28th Annual International Conference 
on Digital Government Research

AI Transformation and Government Innovation:

Advancing Theoretical Foundations and Empirical Evidence 

DG.O 2026
Seoul National University of Science and Technology (SeoulTech)
Seoul, The Republic of Korea 
June 28 - July 01, 2027

CALL FOR PAPERS / PROPOSALS

seoultechCurrent

The Digital Government Society (DGS) announces the 28th Annual International Conference on Digital Government Research (dg.o 2027), under the theme “AI Transformation and Government Innovation: Advancing Theoretical Foundations and Empirical Evidence.” The dg.o 2027 will be hosted by Seoul National University of Science and Technology (SeoulTech) in Seoul, Republic of Korea, from June 28 to July 1, 2027. The dg.o conference series is an established forum for the presentation, discussion, and demonstration of interdisciplinary research on digital government, civic engagement, artificial intelligence, technology innovation, and related applications and practices. Each year, the conference brings together scholars and practitioners whose work advances both theory and practice and addresses timely and consequential issues in digital government.

THEME & TOPICS The dg.o 2027 theme articulates the movement now under way in governments worldwide, from digital transformation (DX) to AI transformation (AX). Building on decades of digital government innovation, public organizations are no longer piloting artificial intelligence at the edges of their operations; they are beginning to embed it in core administrative processes including decision support, service delivery, regulation, inspection, and policy analysis. This is not simply a technological upgrade. It changes how public authority is exercised, how administrative discretion and responsibility are distributed between; human officials and AI, and how citizens interact with the state. 

 

At the same time, AI transformation represents one important dimension of the broader digital government landscape. While AI transformation is a central focus of dg.o 2027, the conference welcomes research across the full breadth of the digital government domain, including work on interoperability, digital inclusion, digital public infrastructure and services, cybersecurity, and organizational transformation that does not directly involve AI.
Advancing theoretical foundations. Much of what the field knows about digital government was built for an era of digitization, platform-based service delivery, and data sharing. AI in the public sector raises questions those frameworks were not designed to answer: what accountability means when a decision is produced by an AI whose reasoning is not fully legible; what administrative discretion becomes when it is shared with or mediated by AI; what legitimacy rests on when the outputs of the state are AI-generated. The dg.o 2027 invites scholarly research that extends, adapts, or productively challenges existing theory, and research that builds new conceptual apparatus for AI-era government.
Advancing empirical evidence. Claims about artificial intelligence in government have expanded more rapidly than the evidence supporting them, creating an urgent need for stronger empirical research. We particularly welcome rigorous empirical contributions (including case studies, comparative research, field and survey experiments, administrative data analysis, computational and text-analytic methods, ethnographic work, and mixed-methods research) that document what is actually happening as AI is adopted in public organizations and examine its effects on efficiency, equity, service quality, the public workforce, and public trust. Negative results and well-documented failures are as valuable to this community as success stories.
Public values remain the guide and the purpose. As AI becomes increasingly embedded in government, technological transformation must ultimately be evaluated against the public values that government is expected to uphold. Effectiveness, equity, transparency, accountability, efficiency, responsiveness and fairness do not become less important as systems become more capable; they become harder to secure and more consequential when they fail. Understanding how public values are created, embedded, displaced, or eroded by AI is therefore central to this conference.

Four key threads

  • Algorithmic accountability: transparency, auditability, contestability, and redress when public decisions are shaped by algorithmic systems; oversight institutions, procurement, and standards. 

  • Human–AI collaboration: how public servants, professionals, and AI systems divide work, build or lose trust, and reshape administrative capacity, skills, and discretion.
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  • Democratic legitimacy: institutional and constitutional questions raised by AI in government, including authority, oversight, representation, information integrity, and public trust.

  • Citizen engagement: AI-mediated participation and service co-production; accessibility, digital inclusion, and equity; and the changing relationship between citizens and the state.

Building on dg.o 2026 in Omaha, which explored collaborative digital transformation for public value creation, dg.o 2027 deepens that dialogue, from collaborative digital transformation to AI transformation. As the conference comes to Asia, we particularly welcome submissions that bring comparative, international, and regional perspectives to these questions. Please note that all conference sessions are conducted in English.

 

SUBMISSION TYPES AND FORMATS:

Research papers – double blind review: Papers on any topic and using any method, provided that their relevance to digital government problems, goals, or policies is explicit. Approximately 8,000 words, excluding references.

Management or policy papers – double blind review: Management or policy papers (double-blind review): Papers evaluating practical projects, policy

themes, or management approaches. Approximately 5,000 words, excluding references.

Panels: Proposals describing the theme, goals and issues of the panel, its value to attendees, and why the topic suits a panel format, with contact, moderator and panelist details (name, affiliation,

address, email and phone). Approximately 2,500 words.

Posters: Summaries of research, policy or projects, explaining their interest to attendees. Approximately 2,500 words, following the proceedings template. System demonstrations: Descriptions of a system under development or in use, and why it is of interest to attendees. Approximately 2,500 words.

Workshops/Tutorials: Interactive sessions on any digital government topic, in which the proponents select participants and run the activities. Approximately 2,500 words.

