The easy-living student: Academic complexities in the age of AI

• 92% of undergraduates report using AI tools (up from 66% the year before)
• 88% have used generative AI for assessments
• 51% use it to save time
• 50% say it improves work quality
• 45% already used AI at school before university

On this scale, AI stops being a hack; it becomes an infrastructure. Universities are no longer introducing students to AI; instead, they are receiving students who already see AI as normal and who are arriving pre-optimised.

The so-termed easy-living student is not necessarily breaking rules. They are often doing something that feels completely reasonable: using AI to get unstuck, save time, and improve quality.

Modern students behave less like traditional learners and more like editors-in-chief: commissioning drafts, choosing the best version, tightening language, formatting the final output.

• 18% admit to directly including AI-generated text in submitted work
• 59% say assessment has changed significantly in the last 12 months
• 76% believe their institution would spot AI use in assessed work

Since universities tend to grade output as a proxy for learning and since AI can now manufacture high-quality output at speed, what exactly is being assessed?

This is where the friction lies: 63% of students view using AI for entire assignments as cheating, yet institutional policies remain a moving target. While students look for clear boundaries, only 28% of institutions have fully integrated AI into their formal strategies. This creates a grey zone where the ghost student appears: present in the submission, but absent in the critical thinking.

The easy-living student is often reacting to pressure, not avoiding it. The modern academic experience is fundamentally different from what assessment systems were designed for: students are rarely studying full-time anymore.

In place of academia in previous generations, students are balancing multiple competing demands. In 2026, the easy-living student is often a by-product of a hard-living reality. With 39% of students admitting that paid work hampers their studies, AI is less about academic dishonesty and more about economic survival. It’s a tool to compress a 40-hour academic week into the small windows left between retail shifts.

Digital access, once assumed to be universal, remains patchy and unreliable for a significant portion of students. Basic study infrastructure like stable Wi-Fi and personal devices can’t be taken for granted. On top of all this, they’re facing a workload designed for an era when every task genuinely took longer to complete.

A 2024-25 survey by Jisc shows:

• 60% struggled with Wi-Fi connections
• 37% lacked access to a suitable device at some point

Students are trying to survive a system that has not been adjusted to these realities. AI doesn’t just help with coursework in this context. It compresses life. It creates breathing room. It lets students who are working 20 hours a week in retail still submit a decent essay.

“In the context of work pressures and competing demands, it’s not surprising that AI is becoming part of the workflow,” Devendra Saini, Student Expert and Director of Organic Growth at amberstudent.com tells Digital Journal. “Many students are moving from writing from scratch to shaping and refining drafts. The challenge is making sure universities can still recognise genuine learning, not just polished output.”

In other words, the easy-living student is not always the least motivated. Sometimes, they are simply the most overbooked.

The Support Gap

The disconnect goes deeper than just training. Only 28% of institutions have fully integrated AI into their strategies, even as 34% of students are already using AI tools in their learning. And while 23% of students receive institutional AI access, the rest are cobbling together solutions from free tools and ChatGPT.

Only 36% of students say they have received AI training from their institution, even while 67% say it’s essential to use AI effectively to thrive today. Students don’t just want permission, they want provision. 53% think institutions should provide AI tools, but only 26% say their institution currently does.

Digital skills development tells a similar story: while 55% receive course-related digital skills guidance, only 37% get training for employment, and just 27% are offered any formal certification for the AI skills employers increasingly demand.

The risk here is of emerging inequality: some students have access to better tools and better guidance. Others make do with free versions and guesswork. The campus becomes two-speed.

Students are both aware and worried about AI. With 64% of students expressing concern about AI in education, the easy-living student is not carefree; their life is often filled with anxiety.

• 53% fear being accused of cheating
• 51% worry about false or unreliable results
• 31% face institutional discouragement or bans
• 20% find tools too expensive

73% feel overwhelmed by the sheer availability and volume of AI tools, and 50% don’t know how to get the most benefit from AI in their studies.

So students adapt. They use AI, but they rework it. They don’t paste; they paraphrase. They don’t submit the first output; they humanise it. They learn the new hidden curriculum: how to use AI without getting caught, or without getting falsely accused.

The consequences of the easy-living student era play out on two levels: the immediate and the long-term. Around 7,000 confirmed AI-related cheating cases were recorded at UK universities in 2023-24, equivalent to 5.1 cases per 1,000 students. But most AI use will never show up in misconduct statistics, because it’s happening in the grey zone that universities struggle to define: brainstorming, structuring, rewriting, and polishing.

The deeper concern is what happens over time. If everyone can generate decent work quickly, grades start rewarding the ability to manage output, not develop ideas. Submissions get cleaner, language improves, and students cope better. But the hidden cost is skill decay, especially for foundational writing and thinking abilities.

• 59% worry it could reduce critical thinking
• 49% fear becoming over-reliant on AI tools

Paradoxically, AI can make students more productive today while quietly making them less capable tomorrow. The cheating cases are just the visible symptom. The real risk is a generation graduating with polished portfolios but underdeveloped skills.

The era of detection as a primary strategy is over; with 88% of students expecting AI’s role to expand by 2028, the digital prohibition model is collapsing. The focus must shift from policing output to redesigning the process. While 33% of students are finally being consulted on AI policy, this dialogue remains the exception rather than the rule.

The easy-living student is no longer a hypothetical; they are the new campus majority. The ultimate risk isn’t a rise in cheating, but a decline in cognitive stamina. As universities race to catch up, the real gamble isn’t whether a student uses a shortcut, but whether that shortcut eventually replaces the need for an education at all. The degree might be generated by AI, but the graduate still has to live in the real world.