Chair: Denise Hawkes (King’s Business School, Royal Economic Society Professional Development & Education Committee)

Panellists: Prof.Emiliya Lazarova, University of East Anglia; Dr. Petar Stankov, Royal Holloway; Dr. Ioanna Papatsouma, Imperial College London

On 26 November 2025, we hosted our latest EconTEA to mark the launch of the CTaLE–Royal Economic Society Report on Rethinking Economics Assessment for a GenAI World. Chaired by Denise Hawkes (King’s Business School), the event brought together academics in Economics and Statistics to explore how generative AI is transforming the way we teach and assess and comment on our report.

The discussion made one thing clear: AI is not a passing trend – it’s a structural shift. Universities must rethink both what they assess and how they assess it.All the speakers agreed that institutions must balance innovation with safeguarding the integrity of degrees, that assessment reform should combine formative tasks where AI can be used productively with in‑person exams to validate independent skills, and that sector‑wide coordination is needed. However, rigid standards may stifle innovation. A further point was the importance of cross‑disciplinary learning, with economists encouraged to draw lessons from statisticians and other fields to avoid siloed solutions.

Emiliya Lazarova, as Head of Economics at UEA and Chair of CHUDE (the RES’s Committee of Heads of University Departments of Economics), stressed the heavy responsibility carried by heads of departments and highlighted the need to empower academics to innovate while protecting the value of degrees, and encouraging experimentation even if not all attempts succeed. Petar Stankov from Royal Holloway proposed concrete reforms, suggesting that quizzes and problem sets become formative with AI allowed, while final exams remain in‑person, so that students learn with AI but are disincentivized from offloading all cognitive effort. Ioanna Paptsouma from Imperial College London, representing the Royal Statistical Society, emphasized the importance of cross-disciplinary interaction and learning, taking as example the statistical community’s experience, showing how cross‑disciplinary exchange can guide assessment redesign and prevent isolation.

In conclusion, the discussion underscored that adapting to AI in higher education requires collective reflection, flexible reforms, and interdisciplinary collaboration. Empowering academics, rethinking assessment design, and learning from other disciplines were identified as essential steps toward a sustainable future for higher education as well as for economics.

Note: This blog was written by Co-Pilot, with some small edits by Silvia Dal Bianco, as CTaLE officer. The transcript from the Zoom recording was uploaded and the tool was prompted to use the text to write a summary of the discussion. As CTaLE are very resource constrained we find this support from AI tools a useful complement to all we do as humans.