Blog: SDG Mapping in Practice: Insights from the PRME Chapter UK and Ireland Community

The following blog provides an overview of the insights from the PRME Chapter UK & Ireland webinar on SDG Mapping in Practice: Audits, Reporting Frameworks, and AI Tools held in May 2026

The Chapter wishes to extend its gratitude to the four presenters for sharing their expertise: Andrew Hunt (Plymouth Business School), Alan Hanna (Queen’s Business School), Constantine Manolchev (Exeter Business School), and Scarlett Whitthread (Exeter Business School). The webinar was facilitated by Laura Steele (Queen’s Business School and Vice-Chair, PRME Chapter UK & Ireland).

Context

The challenge of embedding sustainability within business and management education is no longer confined to establishing whether the UN Sustainable Development Goals (SDGs) are present within a curriculum. Increasingly, the more substantive question is whether institutions can demonstrate how ethics, responsibility, and sustainability are embedded, experienced, assessed, and enhanced over time. The PRME Chapter UK & Ireland webinar, “SDG Mapping in Practice: Audits, Reporting Frameworks, and AI Tools”, presented three complementary perspectives on this agenda: student-led curriculum auditing, the embedding of sustainability-related criteria within existing documentation and governance processes, and AI-enabled SDG mapping.

Collectively, the presentations indicate an important shift in how business schools might approach sustainability-related curriculum work. SDG mapping should not be understood as a static compliance exercise. Rather, it can be conceptualised as a form of curriculum intelligence: a structured, repeatable, and evidence-informed process through which institutions can assess their current position, identify developmental priorities, support staff engagement, strengthen accreditation narratives, and enhance the student learning experience.

Moving beyond simple SDG alignment

Andrew Hunt (Plymouth Business School) began the webinar by positioning SDG mapping as part of a wider institutional effort to embed PRME systematically, align curricula with the SDGs, establish a continuous improvement cycle, support career-ready graduates, and improve staff engagement. The project’s intended outcomes included baseline measurement, authentic results, staff awareness workshops, and a more future-oriented curriculum. Importantly, the presentation argued that SDG mapping should extend beyond the SDGs alone through a “triple framework” approach. This brings together the language of the 17 UN SDGs and PRME, a set of Responsible Management Education (RME) criteria, and Education for Sustainable Development (ESD) delivery methods.

The SDGs provide a globally recognised framework for sustainability yet, Andrew argued, they do not always translate directly into the discipline-specific or pedagogic language used by academics, professional bodies, and accreditors. Plymouth’s RME criteria, including ethical leadership, sustainable development, social impact, stakeholder engagement, global perspective, corporate governance, and innovation and creativity, offer a more education-facing vocabulary for responsible management. They shift attention from whether a module refers to an SDG towards whether it develops the capabilities, dispositions, and forms of judgement associated with responsible leadership.

The ESD delivery methods add a further pedagogic dimension. Problem-based learning, experiential project work, simulations, and case studies are not simply techniques for teaching sustainability. They are framed as methods through which students can engage with complexity, ambiguity, and real-world decision-making. This reinforces a central insight from the webinar: curriculum mapping is not only concerned with content coverage, but also with how students encounter, practise and demonstrate responsible management learning.

The value of student-led auditing

One of the key methodological insights from the Plymouth case study presented by Andrew was the use of student-led auditing. The project partnered with SOS-UK, with students trained to review student-facing materials such as module guides and learning outcomes. The method deliberately prioritised student perceptions rather than relying solely on academic self-reporting. At least two auditors were used per module to strengthen robustness and reduce the risk of individual bias.

Andrew argued that this is important because curriculum claims can vary considerably depending on the perspective from which they are assessed. A programme team may consider sustainability to be embedded because it is implicit in teaching discussions, assessment examples, or staff assumptions. However, where students cannot identify or recognise that learning, the educational signal may be weak. Student-led mapping therefore provides a valuable authenticity test: it examines not only what staff intend to teach, but also what students are likely to experience.

The presentation also emphasised the importance of action-oriented reflection through follow-up staff workshops. Audit data becomes educationally meaningful only when it is translated into curriculum enhancement. Mapping may reveal that programme leaders have limited tacit knowledge of their starting position, but its principal value lies in creating the conditions for informed academic conversations about content, pedagogy, assessment, and graduate capabilities.

Accreditation, reporting and institutional reuse

Alan Hanna’s presentation on SDG reporting for business school accreditations added a second dimension: how mapping can become part of institutional reporting infrastructure. The Queen’s Business School journey connected SDG reporting to PRME Sharing Information on Progress (SIP) reporting, EQUIS Chapter 9 (Ethics, Responsibility, and Sustainability), AACSB Standards 8 (Impact of Scholarship) and 9 (Societal Impact and Engagement), and AMBA’s interest in sustainable development.

