Crossing a border to learn has always required passing through a gate, and the gate has always changed shape rather than disappeared. Once it was a letter of introduction and a great deal of luck. Today it is an application portal, a visa interview, a credibility check, an agent’s recommendation. What has changed is not whether the gate exists, but who, or what, decides how it opens.
Technology amplifies the intent of whoever builds and deploys it, and the same tools that widen access can just as easily be tuned to extract value from families who can least afford it.
UNESCO’s latest figures put the number of internationally mobile students at roughly 7.3 million in 2024, nearly triple the figure from two decades ago, with mobility projected to approach 9 to 10 million by 2030. India has overtaken China as the single largest source of these students, sending an estimated 1.34 million abroad in 2024. Behind each of those students typically sits a family rather than an individual decision: in much of the developing world, a foreign degree is financed collectively, through savings, borrowed capital, or assets sold specifically for the purpose. When the stakes are that high, a wrong recommendation is not a bad review; it is a family’s plans undone.
It is against this scale, and this level of financial and emotional exposure, that artificial intelligence is now reshaping the sector, and the real shifts are quieter than the current wave of AI-in-education hype suggests.
1. Guidance Is No Longer Rationed by Geography
For decades, the quality of advice a prospective student received depended heavily on which office they happened to walk into. A well-resourced counsellor offered genuine options; an overstretched or commission-driven one offered whatever was easiest to sell.
AI-based counselling tools are beginning to close that gap, providing consistent, always-available guidance that draws on scholarship rules, course requirements, and visa criteria, which would take a human days to compile manually. A 2025 FICCI–EY–Parthenon survey of leading Indian higher education institutions found that 40% had already deployed AI-powered tutoring systems or chatbots, and 57% reported having a formal AI policy in place.
What these tools cannot yet do is reassure a family that a financial risk is worth taking; that remains, and is likely to remain, human work.
2. Trust Is Becoming a Verification Problem, Not Just a Reputational One
Every cross-border admissions system runs on one scarce resource: a reliable answer to whether a document, an offer, or an applicant is genuine. Generative AI has made that harder before making it easier. Fraud-detection researchers have documented a sharp rise in AI-generated fake credentials, offer letters, and financial documents over the past year, sophisticated enough to pass basic manual checks. India’s University Grants Commission continues to publish an annual list of unrecognised institutions operating domestically, and cases of forged financial or admission documents surfacing in visa applications abroad are no longer rare exceptions.
In response, AI-driven identity and document verification is becoming standard infrastructure across serious agencies and platforms, turning what was once a judgement call made on instinct into something closer to a structured, auditable check.
3. The Backend Layer Is Where the Durable Value Sits
Consumer-facing tools come and go quickly in this sector; the infrastructure underneath, verification systems, payment rails, the data pipelines connecting agents, universities, and financial institutions, tends to last much longer and compounds in value.
Consider what happens when an agent’s record and a university’s admissions system disagree on a single field: a fee marked paid on one side and still pending on the other, a scholarship code that fails to map cleanly across two platforms built years apart. No chatbot catches that kind of mismatch; a well-built pipeline does, quietly, before it becomes a missed deadline or a lost seat. AI can move that pipeline faster and more accurately than any team of humans could, but someone still has to decide what it is built to protect in the first place, whose data takes precedence, whose deadline cannot be allowed to slip. That remains a human call.
4. Prediction Is Replacing Reaction in Enrolment Management
Admissions teams have historically found out that a promising applicant had disengaged only after it was too late to intervene. AI-based pipeline monitoring now allows institutions and agencies to flag early signs of drop-off, an application left incomplete, a scholarship deadline approaching unanswered, before an offer lapses. This does not predict the future so much as compress the window in which a human can still act on it. The technology’s real value lies in what it preserves, not what it automates: the moment where someone notices in time to call.
5. Language Is Ceasing to Be a Barrier to Opportunity
For most of India’s population, English fluency has functioned as an informal gatekeeper to global opportunity, regardless of academic merit. That is beginning to change. Government-backed initiatives like Bhashini and BharatGen now support AI tools in more than 20 Indian languages, and vernacular AI adoption is accelerating across education, agriculture, and financial services. A student can increasingly ask about tuition, scholarships, or visa steps in her own language and receive a fluent, judgement-free answer. This is not a minor convenience; it redistributes access that was previously concentrated among the linguistically privileged.
The Way Forward
None of these five shifts makes the system fair by default. Technology amplifies the intent of whoever builds and deploys it, and the same tools that widen access can just as easily be tuned to extract value from families who can least afford it. The institutions and platforms that will matter most over the next decade are unlikely to be the ones that automate the most. They will be the ones that use these systems to get a human to the right family at the right moment, when a decision shaping a decade of someone’s life needs more than an algorithm’s confidence score behind it.
Guest author Dishant Kharbanda is the Chief Innovation Officer at Crizac Ltd., a global student mobility platform that is evolving into an AI-first ecosystem to support students, counsellors, and universities across the international education landscape. Any opinions expressed in this article are strictly those of the author.
