhaps most importantly, highly familiar. They set a standard for how quickly and easily information should flow.”

That standard, however, collides with the reality that many recruiters face today of large and growing volumes of enquiries from prospective students. Edified reports that two in five institutions now receive more than 25,000 enquiries from prospective international students each year, yet, four in five say they lack “a single view of the customer” – that is, a way to effectively manage communications with prospective students at scale.

The authors argue for an “omnichannel” approach that allows recruiters to meet students where they are at, in terms of communications channel, but where all channels are strongly linked to and owned by the institution, where the use of that wider range of channels is properly resourced, where all are integrated into recruitment systems (especially CRMs), and where those aligned workflows and systems can support more effective and meaningful student communications at scale.

“Automation supports this process by enabling both speed and structure, especially during peak enquiry periods,” adds the report. “Beyond simple acknowledgements, segmentation and automation allow institutions to prioritise leads based on factors such as level of intent, programme interest, country, or stage in the journey. High intent enquiries can be surfaced quickly, while earlier stage prospects can be nurtured over time without manual intervention. This ensures that the attention is focused where it is going to have the greatest impact, even when teams are under pressure.”

As the students engagement with the institution continues – as they progress along the enrolment funnel – that alignment between channels, workflows, and systems can equally support a more targeted engagement with well-qualified prospects. In other words, this is the stage at which automation gives way to more one-to-one communication. The study report adds that, “By prioritising personalised dialogue at the bottom of the funnel, institutions create space for meaningful reassurance rather than transactional exchanges. This human connection often becomes the final factor that turns intent into action, helping students feel confident in their decision and supported in taking the next step.”

For additional background, please see:

• “Mystery shopping study finds broad improvement in student enquiry handling this year“
• “Three international education trends for 2025: Revenue optimisation, marketing personalisation, and on-the-ground local intelligence“
• “In a time of shifting student demand, a speedy response to enquiries is a must“

The post Survey highlights a growing “engagement gap” between international student expectations and institutional response appeared first on șÚÁÏčÙÍű Monitor - Market intelligence for international student recruitment.

Prospective students are increasingly using ChatGPT and other AI models to help them make decisions – including to which schools to apply. A recent survey by INTO University Partnerships found that that 17% of recently admitted students reported to have used AI tools for researching study options.

Another stat: Cues.ai, based on web analytics data from around 20 UK universities, saw web visits referred by ChatGPT .

And all of this proof is likely understating how prospective students make decisions right now, for several reasons: People mostly read answers within the tool, and even when they click through to your website, it is notoriously hard to track. And even a traditional search in Google can bring up an AI overview as an answer.

What does AI search mean for education marketing?

Your first instinct may be to make drastic changes, but although there are definitely changes to make, my advice is to take it slow.

While AI search changes how prospective students get information, it doesn’t change the fundamentals of good marketing. You still need to get the right messages to the audience that matters to you and make sure they get the right information at an appropriate time in their decision making process.

All of the below influences how you show up in AI platforms. You’re likely already doing most of them:

• Your website is the only place on the web that is fully controlled by you. Making sure your website provides accurate information and is easy to nagivate helps prospective students directly and “feeds” the AI models at the same time.
• Ranking and comparison websites are especially important when prospective students ask questions around rankings, which they often do.
• Digital word of mouth – what your current students and alumni are saying about your institution across the web. This provides a more ‘impartial’ perspective from students’ point of view, and there are ways you can encourage this, such as working with student ambassadors as content creators.

A more important reason for not making abrupt changes: the “old” channels still work! Prospective students will continue to consult a mix of different sources, both offline and online. They will still visit student fairs and some will prefer to enlist an agent’s help. They’re still on TikTok and instagram. It’s just that AI answers are becoming an increasingly important part of the mix.

So if you’re running a digital campaign that works, keep going and make gradual changes as the need arises. And as I argue in my book , Search Engine Optimisation (SEO) best practices that help your website show up in Google are by and large the same practices that make your institution visible on AI platforms.

What will change

That is not to say that the shift to AI search is business as usual. In the 18 years that I’ve been active in online education marketing, I have seen lots of change, but this is the quickest and most significant shift I’ve seen so far.

Here is what will change:

Tracking and KPIs. Fewer people will visit your website. And tracking those who do will get harder. This means that you will need to get comfortable doing marketing with less data on what works. And at the same time, you need to start paying attention to AI visibility.

