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#33

The AI Revolution: students get It, institutions don't. And what does it mean for Ethiopia?

Future is here

In 2017 Andrew Ng from Stanford AI Lab said: "AI is the new electricity. Just as electricity transformed almost everything 100 years ago,… every industry will transform in the next several years."

Jensen Huang, NVIDIA's CEO, have echoed this view early last year: "Generative AI is not a hype cycle... This new way of computing, this new way of solving problems is here to stay, and it's going to touch literally every single industry."

On February 20, 2025, a new report, authored by Josh Freeman and titled "Student Generative AI Survey 2025" was published by the Higher Education Policy Institute (UK), examining how undergraduate students are using AI tools.

The Report confirms that AI Revolution is well underway in higher education:

  • 92% of students now use AI in some form

  • Only 8% of students report using no AI tools whatsoever

  • 88% have used AI for academic assessments

This isn't a trend—it's a fundamental shift that has already happened.

Students have already adapted to the new reality

The survey reveals that students have not only embraced AI but understand its crucial role in their education and future careers:

  • 67% believe AI skills are essential to thrive in today's world

  • 40% believe AI could produce work worthy of good grades

  • 45% of students had already been using AI before arriving at university

Students recognize the value proposition of AI in their education:

  • 51% use AI because it saves them time

  • 50% believe it improves the quality of their work

  • 40% value the instant support it provides

Students from STEM disciplines particularly understand the potential, with 45% confident that AI can produce quality work in their field. They're not waiting for permission—they're preparing for their future careers.

Kids are most generous and kind

One of the most beautiful aspects of this survey is how forgiving kids are toward failings of adults. Despite inadequate support that is most detrimental to their future success, students are remarkably charitable in their assessments.

  • 42% say staff are well-equipped to support them with AI /and we know that this is impossible/

  • 76% believe their institutions could spot AI use in assessments /and we know that this is not true/

These figures are suspiciously high given other data points.

 

But our kind children generously comply with stupid policies: 53% avoid AI for fear of being accused of cheating, only 25% consider it acceptable to include AI text in assignments after editing /even though many more actually do it/.

Fact: institutions are failing their students

Despite students' charitable views, the data paints a damning picture of institutional readiness:

  • Only 30% of students feel encouraged to use AI by their institutions

  • 38% receive unclear or contradictory messages about acceptable AI use

  • 40% believe AI-generated content would get good grades, yet institutions focus on detection rather than integration

Institutions are extremely weak when it comes to AI education and support. Only 36% support students in improving their AI skills, only 26% of institutions provide AI tools and 31% of institutions are actively discouraging or banning AI use.

Student comments reveal the frustration behind these numbers:

"It's still all very vague and up in the air if/when it can be used and why. It seems to be discouraged without the recognition that it will form an integral part of our working lives."

"Simply banning it and not understanding how most students use it or providing resources on AI literacy is more likely to lead to poor and inappropriate use of AI in an assessed context."

"They have not adequately considered the differences in the application of AI in different disciplines, leading to a one-size-fits-all policy that limits our learning."

Is higher education doomed?

The fundamental question is whether higher education can adapt before it becomes irrelevant. With 67% of students believing AI skills are essential for the future, yet only 36% receiving institutional support to develop these skills, we face a critical gap.

The data suggests most institutions are taking a fear-based, defensive approach: 80% have clear policies about AI use in assessments; 76% of students believe their institution can detect AI use – and this implies that institutes are talking about this. But only 29% feel their institution encourages AI use, revealing a primarily punitive rather than constructive approach.

As AI capabilities continue to grow exponentially, this gap between student needs and institutional response will only widen. If universities continue to treat AI as primarily a threat to assessment integrity rather than a fundamental shift in how knowledge is created and accessed, they risk becoming obsolete.

The institutions that survive will be those that recognize what students already know: AI is not just another tool but a transformation in how we learn, work, and think.

Ethiopia: get ready

While this survey focuses on UK institutions, the implications for African universities (Ethiopian in particular) are potentially even more severe. Several factors suggest the AI revolution could create an unprecedented crisis for these institutions:

The leapfrog effect

Much like how many developing regions skipped landline infrastructure and moved directly to mobile technology, students in Africa may bypass traditional educational approaches and embrace AI tools. This survey already shows 45% of students had AI experience before university—a percentage likely to grow rapidly worldwide regardless of institutional infrastructure.

With free versions of powerful AI tools accessible to anyone with an internet connection and a smartphone, African students can access capabilities that were previously available only to those with extensive research resources or library access. This democratization of knowledge access threatens the traditional value proposition of universities in regions where physical educational resources are scarce.

