– Mr. Sanjay Laul, Founder at MSM Grad
The Future of Jobs Report 2025 released by the World Economic Forum states that there will be 92 million jobs lost globally by 2030. This statistic is frequently referenced not only in admission webinars but also in many parent-based WhatsApp groups; however it is often mentioned without its neighbouring estimated figure also included in the same report. Over the same five years, the Forum projects 170 million new roles will be created, a net gain of 78 million jobs globally. For an international student selecting a major/degree and country of study in 2026, the second figure should form the basis of their decision because it demonstrates actual competition occurring as a result not between machines and people but between graduates educated/able to work in conjunction with AI and those who do not have skills necessary to be able to succeed.
What automation is actually absorbing
The jobs that are going away first do not include senior jobs; they are the entry-level jobs which have been used for many decades as the way for new people to get into their field of work, e.g., initial data cleaning, getting research done but not fully completing it, answering common questions submitted by customers and creating drafts for final production. They are not an end to a job; they help to develop the judgement one will need in order to eventually be promoted for their first time.
According to the 2026 Graduate Hiring Analysis conducted by ZipRecruiter, the rate of hire for graduates that came in with internship or applicable work experience was over 2X greater than those without that experience. Additionally, certain companies like IBM have publicly announced their intention to triple entry-level hiring, specifically in software development, cybersecurity, and AI engineering; that sends its own message: those sorts of jobs are not disappearing; they are changing so that they require people to supervise/ask questions/direct an AI system, rather than just do the tasks that a model can now do at a faster rate than what we as humans could have done before.
The skills employers say they cannot buy
The Forum’s employer survey has a very specific conclusion concerning the changing metric of this statistic as 39% of core workforce capabilities will change between 2020 and 2030, and AI and data literacy are at the top of the list for the fastest growing capabilities. However, if you look deeper at all of the top ten skills on this list, you will see a much different pattern appears; specifically, analytical thinking, creative thinking, resilience, flexibility, agility, and curiosity with a lifelong learning mentality all rank with the technical skills and not below them. Sixty-three percent of employers identify there will be a skills shortfall from the skills they currently have and the skills required to be successful.
Therefore, the limitation on hiring in 2030 will not involve using AI tools, as all competitors will have similar access. However, there will be limitations in terms of gaining access to individuals who have technological proficiency and experience using technology to improve their decision-making processes.
Why international graduates are not starting from behind
In an AI-driven labour market, a certain view suggests that international students are now at risk as potential job seekers because they typically don’t have strong connections, or networks. However, this thought process is incorrect; research indicates that 70% of graduate-level students who are taking master’s programs related to AI (there are already thousands) throughout the U.S. are international. Furthermore, based on industry reports, there is a significant deficit of over one million qualified individuals globally for open AI positions. Thus, international graduates are not looking to join the AI workforce – most of them already constitute a majority of it.
Another thing that global mobility adds is something which cannot be quickly replicated by coding bootcamps: the skill of understanding data across multiple regulatory environments, communicating across languages accurately and developing products that would otherwise be misinterpreted by a single-language, single-market-centric team. As AI technology is implemented globally, that fluency as an obvious characteristic of fluidity, will turn into a technical requirement.
The real gap worth closing
The true threat that all graduates by 2030 face is not automation; rather, it is an educational misalignment between what universities provide graduates with and what employers want to test as skills/qualifications. A recent labour study found that nearly half (47%) of the graduate population surveyed stated AI had impacted the hiring process in their industry, and less than a quarter (23%) of graduates had received effective instruction/training in artificial intelligence during their degree program.
The headline gap number isn’t nearly as concerning as the 24 points difference between them, which is the actual crisis and one of the easiest to fix; a university graduate with a documented applied AI project portfolio, authentic cross-cultural project experience and analytical capacity will not just be competing with automation, but will actually be the reason for a corporation to put money into automating their processes.
Obtaining a degree that has longevity from today to 2030 won’t appear very impressive, even if it carries a very well-known name. The degree that will hold its value over the long term will be the one that produces graduates with the ability to adapt to different cultures, question the response of a computer, and have an ability to continue their learning after graduation. This particular combination of skills is impossible for artificial intelligence (by design) to replicate.