Track Chairs:
Track Description:
The purpose of this track is to provide a forum for academics and practitioners to identify and explore the issues, opportunities, and solutions using Artificial Intelligence, computational ontologies, data driven IS, and intelligence related to business and systems including the social web, intelligent systems design, implementation, integration and deployment. An increasing number of artificial intelligence-based systems are being developed in different application domains employing a variety of tools and technologies. This track is intended to increase cross-fertilization of ideas from these areas, share lessons learned and stimulate areas for further research.
Ontology Driven IS (SIG ODIS)
Minitracks:
Social, Ethical, & Practical Impacts of AI for Organizations and Individuals
AI is an important and increasingly pervasive tool of industry whose widespread adoption has given rise to several criticisms, such as a lack of transparency of analytical models, a lack of explainability of results, workforce disruption, and the potential to introduce or perpetuate implicit biases. This mini-track aims to provide a forum for addressing the social, ethical, and practical aspects of AI and ML. Particularly, papers exploring the impact of AI/ML through various analytic lenses, including societal, organizational, and individual perspectives, are welcome.
Call for Papers:
AI is an important and increasingly pervasive tool of industry whose widespread adoption has given rise to several criticisms, such as a lack of transparency of analytical models, a lack of explainability of results, workforce disruption, and the potential to introduce or perpetuate implicit biases. This mini-track aims to provide a forum for addressing the social, ethical, and practical aspects of AI and ML. Particularly, papers exploring the impact of AI/ML through various analytic lenses, including societal, organizational, and individual perspectives, are welcome.
Potential topics:
- Behavioural and organizational aspects of AI and ML
- Automation of work through AI and ML
- Legal, ethical, governance issues, and biased use of AI/ML
- Effectiveness, business performance, job displacement, and the dark side of AI/ML
- Standards and frameworks for AI/ML modeling and implementation
- Explainable AI
- AI Adoption diffusion
- Ethical AI
- Self-regulation across industries
- Implicit and explicit bias in AI applications
- Social justice and social inclusion
Minitrack Chairs:
- Sunet Eybers, College of Science, Engineering & Technology, Information Systems Department, University of South Africa, Florida, Johannesburg, Gauteng, South Africa, eeyberss@unisa.ac.za
Agentic AI and Machine Learning – Applications, Solutions and Techniques
This mini-track focuses on the emerging paradigm of Agentic Artificial Intelligence (AI) — systems capable of autonomous goal-setting, reasoning in dynamic environments. As AI evolves beyond passive, data-driven models to proactive, self-directed agents, new challenges and opportunities arise in design, governance, human–AI collaboration, and the ethical deployment of AI.
The topic is of growing importance as organizations increasingly integrate autonomous AI systems into business, education, healthcare, and governance.
We invite theoretical, empirical, and application-oriented research that explores innovative agentic AI and machine learning approaches across diverse domains, including healthcare, finance, education, manufacturing, and smart cities. Topics of interest include agent-based modeling, multi-agent reinforcement learning, autonomous decision-support systems, explainable agentic AI, and the integration of large language models (LLMs) into intelligent agents.
This mini-track aims to foster dialogue among researchers, practitioners, and policymakers to advance understanding of agentic AI systems that are not only intelligent but also responsible, interpretable, and human-centered.
Call for Papers:
The Agentic AI and Machine Learning mini-track at AMCIS 2026 invites high-quality research contributions exploring the next generation of AI systems that exhibit autonomous, proactive, and adaptive self-learning behaviors. With the rapid advancement of large transformer-based language models (LLMs), reasoning agents, and reinforcement learning systems, AI research is evolving beyond predictive analytics toward agentic intelligence—where machines can reason, plan, and act with minimal human intervention while maintaining accountability and alignment with human values.