Pre-conference Doctoral Colloquium: A full-day forum for PhD students, ideally with one to two years of study and a structured dissertation proposal, before the dissertation defense. Applications of approximately ten pages, excluding references, tables and figures. Colloquium materials are not published in the proceedings; students are encouraged to submit finished research to a paper track,or ongoing work as a poster or system demonstration.

SUBMISSION TRACKS:

The Data-Driven Services in Government track aims to explore how public sectors can leverage Information and Communication Technologies (ICTs) and various data sources - such as open data, big data, and AI-Ready data - to enhance public services and policy-making. We invite researchers and practitioners to submit papers that examine the dynamic interactions among data application, data governance, and data policy. This track is particularly interested in how the application of AI and data analytics can create innovative public services including transportation, societal resilience, social welfare, and other crucial policy areas. By utilizing data and advanced technologies, governments can transform public services, leading to more responsive and effective governance. Possible topics include, but are not limited to: AI and Data-Driven Service Innovation in the public sector. AI-enabled decision support in government: translating data into usable evidence for public decisions while ensuring human oversight, accountability, and public value. Data Principles and Governance Frameworks, and strategies for Open Data Sharing. Identifying, creating, and assessing the value of government data. The impact of data and AI on diverse policies (e.g., health, social, transportation) across all levels of government. Best practices for public-private sector collaboration on data implementation.

Track Chairs: Hsien-Lee Tseng (National University of Tainan, Taiwan (R.O.C.)), Jason M. Kuo (National Taiwan University, Taiwan (R.O.C.)), Juliano Nunes Alves (Federal University of Santa Maria (UFSM), Brazil) &nbsp &nbsp Keywords: Government data, Evidence-based policy, Data governance, Service innovation, Public value

The track invites contributions not only on practical applications, but also on the theoretical foundations of the interplay between law, technology and innovation. Specific interest areas include the field of privacy (policies, regulations, strategies, recommendations), models of legal and ethical knowledge (especially with respect to core concepts such as ‘norms’, ‘arguments’, ‘rules’, ‘cases’, ‘principles’, ‘values’, ‘procedures’), smart contracts, legal interactions of autonomous agents, digital institutions, technology-driven access-to-justice, legal design and legal visualisation, and both the practice and the foundations (e.g., ethical, legal-theoretical) of the various areas of information law (e.g., data protection law, platform regulation, AI-governance). In particular, the track welcomes contributions focusing on the AI transformation of law and public administration.

Track Chairs: Peter Parycek (Fraunhofer FOKUS, Germany), Diogo Sasdelli (University for Continuing Education Krems, Austria), Christoph Sorge (Saarland University, Germany) Keywords: Legal informatics, AI regulation, Legal automation, Access to justice, Data protection

The adoption and implementation of new ICTs by public organizations have been influenced by organizational factors such as the availability of resources (e.g., funding, infrastructure, technological knowledge, and personnel), leadership, trust, stakeholder involvement, organization’s structure and culture, as well as inter-organizational dynamics. Similarly, the adoption of ICTs in government and society has generated important impacts on the organizational processes, effectiveness, and innovativeness of public organizations, as well as on governance structures and broader society. Artificial intelligence, including generative and agentic AI, is now intensifying these dynamics and reshaping how public organizations work, make decisions and create value. This track solicits research that examines the organizational factors that influence the adoption and implementation, and investigates the impacts, especially the value creation, of new and emerging innovative technologies such as artificial intelligence, generative AI, smart city, data analytics, big data, open data, social media, citizen-centric technologies, and other novel technologies. In line with the dg.o 2027 theme, the track particularly welcomes theory-building contributions and rigorous empirical evidence on AI transformation in public organizations.

Track Chairs: Michael Ahn (UMass Boston, USA), Luis F. Luna-Reyes (University at Albany, USA), Jing Zhang (Clark University, USA), Chris Hinnant (Florida State University, USA)Keywords: Technology adoption, Organisational change, Institutional factors, AI implementation, Public value creation

This research track invites scholarly contributions that critically examine the adoption and implications of Generative Artificial Intelligence (GenAI) and Agentic Artificial Intelligence (agentic AI) within government operations, policymaking cycles, and interactions between the public and the government. Applied agentic artificial intelligence systems (AIS) are largely built on the same foundation models that power generative AIS applications, extending their functions within governance ecosystems from production and synthesis of information to service delivery, planning, invoking tools, and executing tasks with varying degrees of autonomy and delegated authority. Consistent with the dg.o 2027 theme, the track seeks work that extends, adapts, or proactively challenges the frameworks the field inherited from the digitization era, and rigorous empirical research documenting what is actually happening as generative and agentic systems are adopted in public organizations. The track themes are grouped under two pillars: 1) research on the impact and potential positive outcomes of generative and agentic AI for government; and 2) research examining the negative implications and risks. Papers addressing the cross-cutting policy and governance questions of ethical assurance mechanisms, policy alignment, public institutional re-design and governance capacity development are equally welcome. The track places particular emphasis on comparative, international, and regional perspectives.

