On October 26, 2026, Shileen Costain, who heads PTE at Pearson, described a gap between employers’ graduate requirements and students’ AI confidence and workplace skills.
Employers prize communication and applied AI
Half of employers put communication and collaboration among their top three requirements for graduates. That puts the ability to work with other people among employers’ highest stated requirements. For students preparing to use AI, this is a distinct measure of readiness: knowing how to use a tool does not, by itself, demonstrate communication or collaboration. Employers’ priorities therefore span both working with people and using technology in a way that fits a job.¹
Employers also identify limited hands-on experience with workplace AI tools as a leading barrier to graduate readiness. The emphasis on hands-on experience points to a practical test: graduates need opportunities to apply tools in work-related tasks, rather than only become familiar with them in principle. Read alongside the requirements for communication and collaboration, this barrier describes two different kinds of preparation. A student may understand AI tools yet still lack practice using them in a professional setting or working through tasks with others.¹
A student may understand AI tools yet still lack practice using them in a professional setting or working through tasks with others.¹
Students use independent AI tools more than university tools
About half of students use independent tools for writing, compared with 20% who use their university’s AI tools for writing. The figures show that students’ writing-tool use is not confined to systems provided by their institutions. That split makes the setting of AI use relevant: students may be using tools outside the university’s own provision, while still needing to understand the rules that apply to their work. Tool access and confidence about permitted use are separate questions.¹
Education & University InsightsIndia’s Higher Education Agenda Puts Skills, Research and Faculty First
A panel framed the debate around India@2047, while a university chancellor said competitive research ecosystems can take 10–15 years to develop.
Read More →Only 34% of students are highly confident that they are following the AI rules. UK students are better informed about AI guidance than students anywhere else surveyed, yet just 35% are comfortable telling staff about all their AI use. These measures describe different parts of the same issue: knowing guidance does not necessarily translate into confidence about compliance or comfort discussing use. The UK figures show that stronger awareness can coexist with reluctance to disclose AI use fully.¹
Students value university, but few report high-level AI workflow training
Nearly two thirds of respondents, 63%, say AI makes a university education more essential, not less. That view places higher education within the response to AI rather than outside it. It also sits alongside employers’ stated demand for communication, collaboration and hands-on AI experience: students can regard university as important while still needing specific preparation for the way AI tools are used at work. The figure captures respondents’ view of education’s importance, not whether training has met every workplace need.¹
Only 14% of learners say their university training developed their ability to apply AI tools to a professional workflow to a high level. A professional workflow means using tools as part of work tasks, rather than simply writing with them for study. The difference between valuing university and reporting high-level workplace preparation is clear in these figures. The first speaks to the perceived importance of education; the second measures learners’ own assessment of a particular applied skill.¹
UCL links engineering and computer science with industry
UCL’s Industry Exchange Network is run by its engineering and computer science departments. The network connects those academic departments with industry partners, giving students a route into work-related activity alongside their university studies. That structure offers a concrete example of how university and industry can meet: the departments run the network, while industry partners take part. The example is distinct from a general claim about AI training; the stated detail is the programme’s departmental and industry connection.¹
Between 40 and 45% of participants in UCL’s Industry Exchange Network are later recruited by their industry partners. The recruitment figure provides an outcome tied to participation: some students move from the network into roles with the organisations they worked with. It does not measure AI skill specifically, but it shows how an industry-linked university programme can connect participation with recruitment. That makes the network a practical example of education and employers working together, rather than a claim that classroom training alone supplies workplace experience.¹
Education & University InsightsKumar Urges Colleges to Graduate Students with Work Portfolios
Kumar linked policy success to institutional capacity, while industry examples show curricula and hiring tests shifting towards applied problem-solving.
Read More →Only 14% of learners say their university training developed their ability to apply AI tools to a professional workflow to a high level.
Seek Applied AI and Collaboration
Prioritize roles or courses that offer hands-on use of workplace AI tools, since employers name limited practical experience as a leading barrier to readiness. A university program that connects you with industry partners, like UCL's Industry Exchange Network, offers a concrete route: 40 to 45% of participants later get recruited by those partners. When evaluating a course or job, ask directly what AI tools you will use in real tasks, not just in theory.¹
Build communication and collaboration alongside AI skills, because half of employers rank these among their top three graduate requirements. Knowing a tool does not prove you can work with others. Also, only 34% of students feel highly confident about following AI rules, so clarify permitted use early in any role. If you study in the UK, note that better guidance awareness does not mean comfort disclosing AI use—only 35% feel at ease telling staff.¹
Sources
Written by Career Ahead AI. AI can make mistakes, so verify key facts. Report errors to support@careeraheadonline.com
