In an era defined by accelerating artificial intelligence (AI) and automation, students and career-seekers face a profound question, that is which degrees are still worth it in 2030? As machines increasingly handle routine tasks and decision-making processes, the value proposition of traditional academic degrees is being reshaped. In this article, we will explore the impact of AI and automation on higher education, highlights degree programmes that appear future-proof, and offers guidance on how to align degree choices with evolving market demands.
How is AI, Automation and the Changing Job Market?
The convergence of AI and automation is transforming work across industries. According to a broad survey of AI and Life in 2030, much of urban life, from transportation to employment, will be deeply intertwined with intelligent systems. One report estimates that by 2030, while some jobs will be displaced, new roles especially in automation, digital services and technology-driven industries will emerge. Degrees that focus purely on tasks easily automated may lose their relative value. For example, some traditional accounting or library science degrees are flagged as being at risk of obsolescence because the tasks they once covered are increasingly automated.
On the other hand, experts also highlight that degrees which emphasise critical thinking, adaptability, technology fluency, and human-centred skills remain highly relevant. So, this is less about whether a degree is worth it at all, and more about whether it equips you for a world of automation and AI.
Which Degrees Are Still Worth It in 2030?
Here are degree pathways that appear well-positioned for the era of AI and automation, along with reasons why they retain value.
1. Computer Science / Artificial Intelligence & Data Science
One of the strongest bets for 2030 is a degree in computer science (CS), especially with a focus on AI, machine learning or data science. The value of such degrees is underscored by industry leaders; for instance, the Chairman of OpenAI states that while coding may become more automated, the deeper systems thinking and algorithmic literacy cultivated by a CS degree remain crucial.
Reports show that degrees in AI and machine learning are among the most future-proof, enabling careers such as AI engineer, robotics developer, or big-data specialist. Because automation and AI will themselves need skilled humans to develop, manage, interpret and govern them, the value of such foundational degrees remains high.
2. Cybersecurity and Information Assurance
As AI and automation proliferate, so too do digital risks cyber attacks, bad actors leveraging AI, and new threat surfaces. Degrees focused on cybersecurity and information security are expected to remain in demand. For example, one source identifies cybersecurity and information security as among the degrees that will be in demand in 2030. As automation increases, the need for human oversight, security and resilience goes up, preserving value in security‐oriented degrees.
3. Biomedical Engineering / Healthcare Technology
Automation is reshaping healthcare too, AI diagnostics, robotics in surgery, wearables and precision medicine are on the rise. A degree in biomedical engineering, life sciences with technology, or healthcare-plus-AI remains a strong choice. These degrees draw on human judgement, ethics, biology, and technology areas where full automation is less likely or at least more complex by 2030.
4. Human-Centred, Ethical & Interdisciplinary Degrees
Degrees that emphasise human judgement, ethics, critical thinking, and interdisciplinary knowledge will increasingly matter. For example, programmes combining philosophy, politics and economics (PPE) with technological literacy or AI governance are cited as future-valuable. In the world of automation, human-centric roles those involving leadership, meaning-making, ethics, policy, creativity are less easily automated.
5. Sustainable Engineering / Green Technology
One less-obvious but important domain is the sustainable engineering, environmental science and green technology. With automation and AI being deployed in large-scale infrastructure, cities, energy systems, a degree that combines engineering, automation and sustainability is promising. Degrees that blend technology with real-world application and human context remain strongly worth pursuing.
What Makes a Degree Worth It in the Age of AI and Automation?
When evaluating whether a degree will be worth it in 2030, keep the following factors in mind:
- Automation resistance
Does it emphasise skills and tasks that machines are unlikely to replicate fully? Such as creative problem-solving, human-machine collaboration, ethical judgement. - Technology integration
Does it prepare graduates to work with AI and automation, not be replaced by them? - Lifelong learning orientation
Because AI evolves rapidly, the ability to upskill, pivot and adapt matters more than ever. - Interdisciplinary breadth
Degrees that bridge technical expertise and soft skills (communication, leadership, ethics) are increasingly preferred. - Alignment with growth industries
Healthcare technology, AI governance, cybersecurity, sustainable systems all are growth areas. - Credential flexibility
Note recent research shows that while degrees remain valuable, skills are gaining relative importance; many employers emphasize certifications, micro-credentials and practical experiences alongside or instead of formal degrees.
A degree is still worth it but it needs to be the right degree, with the right skills, mindset and domain alignment.
What Are the Degrees that May Decline in Relative Value?
It’s also worth acknowledging degrees that might face more pressure in the era of AI and automation:
- Degrees focused on routine tasks with easily automatable workflows such as basic bookkeeping, elementary library science are at risk.
- Fields where job growth is static or where automation is already widely deployed without much human oversight may face headwinds.
Nevertheless, risk does not always mean no value; many degrees can still provide value if combined with the right adaptation, but the margin for error becomes smaller.
Hence, as we approach 2030, the interplay of AI and automation will reshape not just jobs, but the value we derive from university degrees. The good news is there are plenty of degrees that remain worth the investment especially those aligned with technology, human-machine collaboration, security, healthcare, sustainability and ethics. The challenge is ensuring your degree is not just a credential, but a platform for continuous learning, adaptation and relevance.
Other than AI and Automation: Which Degrees Are Still Worth it, you can also read Degrees That Are Most at Risk of AI in 2026
So, if you are selecting a degree now, look for programmes that offer strong technical foundations and human-centric skills, that prepare you to work alongside intelligent systems, and that give you the agility to pivot as the ground shifts. In a world of automation, the most resilient degrees will be those that emphasise what humans do best; thinking, adapting, leading, innovating.
Hence, yes, degrees are still worth it in 2030 but the value lies in choosing wisely, staying adaptable, and integrating your learning with the realities of AI and automation.
FAQs
1. Will getting a non-tech degree still be worthwhile in 2030 given AI and automation?
Yes, but you will need to ensure that your domain emphasises human-centred skills (empathy, leadership, ethics, creativity) and that you augment it with technological literacy. Degrees that combine non-tech content with an understanding of AI/automation stand a better chance of staying relevant. For example, public policy with AI governance or psychology with data analytics.
2. Should I drop a traditional degree and focus on short courses or micro-credentials instead?
Micro-credentials and skills-based learning are increasingly important, especially in fast-moving fields. Research shows that skill-based hiring is growing in recruitment for AI/automation roles. However, a full degree still offers foundational depth, structured learning, network effects and signalling value. The best approach is to pursue a degree and stay agile by stacking relevant micro-credentials.
3. If I choose a safe degree like computer science or cybersecurity, should I worry about automation replacing those jobs too?
You should prepare for change but don’t assume replacement. For example, even in software engineering, research shows developers will increasingly work with AI assistants, shifting roles rather than disappearing entirely. With degrees like computer science or cybersecurity, staying updated, specialising in emerging subfields (AI governance, ethics, secure automation) and focusing on human-machine synergy will help ensure your value remains high.