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Organisations generate vast amounts of information, which has resulted in along-term research effort into knowledge access systems for enterprisesettings. Recent developments in artificial intelligence, in relation to largelanguage models, are poised to have significant impact on knowledge access.This has the potential to shape the workplace and knowledge in new andunanticipated ways. Many risks can arise from the deployment of these types ofAI systems, due to interactions between the technical system and organisationalpower dynamics.  This paper presents the Consequence-Mechanism-Risk framework to identifyrisks to workers from AI-mediated enterprise knowledge access systems. We havedrawn on wide-ranging literature detailing risks to workers, and categorisedrisks as being to worker value, power, and wellbeing. The contribution of ourframework is to additionally consider (i) the consequences of these systemsthat are of moral import: commodification, appropriation, concentration ofpower, and marginalisation, and (ii) the mechanisms, which represent how theseconsequences may take effect in the system. The mechanisms are a means ofcontextualising risk within specific system processes, which is critical formitigation. This framework is aimed at helping practitioners involved in thedesign and deployment of AI-mediated knowledge access systems to consider therisks introduced to workers, identify the precise system mechanisms thatintroduce those risks and begin to approach mitigation. Future work could applythis framework to other technological systems to promote the protection ofworkers and other groups.

A Framework for Exploring the Consequences of AI-Mediated Enterprise Knowledge Access and Identifying Risks to Workers