Part 4: Using AI for your career

When using Generative AI for career information or Labour Market research, hallucinations can be very common due to constant changes in sector specific legislation and initiatives. As a result, there is a risk that it may not provide factually correct information, which could mislead you into making the wrong career decisions or inputting incorrect information into a job application.

Critical thinking questions

1. How important is it that the career information you're using is factually accurate? For example, links to webpages, job listings and Labour Market Information (LMI).
2. How will you check if job or qualification requirements mentioned by AI are up to date and relevant to your industry or region?
3. Are you cross-checking AI information against official job sites (for example, Prospects.ac.uk, National Careers Service) or advice from your university careers team?

With the increase of misinformation across the internet and social media, there's an increased risk that you may be presented with career information or advice from false or non-credible sources.

Critical thinking questions

1. How can you tell what sources an AI tool is drawing from when giving careers advice?
2. How is the AI careers advice output specific to your location, industry, or level of experience?
3. What other tools (for example, LinkedIn, Handshake, Prospects.ac.uk) might give you more targeted careers advice information?

Some AI tools may offer career advice and cite career development theories to support their advice. This can sometimes be a good starting point for exploring new ways of thinking about your career goals, however, it is recommended that this approach is paired with speaking to a career adviser to get more tailored and personalised advice.

Critical thinking questions

1. When considering theory to support your career decision-making process, how relevant is that career development theory to modern society?
2. Can you draw personal experiences from the theory?
3. Would following certain recommendations of the theory make you feel uncomfortable?

Questions for those who teach, support and/or assess learning

1. How can you help students recognise the limitations of AI tools, such as a lack of reliable sources, in their academic or career development?
2. In what ways could you incorporate discussions about AI's limitations into your own teaching, learning support or careers guidance activities at university?

As explained earlier, some Generative AIs may have been trained on data that is not up-to-date. They may also struggle to provide answers around atypical career paths or new careers or jobs that may not have existed a year or two ago.

Critical thinking questions

1. How do changing laws and regulations around data access (for example, in different countries) affect the kind of career or academic support AI can offer you as an international student?
2. Is the AI including updated laws and regulations within specific job roles or sectors in its responses to you?
3. How recent is the data that the AI is accessing when providing you with information about a job or career pathway?
4. What steps can you take to check or verify AI-generated information, especially when making important decisions like applying for jobs or preparing for interviews?

Questions for those who teach, support and/or assess learning

1. How can you help students recognise the limitations of AI tools, such as outdated knowledge, in their academic or career development?
2. What do you think your responsibility is when using AI tools in peer support, teaching, careers guidance or mentoring, especially when it's unclear what data the tool was trained on?
3. In what ways could you incorporate discussions about AI's limitations into your own teaching, learning support or careers guidance activities at university?
4. What could you suggest students access as an alternative which could provide more up-to-date information (Prospects.ac.uk, luminate.prospects.ac.uk, ISE.org.uk)

The use of AI tools has contributed to a 44% increase in the volume of applications for graduate jobs (59% increase in 2024) (ISE, 2025). There are now approximately 140 applications per graduate job. As a result, employers are using AI-detection software to check applications for AI use. This is making it more important than ever to produce authentic, tailored, and personalised content for each opportunity you apply for. Many employers are highlighting that they are coming across more generic CVs and applications. AI-generated CVs, cover letters, or personal statements often use vague phrases like 'I am a motivated team player' that fail to distinguish you from other candidates. When applying for jobs, look out for the company's application guidance and use it to help you write your applications. 

Critical thinking questions

1. Does your application include specific, evidence-based examples that reflect your actual experience? (also refer back to the section on false information and hallucinations)
2. How can you revise AI-generated content to reflect your personal/human voice and goals?
3. How do you define originality in professional writing, and does your submission meet that standard?
4. Are you convinced that the AI-generated content is showcasing your skillset, behaviours, and experiences?
5. Would you be able to talk about the AI-generated content if an employer asked you about it in an interview?

Questions for those who teach, support and/or assess learning

1. How can you help students, especially international students, avoid submitting generic, AI-like applications and instead express their individuality in CVs or personal statements?
2. What advice would you give to students using AI-generated job application content to make sure it sounds authentic, accurate, and aligned with their real skills and experience?
3. How can you teach or model best practices for using AI in career preparation, like using it to mindmap or structure, but not to replace the student's own voice and insights?

Suggested reading

Institute of Student Employers (2025) Graduates pivot careers due to AI and job automation. Available at: https://ise.org.uk/knowledge/insights/431/graduates_pivot_careers_due_to_ai_and_job_automation/ (Accessed: 21 July 2025).

Content produced by Generative AIs may lack clear evidence of reasoning, understanding of context, and critical thinking. They may struggle to identify nuances in concepts or logically construct a solution to an employer's problem. This may lead to inaccuracies or generalisations where clarity and specificity is required. 

Critical thinking questions

1. Have I checked the AI-generated content against the information on the company that can be found on LinkedIn or their website?
2. Is the AI-generated content including things that I understand and could elaborate on in an interview setting?
3. Is the AI-generated content including things that I can talk about and be critical of through my own professional, academic or personal experience?

Questions for those who teach, support and/or assess learning

1. How can critical thinking be embedded as a core employability competency across disciplines and support services?
2. How can we teach students to critically evaluate AI-generated careers content (for example, job descriptions, market trends, or interview prep tools)?
3. In what ways might overreliance on AI weaken students' ability to construct personalised, well-argued applications or interview responses?

Personal experience is key for employers when considering applicants for a role. Therefore, you need to be able to showcase your experience through personal and relevant examples, that also have a level of complexity to them so that an employer has confidence in your ability to do a job. This is extremely important when creating a CV or writing application answers as you will need to elaborate on these experiences with more context in an interview. If your examples are AI-generated, it will be significantly more challenging to bring these examples to life or answer follow-up questions.

Critical thinking questions

1. What personal experiences, values, or insights can you offer that AI tools cannot replicate in a job application or interview?
2. Are you using AI to enhance your self-presentation, or are you unintentionally removing the personal narrative that employers value?
3. What's more important to you: Something that sounds professional or something that sounds real?
4. Does an AI-generated experience show a journey of personal growth or learning for you?

Questions for those who teach, support and/or assess learning

1. In employability-focused teaching, how do you reinforce that experience-based storytelling is a key skill AI cannot replicate?
2. How can students be encouraged to connect their experiences with career goals in a way that is critical, reflective, and emotionally intelligent, not just algorithmically correct?

Although there is an ever-growing number of AI tools to support you with your career development, decision making, and application skills, we would always recommend that you are critical of these tools and seek clarity and guidance from career professionals at the university.

Critical thinking questions

1. Is it ethical to use AI to write your CV, cover letter, or application responses without disclosing it? Why or why not?
2. Should employers be told if a candidate used AI to prepare for the interview? Where should we draw the line between preparation and misrepresentation?

As mentioned earlier, Generative AIs can create biases based on the data it's been trained on. This can lead to content being produced that may not align with yours or an employer's beliefs or values.

Critical thinking questions

1. How might the AI you're using reflect social or cultural biases - and how could that affect your job applications or career decisions?
2. What voices, experiences, or identities might be missing or misrepresented in the AI-generated advice you receive?