Track Chairs: Fadi Salem (MBR School of Government, UAE), Theresa A. Pardo (University at Albany, State University of New York, USA), Gianluca C. Misuraca (Politecnico di Milano / Inspiring Futures Europe), Yu-Che Chen (University of Nebraska at Omaha, USA) Keywords: Generative AI, Agentic AI, Government operations, Delegated agency, AI risk and safety

For most citizens, the most frequent contact with the state is a request: a call to a municipal hotline such as 311 in American cities, Seoul’s 120 Dasan Call Center or the 12345 lines in China, a message to a national complaint portal, or a question typed into a government chatbot. Artificial intelligence is now entering every stage of this work, from classifying and routing requests to drafting replies, rating frontline performance and predicting problems before anyone reports them. This track examines what these changes mean for government responsiveness and for the trust citizens place in it. It asks whether AI helps agencies solve problems or mainly helps them close cases, how discretion is divided between operators and automated triage, who is accountable for a machine-drafted reply, and why rising completion rates can sit alongside falling satisfaction. We welcome theoretical, empirical and comparative work from any region and any type of political system. Topics include AI triage and routing, generative AI in citizen communication, predictive and proactive service, analysis of hotline and complaint data, frontline workload, performance metrics and their gaming, digital inclusion, and responsiveness and public trust.

Track Chairs: Rongxin Li (Jinan University, China), Yong Li (Shanghai Maritime University, China) Keywords: Citizen request systems, AI triage, Government responsiveness, Frontline discretion, Public trust

During the last years, we have learned about the risks for governments and political institutions using social media. At the same time, innovation capabilities have emerged, promoting governments and other actors to engage with new audiences and social groups in highly interactive ways. The interrelations of AI and social media are challenging previous conceptions of digital communication. Algorithmic properties of social media platforms are benefiting from AI transformations, impacting affordances such as visibility and interactivity. At the same time, public employees are starting to use AI to enhance institutional communication and improve effectiveness. All these happen in a context of democratic backsliding and of concerns on illiberal and populist practices. We are also open to receiving contributions on other aspects of governments' service delivery and social media, including theoretical and conceptual advancements, methodological and data innovations, or case and practical implications coming from diverse contexts. We will welcome papers on both traditional and emerging issues, including opportunities, risks, citizen engagement, service delivery through social media, social media audiences and citizen behavior, political mobilizations and polarization, social media contents and communicative strategies, disinformation challenges, entertainment platforms for political engagement, or social media for crisis and emergency management, among many other topics.
Track Chairs: J. Ignacio Criado (Universidad Autónoma de Madrid, Spain), Julián Villodre (Universidad Pablo de Olavide, Spain), Vincent Mabillard (Université libre de Bruxelles, Belgium)Keywords: Government social media, AI-mediated communication, Platform governance, Disinformation, Political polarization
Governments at all levels are grappling with workforce and institutional challenges as they pursue digital and AI transformation, including difficulties in recruiting and retaining digital talent. These challenges are exacerbated by traditional bureaucratic structures and cultures resistant to change. This track explores the urgent need to build human and institutional capacity, including digital AI capacity, across all levels of government (i.e. national, sub-national, and local) by examining how emerging workforce and talent management strategies, organizational capabilities, leadership, and governance are shaping government transformation. It invites discussion on the impact of remote and hybrid work arrangements, the integration of generative AI, and the facilitation of innovation on public sector capacity. The track also considers how these changes intersect with broader issues such as equity and inclusion, collaboration, and institutional resilience. Relevant topics include digital and AI capacity development, recruitment and retention of digital talent, remote and hybrid work, AI and workforce management, digital leadership and governance, institutional capacity, collaboration, innovation, and equity considerations for the future public sector workforce.

Track Chairs: Maria Gintova (McMaster University, Canada), Laura Alcaide Muñoz (University of Granada, Spain), Cristina Alcaide Muñoz (University of Granada, Spain) Keywords: Public sector workforce, Digital and AI skills, Talent management, Institutional capacity, Digital leadership

Subnational governments are central to the implementation of public policies and services, yet their capacities to pursue digital transformation vary substantially. Building on previous dg.o tracks on digital transformation in subnational governments, this track examines how states, regions, provinces, and municipalities develop, govern, and evaluate digital and AI-enabled change. It focuses on the institutional arrangements, organizational capabilities, and intergovernmental relationships that shape transformation, particularly where resources, infrastructure, and skills are unevenly distributed. The track welcomes theoretical and empirical contributions examining how digital technologies, including AI, affect service delivery, administrative discretion, public sector work, citizen engagement, and public value. Topics include multilevel governance, shared digital infrastructure, data governance, responsible AI adoption, human–AI collaboration, digital inclusion, and territorial inequalities. Comparative studies, longitudinal research, and evidence from implementation successes, failures, and unintended consequences are particularly encouraged. By connecting subnational experiences with broader debates on government innovation, the track seeks to advance explanatory frameworks and generate actionable knowledge for more effective, equitable, and accountable digital transformation across levels of government.

