Microsoft Copilot
The School has Microsoft Copilot enabled for all staff and students and it's the recommended generative AI tool for all LSE members because of its in-built security and data privacy, meaning that none of your inputs are ever stored and thus make it GDPR and Copyright friendly. The way to use it is via the Edge browser and logged in with your LSE email, which will show a label saying ‘protected’ to confirm you’re using the secure work-appropriate interface.
Note: Microsoft Copilot is not to be confused with Copilot for Microsoft 365, which is a much more capable paid service ($30 per user per month, not yet available to educational licenses) that allows secure integration of GPT4 technology directly into M365 apps (Outlook, Word, Excel, PowerPoint, SharePoint, OneNote, Teams) to enhance personal productivity. The tool can see all and only the data the individual user can see within the M365 ecosystem (e.g. your Outlook messages and SharePoint / OneDrive files), and includes advanced functionality like summarising inboxes, meetings, Excel analysis, PowerPoint slide generation and editing etc. all securely grounded in the user’s data. While this is targeted towards everyday work productivity, it could of course be very valuable for research related work particular with the security benefits. The same caveats for all generative AI tasks remain when it comes to needing accurate information retrieval from provided data sources: unless the task is very explicitly targeted, the LLM struggles handling finding accurate information when the scale of text it has to search is large.
Chat GPT and Chat GPT Team and Enterprise Plans
Given that Open AI save user data to train their future models for users on basic free plans by default, for anything work related (or that you wouldn't want to share) where MS Copilot isn’t viable, it’s worth considering adopting the Chat GPT Team, similar to their ‘Enterprise’ offering with enhanced security and privacy, but requiring only 2+ users for any team. The Team plan includes all features of Chat GPT Plus including the latest advanced reasoning models (o1 and o3-mini) - but not the 'Pro' features including Deep Research and Operator which costs $200 per user per month. All data in the Team Plan can be deleted entirely after 30 days and the data is moreover not used to train their models. However, because Open AI still stores the data for 30 days in the US, no personally identifiable information should ever be shared without having had a Data Protection Impact Assessment (DPIA) approved first. The Team plan monthly per user cost is $30 (compared to $20 for Chat GPT Plus) or $25 per user per month if purchased on an annual subscription. The additional cost reflects the enhanced security, privacy and usage limits.
LSE DTS has permitted purchase of the Chat GPT Team Plan for academic units since 2024 where the usage will never entail personal data. The following is the guidance DTS provide before purchasing:
“Each AI provider has its own terms of service, security model, and end user agreements. It’s important to read through these so you understand what any AI service will do with your data, where your data will be stored, and if it can potentially be reused or regurgitated by other users of the service. You need to read these terms of service carefully before proceeding to use an AI service – if you need further help, please talk to the cyber security team via dts.cyber.security.and.risk@lse.ac.uk
In particular, please be aware:
It is highly inadvisable to prompt an AI service with any confidential or personal information.
It is unwise to trust the results as correct, without performing separate verification.
AI is prone to ‘hallucinations’ and may make up data it does not have, or otherwise refer to information inconsistently or incorrectly.
Data may be stored in the US or jurisdictions that do not meet the required standards of UK GDPR, so if any research data is input into it check that doing so wouldn't breach any research data agreement.
Remember that with most AI services there aren't any guarantees of service. ”
The Chat GPT Enterprise Plan has maximum privacy and security along with additional organisational analytics though comes at a significantly higher cost.
Claude
In 2025 Anthropic made waves among LLM 'coinnosseurs' for releasing Claude Sonnet 3.5 , a model many preferred to Chat GPT in key areas: higher quality writing style, understanding long texts (especially academic content - unlike Chat GPT which uses Retrieval Augmented Generation for PDFs, Claude extracts the text and images directly into the prompt context, which allows far better quality understanding), spatial and visual reasoning and especially coding. It has been the no.1 choice for most software developers since Summer 2024 and played a constitutive role in making Cursor AI (integrating LLMs into a a coding environment) the fastest growing Software as a Service of all time. For a while it also had an edge due to its 'Artifacts' feature, enabling live interactive web interfaces in the chat itself. However in 2025 Chat GPT introduced live collaborative editing, code execution and web interfaces with the 'Canvas' feature, including using the advanced o1 reasoner model. While Open AI's o3 series scores better in general coding (see rankings below), Sonnet in early 2025 is still the leader in front-end visual code generation. Claude by default does not store user chat data for model training, user have to 'opt in' to do so; however Anthropic has a clause which retains the right to log any chats flagged for safety concerns. Claude's notable deficits include strict usage limits and a much higher 'refusal rate' to user requests on (occasionally dubious) ethical grounds than Chat GPT.
Gemini
Google's Gemini models and associated applications have been slowly and steadily becoming more competitive after a sluggish start in 2023. Their NotebookLM platform (especially the AI podcast generation tool) went viral in late 2024, followed by reasoner (Google calls them 'thinking') models similar to Open AI's o series which as of 2025 are still some way off the top but are much cheaper to use. Google released Deep Research in 2024 which enables fast and broad online source searching and was best in class until Open AI released their own 'Deep Research' using o3 in 2025 which is more thorough and capable in how it analyses and synthesises the sources it can access. Google also makes some experimental features available for free in Google's AI Studio, including the streaming realtime tool where a user can chat to a voice LLM while sharing the screen.
Model Rankings
Below is the latest leaderboard from LiveBench from February 2025, a private (and therefore uncontaminated, meaning models won't have been trained on the questions) benchmark with challenging questions across various categories.
AI tools dedicated to literature-related research
There have been some long standing literature mapping tools (like Research Rabbit (free), SciSpace (free + paid), Semantic Scholar (free) and Connected Papers (free + paid)) that don’t use LLMs (but use limited semantic NLP) to enhance searches but are nonetheless very useful for building up literature collections.
The most advanced literature review platform that has generative AI integrated as a core feature with a 'made by researchers for researchers' objective is Undermind, with Elicit and Scite AI being strong contenders (see the Literature Review page for more info).