We welcome submissions that advance theoretical frameworks, methodological innovations, and real-world implementations of agentic AI. Research topics may include, but are not limited to:
• Agent-based AI architectures and their integration with LLMs and multimodal models
• Multi-agent collaboration and coordination in distributed and dynamic environments
• Reinforcement learning and autonomous decision-making in complex, uncertain systems
• Human–AI teaming and adaptive interfaces for effective co-agency
• Ethical, explainable, and trustworthy frameworks for agentic AI
• Applications in business, healthcare, education, defense, smart cities, and sustainability
• Evaluation metrics and benchmarks for autonomy, interpretability, and performance
This mini-track encourages interdisciplinary perspectives from computer science, information systems, cognitive science, and organizational research. We particularly welcome case studies, design science research, simulation studies, and empirical analyses that demonstrate how agentic AI systems can transform outcomes, innovation, and human–machine collaboration.
Researchers, practitioners, and policymakers are invited to submit full research papers, research-in-progress papers, or emerging ideas that push the boundaries of AI and machine learning toward agentic, responsible, and human-aligned systems.
Join us in exploring how agentic AI is reshaping the future of intelligent, ethical, and human-centered technologies.
Minitrack Chairs:
- Vedanarayanan Venugopal, School of electrical and electronics engineering, sathyabama institute of science and technology, chennai, Tamil Nadu, India, vedanarayanan.etc@sathyabama.ac.in
- Dr. Vijaya Baskar, ECE, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India, vijayabaskar.ece@sathyabama.ac.in
Promises and Perils in Ethics and Management of Artificial Intelligence: Disruption, Adoption, Dehumanisation, Governance, Risk and Compliance
“In the last decade, Artificial Intelligence (AI) has transitioned from a peripheral technology to a dominant driver of innovation. It is now used to recognize images, parse speech, answer questions, make decisions, and even replace humans.
Generative AI presents exciting possibilities, from text generation to image synthesis, but it also brings ethical challenges. Misused generative AI tools can breach privacy, jeopardize safety, and make unethical decisions. To navigate this landscape effectively, researchers and practitioners must understand the state of the art, adoption, and influence of AI and ML, while addressing ethical and governance mechanisms needed to safeguard human well-being. This minitrack focuses on the ethics and management of AI, with a particular emphasis on adoption, disruption, dehumanization, and governance, risk, compliance, and the ethical mechanisms required to protect and enhance human well-being. We welcome qualitative and quantitative orientations, offering both theoretical and practical contributions, from personal, organizational, and societal perspectives.”
Minitrack Chairs:
- Dr. Valeria Aleksandra Sadovykh, University of Auckland, Auckland, New Zealand, valeriasadovykh@gmail.com
- Gabrielle Peko, University of Auckland, Auckland, New Zealand, g.peko@auckland.ac.nz
- Ruhi Bajaj, University of Auckland, Auckland, New Zealand, r.bajaj@auckland.ac.nz
- Pooja Sengupta, University of Auckland, Auckland, New Zealand, pooja.sengupta@auckland.ac.nz
- David Sundaram, University of Auckland, Auckland, New Zealand, d.sundaram@auckland.ac.nz
Generative AI: Practical Applications and Social Impact
Given the rapidly developing field of Generative AI, this mini-track explores the practical applications of Generative AI across various industries, its profound social impact, and the ethical considerations that arise from its use. Topics of interest include how generative models transform domains including creative content creation, healthcare, and education, while also addressing the societal challenges and moral dilemmas their application presents. Additionally, this track will critically examine the broader impacts of these technologies on society, including issues of algorithmic bias, data privacy, and the development of robust ethical frameworks for generative AI deployment as well as socio-technical perspectives that consider how these technologies can be designed and governed to serve the public good.
Call for Papers:
Potential Topics:
• Practical applications of Generative AI across industries such as healthcare, education and entertainment.
• Societal impact of Generative AI including its impact on culture, society, the future of work and legal frameworks.
• Inclusive and equitable AI innovation: exploring accessibility, representation, and the digital divide.