The model presented was developmental: from audit and gap analysis to ad hoc data requests, systematisation and embedding, routine data capture, digitisation and automation, and finally reporting and reuse. This sequence is instructive because it illustrates how schools may move from reactive reporting towards embedded information systems.

In teaching, the approach included SDG coverage by module, descriptive evidence embedded within existing processes, a “professionally responsible” Assurance of Learning (AoL) competency, links to programme and module learning outcomes, and a “traffic-light” system indicating the degree of coverage. In research, the school uses Pure as the institutional research information management system, with SDG tagging, automated checks against SDG keyword lists, and finally manual validation.

This framing is valuable because it treats SDG reporting as more than the production of accreditation narratives. If designed effectively, the same data can support accreditation, internal quality assurance, curriculum planning, staff reflection, research visibility, and strategic decision-making.

AI as a mechanism for scale, not a substitute for academic judgement

Finally, Scarlett Whitthread and Constantine Manolchev of Exeter University Business School introduced a contrasting but complementary approach: the use of AI automation to map curricula at scale. Their workflow used n8n to process module descriptions, content, learning outcomes, and reading resources. The presentation reported that 544 modules were mapped in approximately 60 minutes by one person, with staff validation ongoing across 60 modules, or around 12% of the total.

The value proposition presented by Constantine and Scarlett is clear. Manual mapping at institutional scale is resource-intensive, time-consuming, and vulnerable to inconsistent interpretation. AI-enabled mapping can generate structured outputs rapidly, including module-by-module SDG alignment, primary and secondary SDG linkages, rationales, gap analysis and spreadsheet-ready data for reporting and planning.

However, the presentation was careful to position AI within a human-in-the-loop model. The key methodological point was not simply that AI can classify modules. Rather, prompts must be designed to constrain outputs against a predefined assessment standard. In the presenters’ terms, prompting is a form of “output shaping”: rather than asking the AI to reason in an open-ended way, the process defines what constitutes an acceptable form of reasoning. The resulting AI output is therefore transparent, auditable and available for expert validation.

This is particularly important for academic governance. AI-generated curriculum mapping should not be treated as authoritative without appropriate validation, Constantine and Scarlett argue. The presentation identified several next steps, including human validation, testing inter-coder reliability, comparing divergence between large language models and transformer models such as BERT and RoBERTa, and comparing SDG alignment with graduate skills and capabilities.

The broader insight is that AI is most useful when it changes the allocation of academic labour. It can reduce the time spent on repetitive coding and create more capacity for strategic interpretation, quality assurance and curriculum design.

Key lessons for business schools

The three presentations converge around several important insights:

• First, SDG mapping requires multiple “languages”. The SDGs are essential, but they should be connected to RME, pedagogy, employability, and graduate capability frameworks. A purely SDG-based map may demonstrate coverage, but it may not demonstrate educational depth.

• Second, authenticity is critical. Student-led auditing offers a method for capturing how sustainability is experienced by learners, rather than relying exclusively on how it is described by staff. This can reduce self-reporting bias and generate more credible evidence for enhancement.

• Third, AI can support scale and consistency, but only where transparent standards, carefully designed prompts and human validation are in place. The most persuasive AI-enabled model is not black-box automation, but auditable curriculum analysis with expert oversight.

• Fourth, accreditation should be treated as a strategic driver rather than an isolated reporting burden. When SDG data is embedded into existing teaching, research, and quality systems, it can support continuous improvement rather than episodic compliance.

• Finally, successful implementation depends on culture as much as technique. As outlined in the webinar, effective communication, clarity about what counts, minimising perceptions of additional administration, securing technical support, and recognising that sustainability impact extends beyond programmes and research alone are vital.

Conclusion: From mapping to meaningful change

The webinar’s central contribution was to reframe SDG mapping as a dynamic practice of institutional learning. Undertaken superficially, mapping risks becoming a “tick box” exercise in which modules are tagged, dashboards are produced and accreditation narratives are assembled. Undertaken rigorously, however, SDG mapping can generate meaningful evidence about what students learn, how staff teach, where curricula are strong, where gaps remain, and how business schools can better prepare graduates for responsible professional practice.

The most promising direction is, arguably, integrative. Business schools could combine student-led authenticity, embedded reporting systems, AI-enabled scale, and robust human validation. This combination can move SDG mapping beyond symbolic alignment and towards a more mature form of RME in line with the Principles of PRME.

For any questions related to this event, please contact Laura Steele (laura.steele@qub.ac.uk), Vice-Chair, PRME Chapter UK & Ireland.