AI literacy is not enough.
Your subject comes first. AI is taught through the standards of your field.Learn with AI. Judge it through your subject.
You will be taught not to accept AI uncritically. You will learn when it is useful, when it is limited and how to test it against the standards of your discipline - safety, evidence and fairness, originality, responsibility and professional judgement.
- Use AI selectively where it supports your learning
- Judge AI by the standards of your subject
- Learn what 'fit for purpose' means in your future profession
- Graduate ready to question, create and lead.
What makes Surrey’s approach different?
Universities must teach AI through disciplinary standards.
AI literacy helps you use the tool. Disciplinary standards help you decide whether, when and how the tool should be used. In every subject, you will learn what a good AI answer looks like – and how to spot a weak one. A good AI answer looks different in every subject, explore our examples below.
See AI in action Choose your subject
Pick a subject area to see what you might actually do with AI at Surrey – and the disciplinary standard you would use to judge whether the output is good enough.
These are examples: AI will be taught through the standards of your own course.
Example Accounting and finance
Use AI to generate complex financial forecasts and models – then rigorously audit the outputs for calculation errors, flawed assumptions, and structural inaccuracies.
What you might do as a student
You might take an intentionally flawed AI-generated financial forecast, create an annotated audit trail highlighting the errors, and submit a fully corrected model alongside a sound investment recommendation.
The disciplinary standard
Is it mathematically accurate, thoroughly audited, and financially sound?
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Example Business
Use AI to simulate a competitor's market behaviour and generate offensive strategic moves – then rigorously critique the outputs for logical flaws to develop a stronger, more resilient counter-offensive.
What you might do as a student
You might prompt an AI to act as a rival attacking a struggling company, write a critique of the AI's strategic blind spots, and submit a superior, human-developed counter-strategy.
The disciplinary standard
Is the final strategy competitively robust, logically sound, and clearly superior to the AI's baseline?
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Example Computer science
Use AI tools to prototype, debug and evaluate code while learning how models work, where they fail and how to build systems responsibly.
What you might do as a student
You might use AI to draft code, then test, secure, explain and improve it yourself.
The disciplinary standard
Is it robust, secure and explainable?
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Example Economics
You will benefit from using AI to source, process and analyse vast amounts of economic data and other sources of information to complete a task under a tight time limit, while keeping a critical eye on the generated output.
What you might do as a student
You might be given one hour to produce a policy brief. Using your existing knowledge from the module and, supported by AI tools, you will predict the effects of AI on the labour market and formulate a policy response and recommendations to alleviate the negative effects of this change.
The disciplinary standard
Is the output produced by AI reliable, accurate and aligned with economic theory?
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Example Engineering
Use AI to generate design ideas, compare options and run early checks - then use engineering judgement to decide what is safe, realistic and worth building.
What you might do as a student
You might ask AI for three bridge concepts, test the assumptions, spot the weak one and improve the final design.
The disciplinary standard
Is it safe, buildable and sustainable?
Example English literature and creative writing
Students are learning to use AI critically in relation to narrative, authorship, creative process and literary judgement. Examples include AI discussion built into modules such as Thinking Like a Critic, critical AI skills in creative writing modules, and assessment changes such as writer's logs, process-based commentaries, presentations and podcasts.
What might you do as a student
You might use AI to generate or compare possible creative approaches, then use your own literary and critical judgement to decide what is original, ethical and convincing.
The disciplinary standard
Does it strengthen interpretation, creativity and critical judgement, or does it flatten voice, context and originality?
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Example Health sciences
Use generative AI tools critically and responsibly to support evidence-informed decision-making, while maintaining independent professional judgement and prioritising patient safety, ethics and compassionate care.
What you might do as a student
Use a generative AI tool to explore a healthcare scenario, evaluate the quality and reliability of the information provided, identify limitations, bias and inaccuracies, and determine where further evidence or professional judgement is required.
The disciplinary standard
Use generative AI tools in a way that is evidence-informed, ethically sound, professionally accountable, and safe for people receiving care, recognising that responsibility for decisions remains with the practitioner.
