Theocharis Tavantzis

01 About

• AI transformation & organisational change
• Behavioral software engineering
• Human-centered AI
• Mixed methods

02 Publications

Newest first. See Google Scholar for citation counts.

Journal articles

1. 2026

   JSS

   From challenge to change: Design principles for AI transformations

   T. Tavantzis, S. Lambiase, D. Russo, R. Feldt

   Journal of Systems and Software, vol. 243, p. 113063

   Abstract

   The rapid rise of Artificial Intelligence (AI) is reshaping Software Engineering (SE), creating new opportunities while introducing human-centered challenges. Although prior work notes behavioral and other non-technical factors in AI integration, most studies still emphasize technical concerns and offer limited insight into how teams adapt to and trust AI. This paper proposes a Behavioral Software Engineering (BSE)-informed, human-centric framework to support SE organizations during early AI adoption. Using a mixed-methods approach, we built and refined the framework through a literature review of organizational change models and thematic analysis of interview data, producing concrete, actionable steps. The framework comprises nine dimensions: AI Strategy Design, AI Strategy Evaluation, Collaboration, Communication, Governance and Ethics, Leadership, Organizational Culture, Organizational Dynamics, and Up-skilling, each supported by design principles and actions. To gather preliminary practitioner input, we conducted a survey (N=105) and two expert workshops (N=4). Survey results show that Up-skilling (15.2%) and AI Strategy Design (15.1%) received the highest $100-method allocations, underscoring their perceived importance in early AI initiatives. Findings indicate that organizations currently prioritize procedural elements such as strategy design, while human-centered guardrails remain less developed. Workshop feedback reinforced these patterns and emphasized the need to ground the framework in real-world practice. By identifying key behavioral dimensions and offering actionable guidance, this work provides a pragmatic roadmap for navigating the socio-technical complexity of early AI adoption and highlights future research directions for human-centric AI in SE.

   DOI PDF arXiv

2. 2024

   Future Internet Open access

   The Use of Artificial Intelligence in eParticipation: Mapping Current Research

   Z. Vasilakopoulos, T. Tavantzis, R. Promikyridis, E. Tambouris

   Future Internet, vol. 16, no. 6

   Abstract

   Electronic Participation (eParticipation) enables citizens to engage in political and decision-making processes using information and communication technologies. As in many other fields, Artificial Intelligence (AI) has recently started to dictate some of the realities of eParticipation. As a result, an increasing number of studies are investigating the use of AI in eParticipation. The aim of this paper is to map current research on the use of AI in eParticipation. Following PRISMA methodology, the authors identified 235 relevant papers in Web of Science and Scopus and selected 46 studies for review. For analysis purposes, an analysis framework was constructed that combined eParticipation elements (namely actors, activities, effects, contextual factors, and evaluation) with AI elements (namely areas, algorithms, and algorithm evaluation). The results suggest that certain eParticipation actors and activities, as well as AI areas and algorithms, have attracted significant attention from researchers. However, many more remain largely unexplored. The findings can be of value to both academics looking for unexplored research fields and practitioners looking for empirical evidence on what works and what does not.

   DOI PDF

Conference & workshop papers

1. 2025

   CHASE

   Unpacking Organizational Change in AI Transformations of Software Engineering

   T. Tavantzis, R. Feldt

   IEEE/ACM 18th Int. Conf. on Cooperative and Human Aspects of Software Engineering (CHASE), pp. 149–160

   Abstract

   As Artificial Intelligence (AI) becomes integral to software development, understanding the social and cooperative dynamics that drive AI-led organizational change is important. Yet, despite AI’s rapid progress and influence, the human and cooperative facets of these shifts in software organizations remain relatively less explored. This study uses Behavioral Software Engineering (BSE) as a lens to examine these often-overlooked dimensions of AI transformation. Through a qualitative approach involving nine semi-structured interviews across four organizations that are undergoing AI transformations, we performed a thematic analysis that revealed numerous sub-themes linked to twelve BSE concepts across individual, group, and organizational levels. Since the organisations are at an early stage of transformation we found more emphasis on the individual level. Our findings further reveal six key challenges tied to these BSE aspects that the organizations face during their AI transformation. Aligned with change management literature, we emphasize that effective communication, proactive leadership, and resistance management are essential for successful AI integration. However, we also identify ethical considerations as critical in the AI context—an area largely overlooked in previous research. Furthermore, a narrative analysis illustrates how different roles within an organization experience the AI transition in unique ways. These insights underscore that AI transformation extends beyond technical solutions; it requires a thoughtful approach that balances technological and human factors.