Track Chairs: Beatriz Barreto Brasileiro Lanza (UNU-EGOV and ILGD, Portugal / Brazil), J. Ramon Gil-Garcia (University at Albany, State University of New York, USA), Thiago José Tavares Ávila (FPL Educacional & ILGD, Brazil) Keywords: Subnational government, Multilevel governance, Digital transformation, AI adoption, Territorial inequalities

This track examines how digital government can enable whole-of-society disaster governance by connecting public agencies, private-sector actors, civil society, communities, and citizens across the disaster cycle. Disasters and complex emergencies increasingly exceed the capacity of any single organization or government, making resilience dependent on coordination across inter-agency, publicprivate, and government-society boundaries. The track invites theoretical, empirical, comparative, and practice-oriented research on how digital platforms, data infrastructures, GovTech, Civic Tech, artificial intelligence, and other emerging technologies reshape these relationships and support mitigation, preparedness, response, and recovery. Particular attention is given to boundary-spanning mechanisms, institutional arrangements, trust, accountability, inclusion, interoperability, and the conditions under which digital technologies strengthen rather than fragment collective capacity. In line with the dg.o 2027 theme, the track also welcomes research on AI-enabled emergency management, human-AI collaboration, and responsible AI adoption in high-stakes public-sector settings. Comparative and international studies are especially encouraged.

Track Chairs: Kaiju Chang (National Chengchi University, Taiwan (R.O.C.)), Grażyna Musiatowicz- Podbiał (Gdańsk University of Technology, Poland), Nina Rizun (Gdańsk University of Technology, Poland), Hsien-Lee Tseng (National University of Tainan, Taiwan (R.O.C.)) Keywords: Disaster governance, Whole-of-society resilience, Boundary spanning, AI in emergency management, Data interoperability


Digital technologies increasingly shape the strategic capacity of governments, yet public administrations remain dependent on technology providers operating in global markets, often beyond their jurisdiction, as well as on digital infrastructures, data ecosystems, platforms, standards, and increasingly AI models and services. Such dependencies can create vulnerabilities and constrain governmental autonomy, while also enabling innovation, efficiency, and access to capabilities that public administrations may not develop independently. This raises a fundamental question: how can governments retain meaningful capacity to make and implement digital choices while remaining embedded in globally interconnected digital ecosystems? This track explores digital sovereignty in the age of AI as a multidimensional governance challenge rather than technological self-sufficiency or isolation. The emergence of generative and agentic AI adds a new layer to this challenge, raising questions of AI sovereignty alongside established concerns about data, technological, infrastructural, and digital sovereignty. These dimensions may reinforce, constrain, or come into tension with one another, creating tensions between autonomy, openness, interoperability, innovation, and international interdependence. The track invites conceptual, empirical, comparative, design-oriented, and interdisciplinary contributions examining how governments identify, govern, and respond to critical dependencies while developing the capabilities required for digital agency and resilience.

Track Chairs: Anastasija Nikiforova (University of Tartu, Estonia), Rony Medaglia (Copenhagen Business School, Denmark), Francesco Gualdi (King's College London, UK), Luca Tangi (European Commission Joint Research Centre, Italy) Keywords: Digital sovereignty, AI sovereignty, Technology dependencies, Strategic capacity, Digital infrastructure


This track invites research that applies artificial intelligence, Agentic AI, data science, and computational methods to real problems in digital government. We are particularly interested in studies that move beyond broad discussions of AI and examine how intelligent systems are designed, implemented, used, and evaluated in public-sector settings.

Track Chairs: Loni Hagen (University of South Florida), Charalampos (Harris) Alexopoulos (University of the Aegean), Kellyton Brito, David Valle-Cruz, Shefali Virkar (WU Vienna University of Economics and Business), Corey Kewei Xu Keywords: Computational methods, Design science, Agentic AI, Decision support, Artifact evaluation

Cities are progressing beyond their people-centric digital transformation and now confront the more demanding challenge of people-centric AI transformation. Artificial intelligence (AI) increasingly shapes mobility systems, public-service delivery, infrastructure management and decision-making processes, while digital twins and the integrated virtual environments termed the Citiverse, which is driven by AI. In this context smart cities are evolving from enablers of smart growth, social coherence and industrial transformation into early adopters of AI-driven integrated physical and virtual worlds that must simultaneously address risks of exclusion, social-protection deficits and cybersecurity vulnerabilities. This track invites theoretical and empirical research as well as practice-oriented contributions that examine AI-related risks, development strategies for AI transformation, policy models for AI governance, spatial intelligence, citizen engagement mechanisms and technological innovations. In keeping with the conference theme, particular emphasis is placed on research that advances theoretical foundations and generates robust empirical evidence concerning AI-driven smart cities and the Citiverse, with the objective of enabling autonomous, transparent and personalised public services, non-mediated governance arrangements, data sovereignty, inclusive participation and co-creation platforms, placebased innovation, and the capacity of citizens and communities to maintain well-being and prosperity in the face of cyber-threats, poverty, the AI divide, violence and environmental pressures.