• Technical foundations and Advancements in Generative AI including architecture design, innovations in training techniques as well as performance evaluation and benchmarking.
• Human-centered and participatory design approaches for generative systems.
• Ethical frameworks and governance models for the responsible deployment of generative AI.
• Socio-technical systems thinking: how generative AI reshapes human decision-making, social dynamics, and institutional trust.
Minitrack Chairs:
Quantum Computing and Artificial Intelligence for Intelligent Information Systems
This minitrack focuses on the emerging convergence of quantum computing and artificial intelligence (AI) in advancing the design, optimization, and scalability of intelligent information systems. As classical computing approaches its performance limits, quantum paradigms—such as quantum machine learning, quantum natural language processing, and quantum-enhanced optimization—offer transformative potential for data-driven decision support, cybersecurity, and enterprise analytics. This minitrack invites conceptual, technical, and empirical studies that explore how quantum algorithms, hybrid classical-quantum architectures, and quantum-inspired models can enhance intelligence, reasoning, and interpretability in information systems. We particularly encourage submissions that integrate theoretical foundations with real-world applications, tool development, or design-science artifacts for business, management, or societal contexts.
Potential Topics include:
Hybrid AI–quantum architectures for decision and optimization tasks
Quantum-inspired algorithms for data analytics and intelligent automation
Integration of AI reasoning and semantic technologies in quantum workflows
Design and evaluation of next-generation intelligent systems
Ethical, governance, and organizational implications of emerging computational paradigms
Minitrack Chairs:
- Giridhar Reddy Bojja, College of Business, Michigan Technological University, Houghton, Michigan, United States, gbojja1@mtu.edu
- Loknath Sai Ambati, Meinders School of Business, Oklahoma City University, Oklahoma City, Oklahoma, United States, lambati@okcu.edu
- Dr. Veerpratap Meena, National Institute of Technology – Jamshedpur, Jamshedpur, India, vmeena1@ee.iitr.ac.in
Semantics and Ontologies in Information Systems
Research in ontology, ontology-driven information systems and ontology applications is becoming increasingly widespread in the information systems community, especially given the challenges experienced with providing context for Generative AI. Its importance is being recognized in various research fields and application areas. This mini-track is primarily concerned with the use and application of ontologies and any semantic languages such as RDF(s) and OWL, as well as the associated technologies (such as querying, reasoning and reasoners) within information systems. Within this mini-track, the term ontology includes artefacts that use any semantic web languages such as OWL and RDF(S).
Call for Papers:
Research in ontology, ontology-driven information systems and ontology applications is becoming increasingly widespread in the information systems community. Its importance is being recognized in various research fields and application areas. This mini-track is primarily concerned with the use and application of ontologies and any semantic languages such as RDF(s) and OWL, as well as the associated technologies (such as querying, reasoning and reasoners) within information systems. Within this mini-track, the term ontology includes artefacts that use any semantic web languages such as OWL and RDF(S).
Potential topics:
- Semantic applications supporting generative AI
- Semantic applications within information systems
- Ontology-driven information systems
- Semantic-based systems architecture
- Ontology integration and ontology systems integration
- Meta-data
- Ontology querying and reasoning
- Ontology reuse
- Ontology engineering
- Specialised domain ontologies (e.g. enterprise ontology)
- Ontology tools and technologies
- Ontology-driven systems development and systems development methodologies
- Upper, domain and application ontologies
Minitrack Chairs:
- Aurona, Gerber Information Science, Stellenbosch University, Stellenbosch, Western Cape, South Africa, auronagerber@sun.ac.za
Customer Experience and Organizational Intelligence
Organizations are increasingly engaging with current and potential customers across a multitude of IT-mediated “touch points,” ranging from digital platforms to AI-driven systems. As these touch points expand in variety and sophistication, the need for coordinated and intelligent strategies will dominate management thought in the near and intermediate future. To stay competitive, organizations must leverage cutting-edge practitioner and academic research to tackle crucial challenges, such as differentiating user experiences across these varied interaction points, leveraging AI & ML to increase consumer reach, enhancing conversion rates, sustaining long-term customer loyalty, and seamlessly managing both global and local user experiences. At the core is a network of intelligent technologies, devices, and communication systems that enable seamless computing, collaboration, and commerce functionalities for end-customers. By embedding data, sensors, and controllers into physical and virtual environments, organizations can foster real-time, personalized interactions and dynamic co-engagement, creating value for both the customer and the organization.
