Yakun Zhang
What happens when students swap essay writing for real business challenges, with a dose of generative AI on top? Spoiler: things get delightfully messy – in the best pedagogical sense.
We talk a lot about employability skills in higher education—but let’s be honest, some of our assessments still look like they were designed for a Victorian clerkship. Timed essays and rigid formats might tick the academic boxes, but they don’t exactly prepare students for the chaotic, creative, fast-moving world they’re stepping into (Jackson, 2013; Manville et al., 2022).
No employer is sitting around saying, “What we really need is someone who can quote Kotler chapter and verse under pressure.” They’re looking for sharp thinkers, digital-savvy doers, team players, and people who can roll up their sleeves and solve real problems. In other words, graduates who can actually do the job—not just write about it.
Authentic assessment meets GenAI
Authentic assessment isn’t a buzzword (or it shouldn’t be). It’s about asking students to demonstrate the skills, knowledge, and attitudes they’ll need in the workplace (James & and Casidy, 2018; Sokhanvar et al., 2021). In marketing, that means campaign design, strategic planning, creative execution, and digital literacy. Enter generative AI tools like ChatGPT, Canva AI, and SEMrush – the co-pilots of modern marketing.
Instead of banning GenAI, why not integrate it in an ethical manner? That’s precisely what we trialled in a Level 7 content marketing module: a live brief with a London-based fashion SME. Students tackled a genuine content marketing challenge, co-created goals with the client, and delivered portfolio-ready outputs they could confidently showcase to employers.
The brief that wasn’t so brief
Teams created campaign posters as formative assessment, then developed full content marketing plans individually for summative assessment. Tools like SEMrush provided audience insights, ChatGPT drafted taglines, and Canva AI transformed ideas into visuals. All underpinned by guided sessions on ethical and critical AI use – shifting the narrative from “AI as cheating” to “AI as creating with integrity” (Johnston et al., 2024; Zhu et al., 2025).
What happened?
Students didn’t just survive—they thrived. One even called it “a creative subject with real-world excitement” (which, let’s be honest, is high praise in a world of group projects and 9 a.m. lectures). Average grades increased by 24%, but more importantly, students walked away with portfolio-ready work that actually means something—evidence of creativity, strategic thinking, and solid problem-solving skills.
And the SMEs? They didn’t just nod politely for the university newsletter photo op. They got real value—ideas backed by research, prototype assets they could actually test, and fresh insights into how to better connect with their audience. And here’s the cherry on top: through conversations with one founder to nail down their needs, I got to know their business so well that I ended up recommending a student looking for marketing experience. Long story short: internship secured. Everyone won. It’s the kind of collaboration that doesn’t just tick boxes—it builds real bridges between classrooms and boardrooms.
So what?
Beyond the satisfaction of receiving good module feedback, authentic assessment with GenAI prepares students for workplaces that AI is already transforming. Marketing roles increasingly require AI fluency – from drafting first-line copy to generating quick design prototypes. Simulating this reality in assessments gives students confidence and a competitive edge (Manville et al., 2022).
However, let’s not romanticise. Integrating AI reveals a harsh reality: unequal access. Students who can afford premium tools, such as ChatGPT Plus or Grammarly Premium, receive better support. This isn’t about ability; it’s about resource disparity. The risk? Systemic bias in assessment outcomes further entrenches inequalities (Zhu et al., 2025).
Now what?
Future research should unpack:
• What do students value most in live brief-based authentic assessments?
• What challenges do they encounter with real clients and AI tools?
• Do these experiences feel empowering or exploitative, and why?
• What support structures foster equitable engagement and outcomes?
The goal is not just higher grades or happier employers but inclusive, empowering, and future-ready learning environments.
Final reflections
Authentic assessment in marketing isn’t about ticking an employability box. It’s about bridging the often-yawning gap between theory and messy, caffeinated, client-driven reality. Adding AI tools into the mix doesn’t replace creativity; it reframes it. Students learn to ask better questions, iterate ideas rapidly, and critically evaluate machine-generated suggestions.
Ultimately, it’s not about AI versus humans or universities versus industry. It’s about creating learning ecosystems where students, educators, and SMEs grow together – ethically, creatively, and authentically.
References
Jackson, D. (2013). Business graduate employability – where are we going wrong? Higher Education Research & Development, 32(5), 776-790. https://doi.org/10.1080/07294360.2012.709832
James, L. T., & and Casidy, R. (2018). Authentic assessment in business education: its effects on student satisfaction and promoting behaviour. Studies in Higher Education, 43(3), 401-415. https://doi.org/10.1080/03075079.2016.1165659
Johnston, H., Wells, R. F., Shanks, E. M., Boey, T., & Parsons, B. N. (2024). Student perspectives on the use of generative artificial intelligence technologies in higher education. International Journal for Educational Integrity, 20(1), 2. https://doi.org/10.1007/s40979-024-00149-4
Manville, G., Donald, W. E., & Eves, A. (2022). Can Embedding Authentic Assessment Into the Curriculum Enhance the Employability of Business School Students? GILE Journal of Skills Development, 2(2), 73-87. https://doi.org/10.52398/gjsd.2022.v2.i2.pp73-87
Sokhanvar, Z., Salehi, K., & Sokhanvar, F. (2021). Advantages of authentic assessment for improving the learning experience and employability skills of higher education students: A systematic literature review. Studies in Educational Evaluation, 70, 101030. https://doi.org/https://doi.org/10.1016/j.stueduc.2021.101030
Zhu, W., Lei, H., Xinni, Z., Xiaoya, L., Gaojun, S., Jingxin, Y., & and Wang, C. (2025). Could AI Ethical Anxiety, Perceived Ethical Risks and Ethical Awareness About AI Influence University Students’ Use of Generative AI Products? An Ethical Perspective. International Journal of Human–Computer Interaction, 41(1), 742-764. https://doi.org/10.1080/10447318.2024.2323277
Dr Yakun Zhang is a Senior Lecturer in Advertising and Marketing Communications at the University of Greenwich. She is passionate about bridging theory and industry practice through authentic assessment and co-creation. Her teaching focuses on marketing communications, consumer psychology, creative content, and trends in advertising. At the same time, her research explores how sensory stimuli, such as images and sounds, enhance the effectiveness of advertisements.
Email: yakun.zhang@greenwich.ac.uk