Track Chairs: Leonidas Anthopoulos (University of Thessaly, Greece), Manuel Pedro Rodríguez Bolívar (University of Granada, Spain), Alois Paulin (University of Ludwigsburg, Germany)Keywords: AI-driven smart cities, Urban digital twins, Citiverse, Spatial intelligence, Urban AI governance

Generative and agentic AI raises a practical question for digital government: what must public organisations know, judge, and control when AI contributes to their decisions and acts on their behalf? This track examines institutional judgment and accountable delegation across policy analysis, administrative work and public service delivery. It focuses on the arrangements through which organisations establish the provenance and contextual adequacy of AI-generated advice, retain professional discretion, authorise agent actions and provide reasons, review and redress. The track invites empirical, theoretical and design-oriented contributions on human oversight, shadow AI, verification work, institutional memory, procurement, and the allocation of responsibility across officials, vendors and technical systems. Comparative and international studies are particularly welcome, including research on differences in administrative capacity, language and institutional context. Contributions may investigate successful implementation, failures, workarounds or decisions to limit deployment. The track connects the conference’s concern with theoretical foundations and empirical evidence by examining how specific governance arrangements affect organisations’ capacity to make and justify public decisions. Its goal is to develop explanations and practical approaches for effective, accountable AI use grounded in the conditions of administrative practice.

Track Chairs: Luis Lozano-Paredes (University of Technology Sydney, Australia) Keywords: Institutional judgment, Accountable delegation, Evidence verification, Administrative discretion, Shadow AI


Human-AI collaboration and AI-enabled civic engagement are two emerging governance strategies with the potential to improve policy decision-making and implementation, but they create substantial accountability challenges. In human-AI collaboration, decision-making authority is distributed among governments, public employees, AI systems, and technology vendors, making it difficult to determine who should be held accountable for AI-assisted decisions. AI-enabled civic engagement further complicates accountability because governmental and non-governmental actors interact throughout the decision-making process. Addressing these accountability challenges is essential to improving public management and governance. Therefore, we invite scholars to investigate the following topics: (1) accountability framework for human-AI collaboration and AI-enabled civic engagement, (2) citizens’ perceptions of accountability attribution between state and non-state actors in human-machine interaction and AI-mediated civic engagement, (3) governance designs that clarify responsibilities and strengthen accountability among governments, public employees, technology providers, and civil society in AI-enabled cross-sector collaboration. We welcome conceptual articles and empirical research papers with qualitative, quantitative, and mixed-method approaches.

Track Chairs: Yi-Fan Wang (National Cheng Kung University, Taiwan), Tzuhao (Howard) Chen (Florida International University, USA), Yeonkyung Kim (Kean University, USA) Keywords: Accountability attribution, Human–AI collaboration, Civic engagement, Distributed responsibility, Cross-sector governance


This track examines the demand side of AI transformation, focusing on how artificial intelligence (AI) can improve citizen-facing public services and societal well-being by shifting attention from government providers to the needs, experiences, and outcomes of service users. As AI moves beyond technological development, it is being increasingly adopted across government, public services, and everyday life. AI policy must therefore address not only how AI is developed and supplied, but also how it is effectively adopted, used, diffused, and governed in society. The track examines the institutional and policy conditions needed to translate technological capabilities into public and societal value, with particular attention to the potential gap between rapid technological change and slower adaptation in legal and institutional frameworks, organizational processes, data governance, public-sector capabilities, and citizen adoption. It welcomes conceptual, empirical, and comparative research linking AI transformation in public services to citizens’ quality of life. Ultimately, the track seeks to clarify how AI adoption affects efficiency, accessibility, inclusion, safety, trust, quality of life, and broader societal well-being.

Track Chairs: Dongwook Kim (Seoul National University, South Korea), Seok-Jin Eom (Seoul National University, South Korea), WookJoon Sung (Seoul National University of Science and Technology, South Korea)Keywords: Demand-side AI policy, Citizen-facing services, AI adoption and diffusion, Institutional readiness, Societal well-being

Artificial intelligence (AI) is reshaping economic activity, public administration, and social interaction, while intensifying the strategic importance of data as a foundation for innovation and decision-making. At the same time, the growing deployment of AI systems creates interconnected challenges involving privacy, security, accountability, transparency, and the protection of fundamental rights. These concerns are particularly significant as AI becomes embedded in critical infrastructure, public services, and highimpact decision-making processes. This track examines how legal, institutional, and technical frameworks can support the development of an AI-driven society that is both innovative and trustworthy. Addressing issues such as data governance, privacy protection, cybersecurity, and AI regulation, it encourages integrated approaches that reflect their increasing interdependence. Particular attention is given to the governance of AI risks across the lifecycle of AI systems, the allocation of responsibility among relevant actors, and the evolving role of public institutions in establishing effective oversight and assurance mechanisms. It also considers international coordination and interoperability in response to the cross-border nature of AI. The track welcomes theoretical, comparative, empirical, and case-based research from multidisciplinary perspectives, with the aim of advancing policy and governance approaches that can balance AI innovation with security and public trust.

