# AI and the Archivist: Assistant, Not Replacement _Published: 7 August 2026_ You know the feeling. A collection arrives, or has been sitting waiting for attention for longer than anyone would like to admit. The material is significant. Some of it is fragile. Some of it is extraordinary. And the task of cataloguing it properly, describing each item accurately, applying consistent metadata, creating records that will make the collection genuinely discoverable and usable, is enormous. You also know what usually happens next. Other priorities intervene. Funding is limited. Time is short. The collection waits. This is not a failure of professionalism or commitment. It is the reality of working in a sector that holds some of the most important material in existence, with a fraction of the resources needed to do it justice. The cataloguing backlog is not a new problem. But it is getting harder to ignore. AI is increasingly being discussed as part of the answer. And if your reaction to that is cautious, sceptical or somewhere between curious and concerned, that is entirely reasonable. The claims being made about AI are often sweeping, the technology is moving fast, and the stakes for archive and heritage collections are high. Getting it wrong matters. So rather than telling you not to worry, this article tries to be straight with you about what AI can and cannot do, where it genuinely helps and where professional judgement remains not just valuable but essential. ### What our AI is actually good at The tasks that our AI handles well in an archive context are, broadly speaking, the ones that are repetitive, high-volume and time-consuming: the work that often needs doing before the more complex intellectual work can begin. This includes reading digitised documents and extracting structured information from them, generating descriptive titles based on the content of an item, identifying names, dates, places and organisations, applying consistent tags across a collection, and producing a first pass of catalogue data. These are not trivial tasks. At scale, across a collection of thousands or tens of thousands of items, they represent an enormous amount of work. When done manually, this can delay a project by months or even years, or prevent it from happening at all. Our AI can move through that work quickly and consistently. Not perfectly, but consistently. And consistency across a large collection has real value. The aim is to give archivists, cataloguers, curators and collection holders something meaningful to work with, rather than starting from a blank page. ### What AI cannot do Our AI cannot replace people. Our AI is designed to support people, not replace them. The final understanding of an archive still belongs with people. It can help read and contextualise documents, identify useful information, recognise relationships and create a structured first pass across a collection. But it does not replace the knowledge, care and judgement of archivists, cataloguers, curators or collection holders. Archives are not just data, understanding their significance often requires human context: knowledge of a collection’s history, its provenance, its sensitivities and the people or communities it represents. Our AI can support that work, but it should not make final decisions about significance, sensitivity, access, preservation or publication. Those decisions need human oversight, particularly when working with fragile, complex or sensitive material. Questions around personal data, ethical considerations, cultural context, provenance and what should or should not be made accessible all require careful judgement. The aim is not to hand control to AI. It is to give people a stronger starting point, reduce repetitive manual work and keep human expertise at the heart of the archive. ### On the question of accuracy Accuracy is one of the most common and most legitimate concerns archivists raise about AI. If the catalogue data is wrong, the collection becomes harder to use, not easier. Errors can propagate. Trust is difficult to rebuild. It is worth explaining how responsible AI systems approach this. Rather than generating information from general knowledge or making educated guesses, well-designed archive AI works by extracting information directly from the source document. Every piece of data it produces can be traced back to the exact page and location it came from. That traceability is not just a technical feature. It is what makes human review meaningful, because it allows an archivist to check not just what the AI has produced, but where it came from and whether the extraction was accurate. The aim is not to produce a finished catalogue. It is to produce a structured, traceable first pass that a professional can review, correct and approve. The archivist remains in control of what goes into the final record.  ### On the question of security The other concern we hear most often is about security. What happens to the collection data? Who can access it? Is sensitive or confidential material at risk? These are the right questions to ask of any technology supplier, and they deserve a straight answer. Archive AI should operate in a secure, isolated environment. Your collection data should not be shared, should not be used to train general AI models and should not be accessible to anyone outside your organisation. The system should work exclusively with the material you provide, and nothing else. If a supplier cannot give you clear, specific answers to these questions, that is important information. The security of collections, particularly those containing personal, sensitive or legally significant material, is not a detail to be glossed over. ### What this means in practice The honest version of what AI offers an archivist is this: a way to make a start on work that might otherwise not happen at all. A collection that has sat uncatalogued for years because there has never been enough time or resource to tackle it properly. A backlog that has grown to the point where it feels unmanageable. A digitisation project that produced thousands of images but no structured data to make them searchable or usable. AI can produce a first pass of catalogue data for that collection, consistently and at scale, in a fraction of the time manual cataloguing would take. That first pass will need review. Some of it will need correction. But it gives a professional something to work with, and it means the collection can begin to move from stored to described, from inaccessible to discoverable. The archivist's role in that process is not diminished. It is focused. Instead of spending time on the mechanical work of creating records from scratch, professional expertise can be directed at the work that actually requires it: reviewing, refining, contextualising, making judgements that no AI system can make. ### A note on the wider conversation The debate about AI in the archive and heritage sector is still relatively young, and it is not always a comfortable one. There are legitimate questions about the role of technology in a profession built on careful, considered human judgement. There are reasonable concerns about what is lost when speed is prioritised over depth. And there are broader questions about who controls the technology, whose data it is trained on and what the long-term implications might be. These are worth having. They are also worth separating from the more immediate and practical question of whether AI-assisted cataloguing, used carefully and with proper human oversight, can help address a problem that is very real and very pressing. The cataloguing backlog is not going to solve itself. Collections are at risk. Material is deteriorating. Knowledge is being lost. The resources needed to address all of this through traditional means alone are not available to most organisations. AI is not a perfect solution. But used responsibly, with transparency about what it can and cannot do and with archivists in control of the process and the outputs, it can be a genuinely useful tool. ### We are still learning too One more thing worth saying: the application of AI to archive and heritage collections is still developing. The technology is improving, the approaches are being refined and the conversations between technologists and heritage professionals are still finding their shape. We do not have all the answers. What we do have is a genuine commitment to working with the sector rather than at it, to being transparent about how our systems work, and to building tools that archivists can trust and use with confidence. If you have questions, concerns or simply want to understand more about how AI-assisted cataloguing works in practice, we would welcome the conversation.   _Find out more about Archive Intelligence and how we work with archive and heritage collections, or __[get in touch](https://microform.digital/contact)__ to discuss your collection._ --- [Read the full article](https://microform.digital/resource-centre/ai-and-the-archivist-assistant-not-replacement) --- **Request a quote:** https://microform.digital/contact **Phone:** +44 (0)330 053 6300 **Email:** info@microform.digital