Exploring the potential benefits and challenges of artificial intelligence for research funding organisations: a scoping review
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Background
Artificial Intelligence (AI) is at the forefront of today’s technological revolution, enhancing efficiency in many organisations and sectors. However, in some research environments, its adoption is tempered by the risks AI poses to data protection, ethics, and research integrity. For research funding organisations (RFOs), although there is interest in the application of AI to boost productivity, there is also uncertainty around AI’s utility and its safe integration into organisational systems and processes. The scoping review explored: ‘What does the evidence say about the current and emerging use of AI?’; ‘What are the potential benefits of AI for RFOs?’ and ‘What are the considerations and risks of AI for RFOs?’
Methods
A scoping review was undertaken with no study, language, or field limits. Due to the rapidly evolving AI field, searches were limited to the last three years (2022-2024). Four databases were searched for academic and grey literature in February 2024 (including 13 funding and professional research organisation websites). A classification framework captured the utility and potential, and considerations and risks of AI for RFOs.
Results
122 eligible articles revealed that current and emerging AI solutions could potentially benefit RFOs by enhancing data processes, administration, research insights, operational management, and strategic decision-making. These solutions ranged from AI algorithms to data management platforms, frameworks, guidelines, and business models. However, several considerations and risks need to be addressed before RFOs can successfully integrate AI (e.g., improving data quality, regulating ethical use, data science training).
Conclusion
While RFOs could potentially benefit from a breadth of AI-driven solutions to improve operations, decision-making and data management, there is a need to assess organisational ‘AI readiness’. Although technological advances could be the solution there is a need to address AI accountability, governance and ethics, address societal impact, and the risks to the research funding landscape.
