BPP University needed to rapidly expand its bank of multiple-choice questions for the UK Solicitors Qualifying Examination (SQE).
Crafting each legally compliant question took up to an hour per question because wrong-answer "distractors" must be plausible and precise. With growing student demand for more practice questions, the law school lacked the capacity to scale production through manual effort alone, creating a significant bottleneck in exam-content creation and straining faculty time and budget.
GenFutures Lab deployed a pair-prompting sprint methodology pairing AI engineers with BPP legal SMEs to fine-tune OpenAI LLMs on a structured legal knowledge base, producing SQE-compliant multiple-choice questions with accurate distractors at scale, shifting SMEs from question drafting to review and approval.
Time to produce each exam question dropped from 1 hour to 15 minutes, freeing SME capacity for higher-value review and editorial work rather than question drafting from scratch.
SMEs went from reviewing 10 questions per day to 40. Monthly output reached 500 high-quality MCQs (1,000 produced within the first two months), meeting student demand that was previously unachievable given resource constraints.
The efficiency gains translated to £10,000 per month in cost savings just four months into the engagement, delivering a clear, quantifiable ROI and demonstrating the financial case for AI-assisted content workflows in professional education.
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