The widening global educational divide

The survey reveals troubling digital divides even within the relatively wealthy UK context, with socioeconomic status, gender, and discipline affecting AI adoption. These divides will likely be amplified in Africa, creating a multi-tiered system where:

  • Elite universities with resources to adapt curriculum and provide advanced AI tools

  • Mid-tier institutions struggling with outdated assessment methods

  • Resource-constrained institutions unable to upgrade infrastructure, train faculty, or integrate AI

The 20% of students in this survey who note AI tools are "too expensive" hints at a more significant barrier in Africa/Ethiopia. Without institutional access to premium AI tools, students with financial means will gain substantial advantages over their peers.

The faculty readiness crisis

The survey shows only 42% of UK students believe their faculty are well-equipped for AI integration—and this represents a significant improvement from 18% the previous year. In Africa, where faculty often have fewer professional development opportunities and higher teaching loads, this readiness gap could be catastrophic.

African/Ethiopian faculty may face an impossible dilemma: either ignore the AI revolution and become increasingly irrelevant, or attempt to integrate technologies they haven't been trained to use and don't have institutional support to implement.

The policy paralysis trap

Many African institutions operate within highly bureaucratic systems with centralized policy development. The survey shows even UK universities struggle to create coherent AI policies. African institutions might find themselves in policy paralysis—unable to develop guidelines quickly enough to match the pace of AI development and adoption.

This creates a scenario where institutions either:

  1. Ban AI tools entirely (unenforceable and counterproductive)

  2. Ignore the issue (allowing unguided and potentially problematic use)

  3. Adopt policies from Western institutions without local adaptation (potentially unsuitable for local context)

The potential for innovative disruption

However, the crisis also presents opportunities. Institutions in Africa might actually have advantages in adapting to AI if they:

  • Face fewer entrenched traditions and bureaucratic barriers to change

  • Embrace AI as a solution to resource constraints rather than a threat

  • Develop assessment models that assume AI use rather than fight against it

  • Create collaborative networks to share faculty development resources

Smartest Ethiopian institutions that survive may leapfrog traditional models and emerge with educational approaches better suited to a world where AI is ubiquitous.

The question is whether leadership in these institutions will recognize the inevitability of this transformation before their students leave them behind.

Let us get to work!

Mikael Alemu Gorsky

Mikael Alemu is an educator and researcher, and the author of two programs: Agentic Software Engineering, on building software with AI agents, and Building AI-Native Agentic Systems, on building software that thinks.

He teaches at the Holon Institute of Technology, near Tel Aviv, where Agentic Software Engineering runs as a credit-bearing course. He is an educator and researcher.

Nine published works, 76 citations. A 350-page textbook under contract with a major academic publisher.

Teaching and programs

Agentic Software Engineering — program, preprint and textbook

The discipline of structured, auditable human-agent workflows for building software. The human frames, specifies and judges. The agent executes. Nineteen modules in four parts, built on a running project called Tribunal, a web application in which agents argue opposing sides of a case and a judge agent decides. Taught for credit at the Holon Institute of Technology.

Agentic Software Engineering curriculum

Building AI-Native Agentic Systems — program, paper and book in writing

How to build systems that hold a language model as a working component, and treat that component as what it is: stochastic, slow and metered. Fourteen modules in four parts, about seventy hours. The running project is the Observatory, a news agency that watches sources, selects what matters and publishes on a cadence.

Research and analytics

Publications — journals and proceedings

Nine works, 76 citations. Research on artificial intelligence in education, with Ilya Levin and Alexei Semenov.

The AI Pravda — LinkedIn newsletter

Critical analysis of artificial intelligence and its effect on work and society. 5,500+ subscribers. The complete archive of 103 issues (2023–2026) is published in full at mgorsky.net/theaipravda.

Subscribe to The AI Pravda on LinkedIn

Pro bono

AI for seniors — free workshop

Helping older adults use everyday AI tools. Delivered to Russian-speaking communities in Israel.

For older adults, artificial intelligence is about preserving quality of life, maintaining autonomy, and sustaining the feeling of independence that defines dignified aging. For seniors who have emigrated, AI becomes a bridge: it can translate documents, explain official letters, help compose emails in the local language, and guide users through government websites. The workshop has been delivered to Russian-speaking communities in Israel, where participants — many of them in their 70s and 80s — discovered that AI could help them read Hebrew documents and communicate with Israeli institutions.

Startup competitions — unpaid time

Judging and mentoring early-stage ventures. Helping teams clarify their value proposition, assess technical feasibility, and prepare for the realities of scaling an AI product.

AC/VC LinkedIn group — community

A group for developers and students working with coding agents. The community shares practical insights, code examples, tool comparisons, and honest assessments of what works in production.

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