Call for Papers:
Organizations are increasingly engaging with current and potential customers across a multitude of IT-mediated “touch points,” ranging from digital platforms to AI-driven systems. As these touch points expand in variety and sophistication, the need for coordinated and intelligent strategies will dominate management thought in the near and intermediate future. To stay competitive, organizations must leverage cutting-edge practitioner and academic research to tackle crucial challenges, such as differentiating user experiences across these varied interaction points, leveraging AI & ML to increase consumer reach, enhancing conversion rates, sustaining long-term customer loyalty, and seamlessly managing both global and local user experiences. At the core is a network of intelligent technologies, devices, and communication systems that enable seamless computing, collaboration, and commerce functionalities for end-customers. By embedding data, sensors, and controllers into physical and virtual environments, organizations can foster real-time, personalized interactions and dynamic co-engagement, creating value for both the customer and the organization.
Potential Topics for Submission:
Intelligent Customer Touch Points
AI and ML-Driven User Experience
AI Mechanisms for Expanding Consumer Reach
Improving Conversion Rates through AI/ML
Sustaining Customer Loyalty through Predictive Analytics
Managing Global and Local Customer Experiences via AI-driven Solutions
Seamless Customer-Organization Interaction through ICT
Organizational Intelligence: Acquisition and Management
Enhancing Customer Experience via Digital Technologies
Customer Value Co-Creation through Intelligent Service Systems
Emerging digital technologies, AI, learning for personalized interactions
Innovative customer service models.
Submissions should demonstrate how AI/ML and advanced analytics create dynamic, personalized customer experiences, fostering proactive engagement and innovation across industries. Join us in exploring the future of customer interaction through cutting-edge technologies.
Keywords: AI, machine learning, predictive analytics, preventive analytics, recommender systems, quality of service, customer experience, user engagement, conversion optimization, ICT, IoT, big data, digital transformation, personalization, global/local engagement strategies
Minitrack Chairs:
- Sowmya Kamath, Dept. of Information Technology, National Institute of Technology Karnataka, Surathkal, Mangalore, Karnataka, India, sowmyakamath@nitk.edu.in
- Geetha Vasantha, Dept of Information Technology, NITK Surathkal, Mangalore, Karnataka, India, geethav@nitk.edu.in
Interplay and Acceptance of Intelligent Information Systems
In recent years, digital transformation has not only led to increased acceptance of the use of information technologies but also great challenges. As a result, new topics and trends emerged to address the steadily increasing amount of data and its efficient and innovative exploration. Apart from the main drivers, artificial intelligence and cloud computing, also concepts like edge computing, big data, microservices, deep learning, distributed systems as well as composable architectures came into play. Although these are widely recognized today, their interplay provides new potentials and reveals novel challenges. Hence, in this mini-track, we welcome a variety of research approaches related to the investigation of related topics.
Potential topics:
-Artificial intelligence and cloud computing
-Edge computing and big data
-Microservices and distributed systems
-Deep learning and intelligent systems
-Cyber-physical systems
-Behavioral and managerial aspects of intelligent systems
-Acceptance and adoption of intelligent systems
Minitrack Chairs:
- Matthias Volk, Department of Technical and Business Information Systems , Otto-von-Guericke University Magdeburg, Magdeburg, Germany, matthias.volk@ovgu.de
- Daniel Staegemann, Otto-von-Guericke University, Magdeburg, Germany, daniel.staegemann@ovgu.de