Artificial intelligence is changing how software is created, but that does not mean students should abandon computer science. For those choosing CAO courses for 2027, the expansion of AI may make ICT and computing degrees more valuable—not less.
Breaking News: Should students avoid computer science because of AI?
No. The central argument is that AI is likely to increase demand for software, digital infrastructure and technical expertise. While modern AI tools can generate code, identify bugs and produce basic applications quickly, they do not remove the need for people who understand how technology works.
Students considering computer science should look beyond the ability to write routine code. A computing degree can develop knowledge of algorithms, data structures, cybersecurity, databases, artificial intelligence, software architecture and ethical decision-making. Those foundations become more important when technology is being built and deployed at speed.
Why AI is changing technology careers
Generative AI has made programming more accessible. A user can describe a desired function in ordinary language and receive code, suggest corrections or create a prototype. This has led to the growth of “vibe coding”, a term used for building software through conversational prompts and iterative experimentation.
These tools can be powerful, but generated code still needs to be tested, secured and maintained. An application that works in a demonstration may fail when it handles real users, sensitive information or unusual conditions. Understanding the underlying systems allows professionals to recognise those risks.
AI also depends on a substantial technical ecosystem. Models require data, computing power, networks, storage, monitoring and carefully designed interfaces. Organisations need specialists who can integrate AI into existing systems rather than simply produce isolated demonstrations.
Skills that remain important
A future technology professional may spend less time typing every line of code, but more time defining problems, checking outputs and designing reliable systems. Important skills include:
- Logical and computational thinking
- Software testing and quality assurance
- Cybersecurity and privacy protection
- Data analysis and database management
- System design and cloud computing
- Communication, teamwork and project management
- Understanding the social and ethical impact of technology
These capabilities cannot be replaced simply by asking an AI model to produce an answer. They help a person decide whether the answer is accurate, appropriate and safe to use.
Computer science and Ireland’s future workforce
The question has particular relevance in Ireland, where technology companies, public services and businesses depend on digital systems. Ireland’s economy needs people who can develop software, manage information securely and apply emerging tools responsibly.
Demand may shift rather than disappear. Entry-level tasks that once required extensive manual coding could become faster, while employers place greater emphasis on system thinking, technical judgement and the ability to work with AI-assisted development tools.
That change may also create opportunities beyond traditional software engineering. Graduates with computing knowledge can work in data, product development, digital transformation, research, information security, financial technology, healthcare technology and public-sector innovation.
What students should consider before choosing a CAO course
AI should be part of the decision, but it should not be the only factor. Students should consider whether they enjoy solving problems, investigating how systems operate and learning continuously. Technology changes quickly, so curiosity and adaptability are valuable qualities.
Applicants should also examine individual course content rather than relying only on the title of a programme. Relevant questions include:
- Does the course cover programming fundamentals and algorithms?
- Does it offer modules in AI, data, cybersecurity or networks?
- Are there practical projects, work placements or industry links?
- How does the programme address ethics, privacy and responsible technology?
- Will students gain experience evaluating tools as well as using them?
A strong course should prepare students for technologies that are known today while giving them the foundations to adapt to technologies that have not yet been developed.
AI tools still have significant limits
AI-generated software can contain errors, insecure practices and hidden assumptions. Models may produce confident but incorrect explanations, misunderstand a requirement or use outdated approaches. They can also reflect weaknesses in the data used to develop them.
For organisations, responsibility does not disappear when a machine creates the code. People must decide how systems collect and process information, who can access them and how failures will be handled. Regulation and professional standards are likely to increase the need for workers who understand both technology and accountability.
Frequently asked questions
Will AI replace computer science graduates?
AI may automate some tasks traditionally performed by programmers, but it is not expected to remove the need for people who design, test, secure and manage complex systems. The nature of the work is changing.
Is computer science still a good CAO choice for 2027?
For students interested in technology and problem-solving, it can remain a strong option. Applicants should compare course content and career pathways while considering how each programme teaches modern AI and computing fundamentals.
Do students need to become expert programmers?
Programming remains useful, but future roles may also require data literacy, cybersecurity awareness, communication and the ability to evaluate AI-generated work.
Conclusion: AI makes computer science more relevant
The rise of AI is not a reason to avoid computer science. It is a reason to understand digital systems more deeply. As machines generate more software, people will still be needed to define meaningful problems, judge the quality of solutions and ensure technology works safely in the real world.
For students making CAO choices, the clearest takeaway is simple: choose computer science because of an interest in how technology works, not because the field is unchanged. AI may write more code, but computer science remains essential for deciding what should be built, how it should function and who it should serve.