Track Chairs: Hun-Yeong Kwon (Korea University, Republic of Korea), Jung-Hee Lee (Korea University, Republic of Korea), Beop-Yeon Kim (Korea University, Republic of Korea), Mi-Ryang Kim (Sungkyunkwan University, Republic of Korea), Lyse Langlois (Laval University, Canada)Keywords: AI risk governance, Data protection, AI safety, Cybersecurity, Regulatory coordination

Local governments play a pivotal role in the digital transformation of public services, as they directly interact with citizens and communities. The adoption of AI technologies at the subnational level (cities, counties, municipalities) is reshaping how policies are implemented, how services are delivered, and how public officials interact with residents. This track explores the transformative role of Artificial Intelligence (AI) in local government (AX: AI Transformation), focusing on the intersection between ethical principles and the pursuit of public value. As AI systems increasingly support policy decisions, welfare services, and local governance, questions arise about fairness, transparency, accountability, and trust. The track invites scholars and practitioners to investigate how local governments can design, adopt, and govern AI in ways that not only ensure technical robustness but also align with core public values and democratic legitimacy. We particularly encourage contributions addressing algorithmic accountability, human–AI collaboration in local administration, citizen engagement with AI-enabled services, and comparative cases across different national or local contexts. By examining both opportunities and challenges, this track aims to build a shared understanding of how AI transformation can contribute to public value creation and public innovation at the local level.

Track Chairs: Jooho Lee (University of Nebraska at Omaha, U.S.), WookJoon Sung (Seoul National University of Science and Technology (SeoulTech), South Korea)Keywords: Local government, AI transformation, AI ethics, Algorithmic accountability, Public value

Who designs, delivers, and controls the digital public infrastructure of the future? Governments no longer hold a monopoly on digital public services. On the one hand, foreign BigTech providers deliver a growing share of the digital public infrastructure, from office software and cloud services to AI chatbots. On the other hand, GovTech startups, scaleups, and multi-helix initiatives deliver innovations such as AI-based assistants for public professionals and digital identity wallets. While GovTech promises co-creation and local market development, it also poses risks to long-term stability and knowledge dependencies. Meanwhile, digital sovereignty – the ability of governments to control their data, technology, and operations, and to determine which laws apply to them – is becoming a growing concern. Policy responses range from open innovation to protectionism, including sovereign cloud and AI, open-source software, public digital commons, and procurement requirements for interoperability and exit. GovTech and digital sovereignty can reinforce each other, but getting the balance wrong carries risks: GovTech without digital sovereignty safeguards can transform digital innovation into digital dependency, while digital sovereignty without GovTech innovation can turn digital control into protectionism, fragmentation, and costlier public services. This track invites papers on GovTech, digital sovereignty, and the balance between them.

Track Chairs: Nitesh Bharosa (Delft University of Technology, the Netherlands), Yannis Charalabidis (University of the Aegean, Greece), Joep Crompvoets (KU Leuven, Belgium), Tomasz Janowski (Gdańsk University of Technology, Poland / University for Continuing Education Krems, Austria), Anastasija Nikiforova (University of Tartu, Estonia) Keywords: GovTech, Digital sovereignty, Digital public infrastructure, Public digital commons, Procurement and vendor lock-in

Artificial intelligence (AI) is transforming cybersecurity in digital government by expanding capabilities for threat detection and response while introducing new vulnerabilities and enabling malicious activities. Governments must address three interconnected challenges: using AI to strengthen cyber defense, protecting public-sector AI systems, and responding to AI-enabled threats to public institutions and services. This track examines these challenges through technological, human, organizational, and governance perspectives. It invites research on AI-enabled cyberattacks; government adoption and evaluation of AI for cybersecurity; the security of generative and agentic AI; human–AI collaboration and organizational preparedness; and the implementation and effectiveness of governance frameworks. Particular attention is given to how institutional arrangements, administrative capacity, and oversight shape security outcomes and public values, including privacy, equity, accountability, and trust. We welcome theoretical contributions, rigorous empirical studies, and practice-informed evaluations across jurisdictions and levels of government, including negative findings and documented implementation failures. By connecting cybersecurity to the conditions under which AI supports responsible government innovation, the track advances the dg.o 2027 emphasis on theoretical foundations and empirical evidence.

Track Chairs: Sukumar Ganapati (Florida International University, United States), Catalin Vrabie (National University of Political Studies and Public Administration, Romania), Chul Hyun Park (University of Maryland, Baltimore County (UMBC), United States), Robert Richards (University of Arkansas, United States), Songkhun Nillasithanukroh (University of Arkansas, United States) Keywords: AI for cybersecurity, Security of AI systems, AI-enabled cyber threats, Cyber resilience, Security governance

This track examines the intersection of AI-driven municipal infrastructure, digital government governance, and social cohesion within modern private-public urban ecosystems, taking City, in example: BSD City in Banten Province, Indonesia, as a primary empirical model. As rapid urbanization accelerates across emerging economies, hybrid smart cities rely heavily on integrated technologies, including adaptive AI traffic management systems, subterranean electrical and fiber-optic micro-tunnels, hyper-speed telecommunications, and edge/cloud data centers. However, technological optimization alone does not guarantee equitable urban livability or social harmony. This track explores how smart physical infrastructure and localized data governance can be designed and regulated to bridge socioeconomic divides, reduce urban friction, and enhance civic trust. Key topics encompass AI traffic optimization, subterranean utility digital twins, data center policy frameworks, public-private-people partnerships (4P), and algorithmic equity in municipal service delivery.

