Artificial Intelligence (AI) is rapidly reshaping professions across the globe, and archivists and records managers are no exception. From public archives safeguarding cultural heritage to corporate records centers ensuring regulatory compliance, these fields are on the cusp of significant transformation. The integration of AI – including technologies like natural language processing (NLP), machine learning, and automated metadata generation – promises to streamline routine tasks and unlock new capabilities. Global forecasts suggest that while millions of jobs could be affected by AI-driven automation, even more new roles will emerge; for instance, one report projects 92 million jobs may be displaced but 170 million new ones created by 2030, a net gain of 78 million 1 . Within archives and records management, experts similarly anticipate an evolution of roles rather than wholesale replacement.
This report provides an overview of how AI is expected to impact the career paths of archivists and records managers, focusing on future projections in both public archival institutions and corporate records programs. Key areas examined include AI-driven changes in workflows, emerging skill requirements, potential job displacement or creation effects, new career opportunities (or hybrid roles), and real-world initiatives that illustrate these trends. Throughout, a distinction is drawn between the context of public archives (e.g. national or cultural heritage institutions) and corporate records management (in business and government organizations) to highlight sectorspecific nuances.
AI Transforming Archival and Records Management Workflows
AI technologies are poised to revolutionize many core tasks in archives and records management. Automation and efficiency gains are a primary benefit, as intelligent systems can process vast volumes of information far faster than humans. For example, AI systems can “automatically classify thousands of documents within minutes while maintaining high accuracy rates,” a task that would have once consumed countless staff hours 2 . Machine learning models trained on organizational records are increasingly able to categorize, tag, and sort information with minimal human intervention, greatly reducing the need for manual filing and data entry
3 . In both public and corporate contexts, this means mundane, repetitive chores – like labeling incoming documents or routing emails – can be handled by AI, freeing up professionals to focus on higher-level duties. Indeed, records management experts note that AI is taking over “the mind-numbing tasks that make us question our career choices” (such as slogging through thousands of old emails or poorly named files) 4 .
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