Tracking AI visibility is tough: the only way to see inside the black box is to ask each tool the same question repeatedly and see whether your school is mentioned and with what sentiment. There are tools which will automate this process and provide aggregated statistics that you can drill down on. I personally use peec.ai.

Before you start tracking, spend some time investigating which questions prospective students are likely to ask. You can find clues by checking popular search keywords, mining student enquiries and analysing forum discussions.

Accuracy. Another aspect to pay attention to: the content of AI answers. Do they represent your institution accurately? For example, you may have offered a scholarship that has since then been discontinued. If it is still mentioned on an abandoned page on your website, AI may pick up on it.

AI tracking tools will cite the sources that informed particular answers, so if you check the answers on a regular basis, it’s often easy to find the culprit. Once you know incorrect information is out there, you can move to correct it.

Influencing AI mentions. Once you start tracking your visibility, you’ll notice that you’re not always part of the answers you’d love to be mentioned in. Influence your visibility by publishing helpful content around the question’s topic on your website and elsewhere. Since AI tools like to draw on a variety of sources, this content should come in different shapes and forms: a blog post on your website, a helpful YouTube video, a student ambassador participating in Reddit conversations. Sounds a lot like common sense good marketing, doesn’t it?

In short

Prospective students are increasingly using AI tools to compare and evaluate their study options. While there’s no need for abrupt changes to what you’re doing (keep doing what works!), this change will impact online marketing success measures. So expect fewer website visits and conversions as more people get their answers from ChatGPT, Perplexity or inside Google AI Overviews.

Now is the time to start paying attention to whether your school is mentioned in AI tools at all, and what they say about you.

For additional background, please see:

• “The ChatGPT Generation: How AI Is quietly rewriting the global student search experience”
• “Growing use of AI for study abroad decisions highlights importance of multi-channel marketing strategies”
• “Students are switching to AI for search. Are you ready?”

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In September 2025, we conducted a cross-institution survey of over 1,600 newly enrolled international students in the US and UK. Our goal was simple: to understand how students are using AI in the crucial, early part of their journey –Ìęidentifying and applying to university –Ìęlong before they ever step into a lecture hall.

Approximately one in six respondents (17%) indicated they used AI (Chat GPT etc) as part of their initial search, but that varies significantly by home country.

The most critical finding however appears to deliver a clear message on the value students ascribe to Large Learning Models (LLMs): 96% of AI users found the guidance they received from AI tools (ChatGPT, etc.) either met or exceeded the quality of information provided by traditional sources (websites, brochures, agents).

This figure –Ìęderived from 81% who found AI more helpful and 15% who found it about the same –Ìępresents a potentially profound challenge to the legacy digital experience offered by institutions and advisers.

While 17% of newly enrolled students used AI for their search, this 96% endorsement appears to validate the technology as functionally superior for pre-application research. For those who embrace the tool, it has become the standard.

The context: AI is already central to most university students

To place the 96% figure into context, it is important to understand that AI is not a novelty for today’s students; for many, it is already an ever-present companion in their academic lives. This survey of 1600 international students simply suggests that recruitment and admissions may simply be the final frontier of adoption.

• Turnitin produced of how students use AI. They reveal that an overwhelming majority – 86% of students globally – are already regularly using AI in their studies, with 54% using it weekly.

• In the UK, the use of generative AI tools for assessments has seen an explosive increase, with recent reports indicating that 88% to 92% of undergraduates now use AI for their coursework in some capacity.

• According to , Students commonly utilise AI to explain complex concepts, summarise articles, suggest research ideas, and search for information.

• The fact that only 17% of newly enrolled students in this survey reported using AI for their initial university search suggests this phase is the last part of the educational lifecycle to be fully integrated with this standard technology.

The new asymmetry: East Asia leads the adoption race – for now

While only 17% of newly enrolled students reported using AI for their search, this near-unanimous endorsement within this early-adopting sample (n=1622) suggests that for those who embrace the tool, it is becoming new standard pre-application research.

Beneath that single number lies a more nuanced adoption story. Usage rates vary sharply by region: nearly 30% of students from South Korea and the Philippines report using AI, along with 28% from Taiwan, 25% from Vietnam and 22% from Japan. Mainland China sits at 21%, while South Asia, Latin America and Africa show more modest uptake.