Track Chairs: Ripto Mukti Wibowo (Atma Jaya Catholic University of Indonesia, Indonesia), Iqbal Sasmi (Seoul National University / BRIN, Indonesia), Feliks Prasepta S. Surbakti (Atma Jaya Catholic University of Indonesia, Indonesia)Keywords: Smart urban infrastructure, AI traffic management, Underground utilities, Data center governance, Social cohesion

Public Sector Co-Creation under Digital and AI Transformation examines how co-creation is evolving as public organizations respond to technological, institutional, and societal change. The track investigates how new forms of participation, digital and AI-enabled collaboration, computational approaches, and evolving relationships among governments, citizens, civil society, businesses, and other actors reshape co-creation across policymaking, public administration, and service delivery. The track welcomes theoretical and empirical research on the design, implementation, and evaluation of co-creation; citizen and stakeholder engagement; computational co-creation combining stakeholder knowledge with data and computational methods; the roles and competencies of participants; and the institutional and ecosystem conditions required to sustain meaningful co-creation. Particular attention is given to inclusion, equity, diversity, representation, ethics, sustainability, transparency, accountability, trust, resilience, and public value. AI-enabled and emerging agentic forms of co-creation constitute an important new area of inquiry, raising questions about participation, influence, discretion, and responsibility. Comparative studies, case studies, experiments, mixed-methods research, and studies of both successful and unsuccessful co-creation initiatives are particularly encouraged.

Track Chairs: Ripto Mukti Wibowo (Atma Jaya Catholic University of Indonesia, Indonesia), Iqbal Sasmi (Seoul National University / BRIN, Indonesia), Feliks Prasepta S. Surbakti (Atma Jaya Catholic University of Indonesia, Indonesia) Keywords: Smart urban infrastructure, AI traffic management, Underground utilities, Data center governance, Social cohesion

Traditionally, digital government research has focused on improved service delivery, efficient administration, open decision-making, and engaged citizens. This research was mainly driven by problems internal to government or to government-citizen relationships. More recently, the focus has shifted to mega-problems like pandemics, war, climate change, migration, etc., that no government can handle alone, and to problems of democratic breakup that require balancing government and societal powers. Addressing such problems requires institutions and individuals to work together for the wellbeing, security, and prosperity of all members of society, i.e., a stronger society based on cohesion, solidarity, resilience, equity, inclusion, and other values. This track will examine the evidence of digital government making societies stronger and capable of a whole-of-society response. For example, using assistive technologies across government and the economy to empower people with disabilities to lead independent, productive lives and support one another. The track will also examine evidence that digital government makes societies weaker and less capable of a whole-of-society response. For example, using social media to run divisive political campaigns (e.g., farmers vs. consumers) to win votes, while undermining prospects for common climate action.

Track Chairs: Nina Rizun (Gdańsk University of Technology, Poland), Noella Edelmann (University for Continuing Education Krems, Austria), Arpine Korekyan (United Nations Department of Economic and Social Affairs, USA), Amal Marzouki (University of Quebec at Rimouski, Canada), Maria Gintova (McMaster University, Canada) Keywords: Public sector co-creation, Stakeholder engagement, Computational co-creation, AI-mediated participation, Public value

Literacy originally means the ability to read and write. Digital literacy has become one of the most basic forms of human capital in a digital society, and unequal access to it translates into social inequality. Early research on the digital divide focused on gaps in access explained by socio-demographic factors such as gender, age, income, and education. Later work showed that the divide also lies in skills and use, and in the outcomes people gain from being online. More recently, the debate has moved beyond closing gaps between groups toward digital inclusion and equity as public policy and institutional design. Each new wave of technology has reopened the question: the big data era raised issues of data literacy and capability, and the rapid spread of AI now brings AI literacy and AI divides to the center. This track invites theoretical, methodological, and empirical contributions, including case studies and comparative research, on how digital and AI literacy, divides, inclusion, and equity are changing, and on what governments can do about them.

Track Chairs: Hanbyul Choi (Jeonbuk National University, Republic of Korea), Seung-Yoon Shin (Kyungpook National University, Republic of Korea), Jung Wook Moon (Korea Information Society Development Institute (KISDI), Republic of Korea), WookJoon Sung (Seoul National University of Science and Technology (SeoulTech), Republic of Korea)Keywords: Digital and AI literacy, Digital divide, AI divide, Digital inclusion, Equity in public services

The “Responsible AI in Government: From Standards to Public Value Evidence” track builds on the dg.o 2026 track “Responsible Digital Government: Standards and Public Value” and responds directly to the dg.o 2027 theme. Governments now operate under a growing body of responsible-AI principles, standards, and regulations, including ISO/IEC 42001, the NIST AI Risk Management Framework, and the EU AI Act. Yet evidence on whether these instruments build public trust, change how AI is designed and deployed, and ultimately create public value remains limited. This track aims to close that gap by connecting theoretical foundations of responsible AI governance with rigorous empirical evidence from practice. It welcomes conceptual, empirical, design-science, and comparative research, as well as practitioner case studies. Relevant topics include adoption and implementation of AI standards in public agencies; trust and human–AI collaboration in government services; algorithmic transparency, accountability, and auditing; methods and metrics for measuring the public value of AI; AI risk management and procurement; institutional and organizational factors in responsible AI transformation; AI literacy and workforce readiness; citizen engagement and inclusion; and cross-national comparisons, including Asia-Pacific and Global South contexts.

