AI presents challenges and opportunities for learning, teaching and assessment.

How do universities prepare students for working life and educate them in the responsible use of AI? How can they be assessed in a way that accurately reflects their own knowledge and intellectual ability and upholds academic integrity?

Students need content and context to apply AI tools to. They also need a baseline of knowledge and practice so they can use AI critically and constructively. The simulation provides both.

SustainabilitySim covers both the academic challenges of AI in learning and assessment, and its ethical and commercial use in business. It helps students learn how to use AI responsibly and critically.

Academic

Several key tasks within the simulation require students to present their ideas, individually and in groups. There is proven pedagogical and skills value in getting students to share their ideas verbally. Oracy is not only a vital professional skill. It demonstrates retained knowledge and embedded expertise that can’t be replaced by AI.

Working with simulated content that is outside the scope of LLMs, can help ensure that students are producing their own ideas and analysis. Other approaches and measures are needed too, e.g., open questions, answers that require students to draw on personal experience, and regular in-simulation submissions of work for ongoing assessment.

Authentic assessment supports this, testing not only what the students knows but also how that knowledge is applied.

The QAA has produced guidance on the use of AI in higher education, including:

“Practical ways to foster AI skills, ensuring that students develop not only AI literacy but the capacity for meaningful critical engagement.”

“Educators can move beyond surface-level GenAI literacy to foster deeper criticality in students. As higher education continues to evolve alongside AI technologies, embedding these practices into teaching will help ensure that students are not only users of GenAI but informed critics and ethical stewards of its application.”

QAA: An evidence-based toolkit on leveraging Generative AI to support the graduates of the future

Business

SustainabilitySim helps prepare students for the ethical and commercial use of AI in business.

Employers’ AI literacy expectations of graduates

Appropriate use: data extraction and basic analysis; preliminary research, drafting outlines: repetitive or manual task automation

Human‑Led responsibilities: interpreting outputs; forming conclusions; sceptical evaluation of AI‑generated content and opinions; ensuring compliance with professional and ethical standards

Critical and responsible use indicators: transparency about AI’s contributions to work; ability to critique and refine AI outputs; avoiding plagiarism with appropriate referencing; consistent alignment with organisational and data-protection policies.

Scenario & tasks (1)

AI presents challenges to the Consulting sector. Its integration is disrupting the traditional business model of consulting firms, which has historically relied on billing clients for time spent on projects. Consultants are being forced to consider how credibility with clients is earned and protected.

Clients expect consulting firms to pass on the financial benefits of AI-driven productivity in the form of lower costs. Some are even questioning the use of consultants for some projects if they can generate the required expertise and advice themselves using AI.

Clients are seeking a shift to payment based on delivery rather than time. Consultancies are under pressure to protect their income streams without losing business or revenue.

The consultancy in the simulation, Twelvex, has decided to review its policy on AI use and the impact on client outcomes. Their consultants (the students) are tasked with reviewing its client fees and justifying a transition towards delivery-based pricing.

Scenario & tasks (2)

In the simulation students are tasked with critically evaluating an AI-generated ESG Strategy, comparing it to the one developed for the client by the consulting team. This is in response to the client’s request to justify the uniqueness of their expertise and the value of their services.

The exercise enables students to recognise the value and limitations of AI. It also reminds them of the reality that awaits them in business, especially in consulting, where clients may question the value of AI-generated advice and expertise.