Should I switch to a tech degree because of AI?

Not unless you want to work in tech. AI affects every field, so switching to CS does not protect you from change. A lawyer who understands AI will be more valuable than a CS graduate who cannot code. Stay in your field and learn to use AI within it.

Will my degree be worthless by the time I graduate?

No. Degrees remain valuable as credentials, as proof of sustained effort, and as structured learning. What may change is which specific skills from your degree employers test for. Adapt by building practical skills alongside the academic content.

Is AI just hype that will fade?

The specific tools will change. ChatGPT might be replaced by something better. But the underlying trend, machines that can process language and generate content, is not going away. The safe bet is to learn to work with these tools while building skills they cannot replace.

What AI means for the degree you just started | Campus

What AI means for the degree you just started

AI changes what is valuable about your degree, not whether it is valuable. Memorising facts matters less because AI retrieves them instantly. Understanding, problem-solving, and applying knowledge to real situations matter more because AI cannot do those reliably. Students who work with AI while building deep understanding will outperform those who ignore it and those who depend on it.

What AI changes about university learning

Before AI, a lot of university work rewarded memory. Memorise definitions, reproduce procedures, recall case studies. AI makes that kind of work worth less, because a language model can generate a definition faster than you can write one.

What AI cannot do well: apply a concept to a specific, messy, real-world problem. Debug code it has never seen before. Evaluate whether a business idea makes sense in the Kenyan market. Lead a team through a disagreement. These require judgment, context, and experience that AI does not have.

This means the valuable parts of your degree are shifting. The lectures that teach you to think (case studies, design projects, problem sets) are becoming more important. The lectures that teach you to memorise (rote definitions, fill-in-the-blank exams) are becoming less useful, though you still need to pass them.

Which degrees are more affected

Content-heavy degrees (law, humanities, business) feel the shift most. AI can generate essays, summarise cases, and draft reports. If your degree mostly tests written output, you need to develop skills that go beyond what AI can produce: critical analysis, original research, and practical application.

Technical degrees (CS, engineering, medicine) are affected differently. AI can write code, but it writes buggy code that someone needs to review. AI can suggest diagnoses, but a doctor needs to examine the patient. The core of these degrees (building, diagnosing, designing) remains human. The routine parts (looking up syntax, writing boilerplate) get faster with AI.

Creative degrees (design, media, architecture) face a mixed picture. AI can generate images and copy, but the creative direction, the taste, and the understanding of what a client actually needs remain human skills. Students who learn to use AI as a tool for faster iteration, not as a replacement for creativity, will do well.

What to do about it while you are still studying

Learn to use AI tools properly. The guide on AI tools for university work covers how to use them without undermining your own learning. Treat AI as a study partner, not a ghostwriter.

Focus on skills AI cannot replicate. Problem-solving, teamwork, communication, and the ability to apply knowledge to new situations. These are the skills that will still be scarce when you graduate, regardless of how good AI gets.

Build things, not just essays. A project that works (a deployed app, a research prototype, a business plan you executed) proves you can do something AI cannot: take an idea from zero to reality. Build your first real project and keep building.

Stay current. AI tools change every few months. The student who learned ChatGPT in 2024 and never explored new tools is already behind. Follow AI developments in your field. Experiment with new tools as they appear. Being comfortable with change is itself a career skill.

What to do this week

Identify one AI tool relevant to your field and spend an hour learning to use it this week.
In your next assignment, use AI to help research but write the analysis and conclusions yourself.
Start one project this semester that demonstrates a skill AI cannot replicate in your field.

Frequently Asked Questions

Should I switch to a tech degree because of AI?: Not unless you want to work in tech. AI affects every field, so switching to CS does not protect you from change. A lawyer who understands AI will be more valuable than a CS graduate who cannot code. Stay in your field and learn to use AI within it.
Will my degree be worthless by the time I graduate?: No. Degrees remain valuable as credentials, as proof of sustained effort, and as structured learning. What may change is which specific skills from your degree employers test for. Adapt by building practical skills alongside the academic content.
Is AI just hype that will fade?: The specific tools will change. ChatGPT might be replaced by something better. But the underlying trend, machines that can process language and generate content, is not going away. The safe bet is to learn to work with these tools while building skills they cannot replace.