Track Chairs: Farhana Faruqe (University of Virginia, USA), Larry Medsker (University of Vermont, USA)Keywords: Responsible AI, AI standards implementation, Public value evidence, AI auditing, Trust and accountability

Digital Research Infrastructure (including cyberinfrastructure, high-performance, and AI computing) has become a strategic national asset, encompassing advanced computing systems, national research networks, data platforms, scientific software, and the human expertise required to operate and use them. Investments in cyberinfrastructure support scientific discovery, economic competitiveness, technological innovation, national security, public health, environmental resilience, and evidence-based policymaking. As governments increasingly invest in artificial intelligence, advanced modeling and simulation, dataintensive science, and emerging technologies, decisions regarding the development and governance of cyberinfrastructure have become matters of public policy with significant societal implications. This track examines the governance, policy, and strategic dimensions of digital research infrastructure at national, regional, and international scales. We welcome scholarship investigating public investment in supercomputing and advanced computing resources, the development of critical research facilities, national and international research infrastructure initiatives, scientific collaboration ecosystems, workforce development, sustainability challenges, and the public benefits produced through computationally enabled research. Contributions may explore governance models, funding strategies, organizational arrangements, access policies, and the societal impacts of cyberinfrastructure programs and facilities. We particularly encourage work examining how research cyberinfrastructure supports collaborative science, innovation, and national capacity in an era increasingly shaped by artificial intelligence and emerging technologies.

Track Chairs: Richard Knepper (Cornell University, USA), Kerk Kee (Texas Tech University, USA), Yu- Che Chen (University of Nebraska at Omaha, USA)Keywords: Research cyberinfrastructure, AI computing platforms, Infrastructure governance, Collaborative science, Public investment

We invite papers that address existing and novel issues of digital government, information systems, information policies, and AI in public health, healthcare and/or environmental sustainability. Governments and public institutions play critical roles in sustaining health and wellness through diverse activities, many of which are supported by information and communication technologies, data policies, and more recently artificial intelligence (AI). The goal of this track is to bring together people and research that address the following or related topics: The role of digital government and AI for advancing health. Applications of AI for public health, clinical medicine and/or environmental sustainability. Innovations in public health surveillance and health information systems. User-experience and design elements of websites and dashboards for public health data. The development and promotion of evidence-based guidelines. Information and communication technologies for environmental health or sustainability. Policies and regulations that address the secure use of health information. Social, psychological and/or political issues in health information and communication. Risk and crisis communication that impact public health, healthcare or environmental sustainability. Interoperability issues and solutions in the health data ecosystem. Strategies, policies and technologies to democratize access to health data.

Track Chairs: Nic DePaula (SUNY Polytechnic Institute, USA), Chun-Hua Tsai (University of Nebraska at Omaha, USA), Srishti Gupta (University at Albany, State University of New York, USA), Sulemana Bankuoru Egala (IESEG School of Management, France)Keywords: Public health, Healthcare, Environmental sustainability, Health information systems, AI enabled health services

Citizen engagement is essential to maximizing the impact of digital government and strengthening democratic governance. This track addresses participation in the design, implementation, and evaluation of public policies and services, and the involvement of citizen and other stakeholders in participatory and collaborative governance. The growing adoption of Artificial Intelligence (AI) in the public sector brings new opportunities and challenges to this agenda. Predictive, prescriptive, generative and agentic AI are changing how governments make decisions and interact with citizens, raising questions about algorithm transparency and accountability, the ability of citizens to understand and contest automated decision, and who takes part in shaping how AI is designed, used, and governed. The track welcomes studies on the structural, institutional, organizational, cultural, political, and cognitive dimensions that foster or hinder engagement, including the behaviors of citizens and civil servants, and on the contributions of engagement to transparency, trust, public innovation, and public value creation, and active citizenship. Research on how AI can enable or constrain engagement is encouraged, as are contributions on equity and inclusion, local and comparative perspectives, engagement during crises, and the effects of disinformation on trust and engagement.

Track Chairs: Edimara M. Luciano (Pontifical Catholic University of Rio Grande do Sul, Brazil), Gabriela V. Pereira (University for Continuing Education Krems, Austria), J. Ignacio Criado (Universidad Autónoma de Madrid, Spain) Keywords: Citizen engagement, Participatory governance, AI-mediated participation, Active citizenship, Citizen influence

This track welcomes forward-looking research on new and emerging issues in digital government that are not covered by the other tracks, including new technologies, new governance models and sociotechnical challenges. Papers that push the boundaries of digital government research are especially encouraged.

Track Chairs: Jooho Lee(University of Nebraska at Omaha, USA), Diogo Campos Sasdelli (University for Continuing Education Krems, Austria), Taehee Kim (Seoul National University of Science and Technology, South Korea)

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