Challenge: Manually reading and categorizing customer feedback is an impossible task at scale. As a result, valuable insights into customer preferences and product flaws remain buried in unstructured text.

Solution: An LLM processes all incoming reviews for a new product. It automatically summarises the feedback, identifying that 20% of negative reviews mention "poor battery life," and presents this insight to the product development team in a real-time dashboard.

Challenge: Supply chain management involves tracking vast amounts of documentation from dozens or hundreds of suppliers. Manually monitoring for risks, such as a supplier consistently missing delivery dates, is difficult and reactive.

Solution: An LLM copilot scans all incoming supplier emails and shipping documents. It flags that a key component supplier has mentioned "production delays" three times in the last week and alerts the procurement team to a potential stock-out risk.

Challenge: NHS Trusts and other healthcare organizations are overloaded with unstructured data. Clinicians and back-office teams spend valuable time manually reading and extracting key information, which slows down patient handovers and referrals.

Solution: An LLM-powered tool is integrated into the electronic health record (EHR) system. With a single click, it generates a concise summary of a patient's record, highlighting key diagnoses, treatments, and outstanding actions, which can be shared with the next care provider.

Challenge: Government department intranets are often vast and difficult to navigate. Employees waste significant time trying to find specific forms or policy documents, leading to frustration and inefficiency.

Solution: A new employee asks the intranet copilot, "How do I book annual leave and what is my allowance?" The LLM provides a direct answer, links to the correct form on the booking system, and displays the relevant section from the HR policy handbook.