   DOI PDF arXiv

2. 2024

   PROFES

   ReqGenie: GPT-Powered Conversational-AI for Requirements Elicitation

   F. Fotrousi, T. Tavantzis

   Product-Focused Software Process Improvement (PROFES), Springer, pp. 352–359

   Abstract

   Requirements elicitation is a crucial activity in the software product lifecycle, ensuring a clear understanding of the user needs and project goals. This process guides the design, development, and validation phases, resulting in a successful and functional product. However, eliciting requirements often encounters the challenge of finding experts to gather, analyze, and validate the requirements. To address those challenges, this study aims to investigate the potential of Conversational AI, specifically utilizing OpenAI’s custom GPT, to elicit requirements through stakeholder interviews. Employing an iterative design science approach, ReqGenie was implemented to gather and summarize requirements from text-based interviews. A preliminary performance evaluation of ReqGenie, conducted by comparing its outputs with two existing Software Requirements Specification (SRS) documents, demonstrates promising results. The findings suggest that ReqGenie is particularly supportive for small-scale requirements elicitation tasks, including the software customization in product lines.

   DOI

3. 2024

   PCI

   Towards exploiting BPMN and DMN in public service modeling

   T. Tavantzis, R. Promikyridis, E. Tambouris

   27th Pan-Hellenic Conf. on Progress in Computing and Informatics (PCI ’23), ACM, pp. 211–216

   Abstract

   Modeling of Public Services (PSs) is used by a large number of public authorities worldwide to improve their quality. The resulting diagrams are useful in the case of simple PSs, however they can become very complex in the case of complex PSs. To address process complexity, the integration of Business Process Model and Notation (BPMN) and Decision Model and Notation (DMN) has been proposed. DMN is applied to model the decision logic of a process and has proven to provide promising results in the private sector. However, BPMN and DMN integration has not been studied in the case of PSs. The aim of this paper is twofold. First, to investigate when DMN is applied to model decision logic in the case of complex PSs. Second, to identify a set of steps and principles for integrating BPMN and DMN. For this purpose, a literature review is conducted, leading to the result that there is limited research on the use of BPMN and DMN in PS while research on integration is missing. In addition, a selected PS is modeled based on criteria and finally, a set of steps and principles for integrating BPMN and DMN is proposed.

   DOI

4. 2022

   ICEGOV

   Integrating BPMN with DMN to model complex Public Services: The case of Getting a Transportation Card for Disabled in Greece

   E. Tambouris, T. Tavantzis, K. Vergidis, A. Gerontas, K. Tarabanis

   15th Int. Conf. on Theory and Practice of Electronic Governance (ICEGOV ’22), ACM, pp. 124–130

   Abstract

   The provision of high-quality Public Services constitutes a core activity of the public sector. Consequently, PS modeling has received considerable attention. The Business Process Model and Notation (BPMN) is a standard often employed in PS modeling. BPMN diagrams are clear and understandable in case of simple PSs. However, this is not true when modeling complex PSs, i.e., those including a large number of versions. Different versions exist since, for example, different groups of citizens may have to submit different supporting documents with their application based on their financial or civil status. In those cases, the relevant BPMN diagrams have numerous gateways thus becoming very complex, which hinders their applicability and usefulness. In the last few years, the Decision Model and Notation (DMN) has been introduced and its integration with BPMN has been used for complicated business processes. However, effectiveness has not been investigated in the context of complex PSs. The aim of this research is to investigate the benefits and challenges of using BPMN and DMN. For this purpose, the Greek “Getting a Transportation Card for Disabled” PS is analyzed and modeled in two different ways, one without and one with the use of DMN. The results suggest that DMN models provide useful insights into PS versions while BPMN diagrams become simpler and more understandable. On the other hand, the public sector needs to accommodate yet another modeling notation which increases the required human capital needed.

   DOI

03 Committees

04 CV

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05 Contact