The pattern is probably familiar to those who track technology diffusion: low overall penetration, but pockets of explosive early adoption. These are the indicators of a curve that has yet to reach its inflection point. Most of us working in higher education know that time will come – and sooner than we expect.

The strategic student (and parent): How students report using AI in their search

Yet perhaps the more important insight concerns how students are using AI. Far from relying on it for superficial tasks, students are deploying it for strategic decision-making. Among those who used AI during their search:

• 61% asked about university rankings and reputation
• 39% sought programme or course details
• 34% investigated career outcomes
• 34% explored student life

These are not trivialities; they are the structural determinants of a student’s choice – with career outcomes near the top of the search.

The picture that emerges is one in which AI acts as an early-stage adviser –Ìęa synthesiser of options, a comparator of institutions and a curator of the overwhelming abundance of online information. Before applicants speak to an agent, attend a webinar or download a prospectus, many have already engaged in a long-form, personalised dialogue with an AI model.

An interesting counterpoint, and one worth emphasising, is that students are discerning in their use of AI for search. They understand where AI is helpful, and where it may be more risky. Only 16% used AI for application essays, and only 17% for visa information. These are domains where inaccuracies can be costly or where plagiarism detection software is sophisticated.

Far from reckless AI adopters, these respondents appear thoughtful and strategic. They are not blindly outsourcing high-stakes decisions; they are using AI precisely where it provides clarity without penalty.

Students value the advice they receive from AI

Students (and their parents) are not using AI simply because it is available; they appear to rate the advice highly. When asked to compare AI guidance with university websites, brochures, and even agents, a majority of students indicated the advice was more helpful than traditional sources. This is quietly significant: for many early adopters, AI is already the more effective source.

As AI moves into the top of the recruitment funnel, the first impression of an institution may no longer come from an optimised Google search, but from a generative AI model such as Deepseek, Gemini, or ChatGPT.

It means students are more likely to ask questions in natural language – “Which universities are best for engineering given my budget?” – and receive answers drawn from a diffuse and imperfect online footprint. This means the accuracy, consistency, and clarity of publicly available information has never mattered more. We all know AI gets it wrong, but it is improving.

The implications for the advisory ecosystem of agents, high school counsellors, career coaches and so on are equally profound. AI has begun to take on the foundational advisory tasks of summarising facts and comparing institutions. Agents and counsellors will increasingly be valued not for reciting facts, but for providing emotional context, personalised judgement, and reassurance – all things AI still cannot do well.

Meanwhile, students accustomed to personalised, instant AI responses will bring heightened expectations to every subsequent interaction: faster turnaround times, clearer messaging, and communications that feel conversational rather than bureaucratic.

A mandate for digital clarity?

The overwhelming student preference for AI’s speed and clarity is a structural challenge that those recruiting or guiding students need to address:

• The New Baseline: For 96% of users, AI either matches or surpasses the information quality of official institutional sources. For a student to choose the official website over AI, the official source must now be unambiguously superior in both information quality and user experience.

• Neutrality is a Challenge: The 15% of users who found AI “about the same” are unlikely to be a neutral group; they are users for whom AI’s superior convenience and 24/7 access make it functionally equivalent to a slow, complex official source.

• Regional Contrast: The urgency is pronounced in regions like the Middle East and Africa (MEA), where a majority (54% of users) found AI “Much more helpful.” Conversely, in South Asia, a higher proportion found AI “about the same” (29%), suggesting that traditional agent networks remain strong and the AI experience has yet to deliver a revolutionary step-change.

• The Critique: With only 4% of users finding AI less helpful, the market will demand speed, clarity, and conversational access, which AI delivers and many institutional systems currently do not.

As AI moves to the top of the recruitment funnel, the first impression is increasingly formed by an LLM synthesis, not a controlled website visit. This means the clarity and consistency of publicly available information has never mattered more.

What can universities and advisors do now

Given how students are already using AI – wisely and in growing numbers – we need to act proactively. The following recommendations respond directly to the patterns in our survey data:

1. Optimise content for AI models, not just humans. Clear, structured programme descriptions, updated entry requirements and unambiguous tuition details improve how LLMs summarise your institution.
   
2. Test how AI currently describes you. Run prompts such as “What is University X known for?” or “Which universities are strongest in Z?” This reveals inconsistencies or outdated perceptions.
   