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Example Hospitality and tourism management
Use AI to explore complex visitor economy scenarios, service systems, and strategic decisions – then apply disciplinary judgement to validate, refine, and justify recommendations using sector knowledge, evidence, and real-world constraints.
What you might do as a student
You might use AI to support comprehension of a complex case, generate alternative interpretations of visitor behaviour, map a service journey, compare destination or event development options, explore aviation or hospitality market scenarios, or stress-test a business plan. Your work would not simply reproduce the AI output. Instead, you would show how AI helped your thinking, where its reasoning was incomplete or unrealistic, and how you used evidence, theory, data, and professional judgement to develop a stronger final analysis or recommendation.
The disciplinary standard
Does the work demonstrate sound sector knowledge, logical reasoning, ethical and sustainable judgement, appropriate use of evidence, and recommendations that are operationally, commercially, and socially realistic?
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Example Human and animal health
Use AI to understand patterns and support better decisions while keeping patient safety, evidence, ethics and human care at the centre.
What you might do as a student
You might review an AI-generated health explanation and identify what needs evidence, caution or a human professional.
The disciplinary standard
Is it evidence based, ethical and safe for people and animal care?
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Example Games design and games art
New modules have been designed with GenAI in mind, using project work, guided themes, workshop-based development, reflective reporting and practical artefacts that require students to evidence their own design process. Programming for games also includes discussion of how GenAI can help identify errors, explain code and support learning, while also addressing industry expectations, code tests, ethics and environmental impact.
What might you do as a student
You might use AI to help debug or explore ideas, but your final game artefact, design choices and reflective account show your own development process.
The disciplinary standard
Is it playable, purposeful, technically understood and genuinely your own design work?
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Example Languages, translation and interpreting
This is one of the strongest areas of existing AI integration. Students are engaging with machine translation, GenAI, LLMs, computer-assisted interpreting tools, smart translation technologies, and the critical evaluation of AI output. Several modules already ask students to evaluate the quality, effectiveness and limitations of AI-generated translation or interpreting support.
What might you do as a student
You might compare an AI-generated translation with your own version, identifying errors, cultural nuance, tone, register and ethical limitations.
The disciplinary standard
Is it accurate, culturally appropriate, professionally usable and ethically defensible?
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Example Law
Use AI to assist in analysing case law and to interrogate your legal arguments. AI can assist in sharpening your reasoning skills so that you can apply your best legal judgement towards building a robust and defensible position.
What you might do as a student
You might use AI to extract key strands of argument from case law or to translate technical concepts into accessible terms. You could use AI to create complex or novel legal disputes for discussion and problem-solving application. AI could also act as an "opposing" lawyer and create counter arguments to test your understanding and reasoning of the law.
The disciplinary standard
Is the position developed with the support of AI tools legally defensible and grounded by accurate sources and evidence? Is it ethically crafted and argued?
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Example Marketing
Use AI to generate multi-platform social media content for specific consumer personas – then critically refine the output to ensure a distinct brand voice, platform-specific nuance, and strong editorial control.
What you might do as a student
You might prompt an AI to draft a week's worth of content, submit the raw text alongside your own tracked-changes edits, and write a brief reflection justifying your adjustments to the tone across different platforms.
The disciplinary standard
Does it demonstrate clear editorial control, platform literacy, and an authentic brand voice?
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Example Media
Students learn to use AI critically and responsibly across film production, animation, digital arts and broadcast engineering. This includes exploring how AI can support coding, research and writing, while considering when its use is appropriate and how its outputs should be tested against reliable sources, technical knowledge and professional standards.
What you might do as a student
You might use AI to help identify a problem in computer code or support research into a film or broadcast technology. You would then check the output, draw on credible sources and explain the technical and creative decisions behind your work.
The disciplinary standard
Is it technically sound, supported by reliable evidence, ethically used and demonstrably your own work?
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Example Music
Modules in music have been redesigned to enable students to engage critically with GenAI and gain valuable skills to prepare them for all areas of employment. You might for instance be writing an innovative patchwork text or engaged in a conversational lectio divina assessment, as a means of exploring the processes behind your written, performed, and composed work.
