The Research Group on Artificial Intelligence and Public Administration brings together scholars examining how AI reshapes the exercise of public authority, the work of public organisations and the relationship between government and society. Its central question is: how should public administrations understand, govern and exercise responsibility for AI, and how might AI challenge the theories, values and practices through which we understand public administration itself?

Our ambition is to develop a sustained, internationally connected research community that moves beyond both technological optimism and accounts centred exclusively on risk. We welcome research on the opportunities, limitations and consequences of AI, including decisions not to adopt it. Rather than treating adoption as an inevitable or inherently desirable outcome, the group asks under what conditions particular uses of AI are justified, whose interests they serve, and how their effects should be assessed. A critical approach to AI, including values-based critiques as well as broader philosophical understandings of the implications of AI for the management of public services and public administration at large, is central to the approach of the group.

The Research Group’s distinctive contribution is to place AI at the centre of inquiry into administrative judgement, institutional authority and public responsibility. Complementing broader research on digital government and technological innovation, we focus on the implications of delegating, sharing or contesting public tasks and decisions involving AI. We connect the governance of AI within public organisations with the strategic orientation and capabilities those organisations require to govern AI across society.

Topics of interest include, but are not limited to:

• Administrative judgement and discretion: how AI changes professional expertise, evidence use, decision-making and the roles of frontline staff, managers and policy advisers; including human–AI collaboration, oversight and the division of responsibility between people and AI systems.

• AI adoption, implementation and non-adoption: individual, organisational and institutional determinants of adoption, resistance, adaptation and sustained use, including leadership, readiness and administrative context.

• Accountability and democratic control: responsibility for AI-supported decisions; transparency, explanation and contestability; and the roles of political representatives, courts and oversight bodies.

• Public values and unequal consequences: fairness, rights, inclusion, accessibility, citizen experiences, trust and legitimacy and the distribution of benefits, burdens and administrative power.

• Public sector performance and public value: effects of AI on efficiency, productivity, service quality, effectiveness, fiscal sustainability and public value creation, including unintended consequences and competing performance objectives.

• Organisational capacity and public work: leadership, skills, professional identities, employment relations and the ability to scrutinise, challenge and maintain AI systems; organisational readiness and the changing nature of public employment.

• Public integrity and responsible AI: the use of AI to detect irregularities and prevent corruption, alongside risks of misuse, manipulation, opacity and the erosion of institutional integrity.

• Public–private relationships and dependency: procurement, contracting, access to data and models, and the implications of reliance on external providers for public authority and institutional autonomy.

• Policy, implementation and regulation: how AI policies and safeguards are interpreted and enacted across administrative systems, policy sectors and levels of government – including at the supranational (European and other regions of the world) and international level

• Knowledge and research practice: how AI challenges public administration concepts, research methods and research ethics, including its use in scholarship and teaching.

We welcome theoretical, empirical, methodological and normative contributions that move beyond documenting AI adoption to examine its underlying determinants, actual effects and broader institutional consequences. Contributions may draw on qualitative, quantitative, experimental, comparative, historical and participatory approaches, addressing established AI applications, generative AI and emerging forms of autonomous systems, while critically examining the claims made about them. Comparative and longitudinal research across administrative traditions, countries, policy sectors and levels of government is particularly encouraged, especially where it helps distinguish developments specific to AI from longstanding challenges in public administration. All contributions - including theoretical-speculative - which address the potential and actual impact of AI on the ways in which we theorise public administration and interpret its values and practices are most welcome. The group aims to provide a supportive intellectual home for established researchers, early-career scholars and doctoral students, including colleagues entering this field from other areas of public administration. Technical expertise is welcome but is not a prerequisite for participation. We particularly encourage contributions from underrepresented institutions, regions and scholarly traditions, and constructive exchange across disciplinary boundaries.

Through conference panels, developmental workshops and opportunities for collaborative publications and research proposals, we aim to build a shared but plural research agenda. Our purpose is not to establish a single position on AI, but to advance rigorous, independent scholarship capable of informing its democratic, responsible and publicly valuable governance.

For the upcoming ENPA conference to be held in Madrid from 1-3 September 2027, the Research Group requests abstracts drawing on current research related to these topics.

During this conference, the Research Group will provide a podium for broad discussion around selected empirical and/or theoretical papers that focus on one or more of the topics this Research Group is built upon (cf. supra). We are welcoming abstracts (no longer than 500 words) that:

• Have a succinct and relevant title; include author affiliations and contact details;

• Cover the main line of argument to be explored in the full paper;

• Show evidence of innovative and creative thinking which is well grounded in theory or otherwise is well argued;

• Indicate whether the proposed paper is theoretical, empirical  and/or normative in orientation.

• Clearly identify the research problem, research question(s) and contribution to public administration scholarship;

• Briefly specify the research design, methods and data sources, where applicable;

• Summarise available findings or expected contributions, distinguishing preliminary results from proposed research.

• Submission deadline, submission portal, notification date and full-paper requirements: to be confirmed in the official conference announcement.

Please note that we are keen to encourage new and existing scholars in the field to contribute to the Research Group. And do not hesitate to contact us with any questions regarding the conference and/or the Research Group.