3. Focus on process. Machine learning AI tools can help transform the often-arduous application process, delivering a faster, more accurate experience for students and their agents, supporting institutional compliance and smarter monitoring of the conversion/yield funnels.
   
4. Support advisers to complement, not compete with, AI. Counsellors should focus on interpretation, empathy and nuanced guidance.
   
5. Publish clear, ethical guidance for applicants. Students are already wary of using AI for essays and visas; universities should reinforce good judgement with transparent policies.
   
6. Prepare for higher expectations. AI-using applicants arrive better informed and less tolerant of slow, generic or opaque responses.

The challenge is not if AI will reshape the student journey, but how quickly. The data from this survey points to a strong directional shift, validating AI as the preferred functional research tool for a growing segment. The ultimate structure of the recruitment ecosystem, however, is not a fait accompli; it hinges on the ability of human advisers and institutions to evolve beyond static information delivery and offer value –Ìęspeed, nuance, and humanity –Ìęthat AI cannot replicate.

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The market is shifting

Somewhere in the middle of 2025, we started talking not just about the Big Four study destinations –Ìęthe United States, United Kingdom, Australia, and Canada –Ìębut also about the Big 14. The latter term is admittedly not always carefully defined, but it certainly has gained currency as a way to describe one of the most important macro trends shaping student mobility this year.

The Big 14 is generally understood to include not only major English-speaking destinations, but also a number of additional countries in Europe and Asia that continue to attract greater numbers of international students. We’re talking here about destinations like Spain, Italy, Germany, France, Malaysia, South Korea, Japan, and Taiwan –Ìęand more.

There are a number of factors at work here, including of course the more restrictive policies put in place across the Big Four over the last couple of years. But that is only part of the story. This important market dynamic is also being driven by demand-side changes, including students’ interest in more affordable destinations, and by a more active recruitment effort on the part of many of the Big 14 countries.

All that to say: There is an excellent chance that we will look back on 2025 as a turning point in the history of our sector – the year in which the marketplace became more competitive and diverse in terms of global student flows.

The calculus of study abroad is different now

There is no question that there is now a greater emphasis across student markets on affordability and on the return on investment for study abroad.

Those factors – affordability and ROI – have come to the fore in recent years. This is not new, but rather a matter of degree – the extent to which this is a priority for students deciding where and how they will study abroad.

When we look back at all the large-scale student surveys from the year, we see the same findings coming through. Students talk about cost of study, cost of living, availability of scholarships, work opportunities, graduate outcomes. Underpinning those priorities are a need for affordability and return on investment.

The effects of these patterns are already wide-ranging. They have an impact on destination choice of course, but also a massive influence on student expectations for study abroad, especially as they pertain to graduate outcomes.

Public support comes from alignment

Speaking on our most recent edition of the șÚÁÏčÙÍű Podcast, immigration specialist Jeremy Neufeld made the point that immigration policy, as it relates to international students, has to deliver demonstrable, broad-based benefits for the host country. This is key if we are to encourage or maintain the support of the general public, and of policy makers as well, for international education.

Our expectation is that, going forward, we will see much more alignment between government policy, institutional recruiting, and the larger societal and economic goals of an individual study destination.

This time we really mean it

We have been talking about diversification of foreign enrolment for years. But 2025 might be the year where the importance of building a diverse student body has truly been driven home for a critical mass of international educators.

Major study destinations have historically been over-reliant on students from a relatively small number of countries, and from China and India in particular. But Chinese numbers have been softening since before the pandemic, and India is now showing signs of slowing as well. At the same time, many institutions are becoming more targeted in their recruitment efforts and more actively diversifying recruitment across a wider field of markets. We expect this to extend into 2026 and beyond.

AI is here

Everyone’s favourite acronym came into even greater prominence this year, and we began to see AI having more concrete impacts across the sector:

• Students searched much more on AI for study abroad options. Stakeholders across our sector are moving quickly to learn and adapt to a “zero-click” future and a very different landscape for online search.
• At the same time, international recruitment professionals are making greater use of AI tools to manage their recruitment pipelines and engage with prospective students more effectively and efficiently. Especially in a more competitive environment –Ìęwhere timeliness and responsiveness are key –Ìęwe can expect this AI toolkit to expand and develop further in the year ahead.

Thank you

Last but not least, we want to take this opportunity to thank you for reading and learning along with us. We look forward to bringing you the latest insights on international recruitment all through 2026.

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