What you might do as a student
AI is embedded in Music modules in sector-leading ways using innovative pedagogies. You might use AI to identify sources of information or enhance spans of text you can robustly evaluate yourself, or to generate musical building-blocks such as isolating stems in an audio track for you to rework into a fully-fledged composition.
The disciplinary standard
Does use of AI facilitate acts of musical creation, interpretation, and research, or does it stifle creativity? How does it diversify knowledge, and at what cost (ethical, environmental, social, health, financial, employability, scholarly, human)? How might it be used in real-world contexts in the writing of, and about, music?
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Example Performing arts and technical theatre (Guildford School of Acting)
GSA examples show a particularly strong emphasis on AI as a tool for research, reflection and idea generation, rather than as a replacement for embodied, creative or collaborative practice. AI has been integrated into areas such as rehearsal and research, professional skills, singing repertoire preparation, production/theatre contexts, and foundation-level study skills. Assessment redesign often focuses on making reflective process, personal contribution and professional judgement more explicit.
What might you do as a student
You might use AI to support initial research for a role, repertoire choice or production context, then test that material through rehearsal, embodiment, collaboration and reflection.
The disciplinary standard
Does it support truthful, ethical and personally owned creative practice, rather than replacing the performer’s or creative’s judgement?
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Politics
Use AI to analyse political behaviour, institutional change and the dynamics of international relations and foreign policy, visualise patterns, and present evidence to inform policy and public debate – then critically assess outputs for bias, rigour, clarity and communicative purpose.
What you might do as a student
You might use AI to process survey data on political preferences, identify and visualise trends, and draw conclusions about a topical political puzzle, such as what drives citizen dissatisfaction with democracy today.
The disciplinary standard
Whose interests does AI serve, how reliable is the evidence it produces, and does the argument add substantive value to public and policy debate?
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Example Sociology
Use AI to analyse qualitative and quantitative data, while thinking critically about the ethics, power and regulatory frameworks involved in artificial intelligence.
What you might do as a student
You might use AI to support your quantitative and qualitative data analysis. You will develop an understanding of the benefits associated with the use of different AI tools. You might consider the ethical and regulatory landscape surrounding AI use.
The disciplinary standard
What power structures support and are upheld by AI agents? How can we critically interrogate and challenge the knowledge produced by machines?
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Testimonials
- Surrey's AI in Education framework is a progressive approach that utilises modern tools in the present world and equips our students for the future, while recognising both the opportunities and concerns students have about AI.
Matt Aikin President, University of Surrey Students' Union - By working closely with the Students' Union and the wider student body, the University has developed a framework that supports responsible use, builds students' professional judgement, and gives Surrey graduates a real edge in a world of work being transformed by AI.
Luana Vasconcelos Vice-President Voice, University of Surrey Students' Union
Your Surrey degree in an AI-shaped world
You are studying at a time when AI is changing almost every profession. That is why, from September 2026, we are embedding AI across our degrees in ways that are specific to each subject.
You will get opportunities to experiment with AI in the context of your subject, using it to explore ideas, test options, and build confidence with technologies that are reshaping professional life.
The aim is simple: you will not just learn how to use AI. You will learn how to judge it.
You do not need to be an AI expert
Build confidence step by step.
Whether you have already used AI tools, barely tried them, or feel sceptical about them, Surrey will help you understand when they are useful, when they are not, and how to stay in control of the final decision.
- Start from your subject: You learn AI in the context of the course you actually chose.
- Practise safely: You explore what AI can do before applying it to more complex work.
- Spot weak answers: You learn how to identify errors, bias, gaps and overconfident claims.
- Own your work: You learn to explain your decisions and show what you contributed.
What this means in practice
You will not just use AI. You will learn how to judge it.
The same AI answer can be useful in one subject and unsafe, weak or unacceptable in another. At Surrey, you will learn AI through your course, not as a generic add-on. You will test its outputs against the standards of your subject and learn when to use it, when to challenge it, and when to reject it.
FAQs
AI should feel useful, not forced. These are the questions many students ask.