The study aims to investigate the digital transformation processes within the agri-food sector and their influence on business model innovation (BMI) as a pathway toward sustainability. Specifically, it analyses how agri-food companies are exploiting the potential of digital technologies (DTs) to reshape their value creation processes, enhance competitiveness, and address environmental and economic challenges. In order to exploit DTs and integrate them into business operations, it is essential to innovate the companies’ business model by rethinking traditional operational and strategic logics. This underscores the necessity of both the adoption of new technologies and the transformation of the business model. Despite the multiple opportunities offered by DTs, their introduction in agri-food companies presents significant obstacles due mainly to a lack of knowledge, limited digital skills or to the high costs associated with their implementation. Addressing these barriers, requires a growing emphasis on knowledge co-creation-oriented approaches, that integrate diverse disciplines and sectors. In order to pursue this objective, the study adopts a theoretical approach, based on an analysis of the existing literature on DTs and their role in fostering BMI and sustainability, and boundary management within the agri-food sector. The research focuses on the role of company boundaries as collaborative spaces that can facilitate the adoption of DTs and promote co-creation dynamics. The findings of the research lead to the development of a theoretical framework aimed at guiding agri-food companies in their transition toward more innovative and sustainable business models. This study offers theoretical contributions to support companies in leveraging DTs for sustainable development.

The adoption of innovative technologies can help agrifood companies face crucial challenges related to meeting the food needs of a growing world population, adapting to and mitigating the effects of climate change, and increasing the resilience of supply chains against sudden disruptions. In fact, several studies highlight the advantages that technological innovation can bring to agrifood supply chains. At the same time, few studies examine the connections between technological innovation and risk management. This study aims to help bridge this gap by reviewing and organizing previous findings. Specifically, this paper provides a classification of the main risks affecting agrifood supply chains and investigates the role that technological innovations may play in helping agrifood companies address key risks. The results lead to the identification of five main risk categories: food safety, information management, environmental, geopolitical, and supply chain management risks. Furthermore, the literature review focuses on six key technologies, including blockchain, Internet of Things, big data, artificial intelligence, drones, and digital twins. From this perspective, the results show that blockchain tracking systems allow companies to monitor product conditions throughout the supply chain. This helps ensure product quality, combat counterfeiting, and support the management of information and product flows. IoT systems are especially useful for mitigating food safety risks by enabling real-time monitoring during cultivation, transport, and distribution. Big data and AI-based solutions mainly support precision agriculture activities, contributing to the mitigation of environmental risks. Finally, the study highlights emerging applications related to drones and digital twins. Ultimately, this study provides several relevant contributions. First, it helps organize the fragmented contributions on the impact of technologies on risk management in the agrifood industry. Second, it offers a solid theoretical foundation for analysing the implications of technological applications on different risk categories. Third, it provides useful insights for practitioners to assess how technological innovation may help manage and mitigate key risks.

The European Union plays an important role in promoting the Sustainable Development Goals (SDGs) of the 2030 Agenda through the advancement of sustainable finance. The aim of sustainable finance is to direct financial resources toward initiatives aligned with ESG (Environmental, Social, and Governance) principles. However, unlike financial ratings based on recognized accounting standards, a globally shared framework for assessing ESG activities and investments is still lacking.
To fill this gap, the EU has launched a process to develop common standards for identifying sustainable economic activities, not only from an environmental but also from a social perspective.
In this context, the proposal for a European Social Taxonomy has emerged, developed by the Platform on Sustainable Finance (PSF). Its goal is to classify projects, investments, and policies based on their social impact. The three main objectives identified, decent work, well-being and adequate living conditions, and inclusive societies, are supported by sub-goals to facilitate implementation and reporting.
Nonetheless, the analysis of social variables remains particularly complex due to their qualitative, multidimensional, and often subjective nature, which makes objective and standardized measurement challenging. In the absence of a global social reporting standard, practices remain heterogeneous and fragmented, undermining data comparability and the development of evidence-based policies.
In this scenario, Public Administrations (PAs) are called upon to adopt effective tools to make their social actions visible, measurable, and communicable. The Final social balance sheet serves as a key tool for accountability and transparency, useful for strengthening the relationship with citizens and evaluating the public value generated.
The integration of the Social Report, the Social Taxonomy, and Artificial Intelligence (AI) represents a strategic opportunity to improve the analysis, monitoring, and implementation of social policies in alignment with the 2030 Agenda. This study analyzes the approach adopted by local administrations in social reporting and the potential of AI to enhance these processes, promoting more effective and sustainable public governance.

The integration of Artificial Intelligence (AI) into sustainability practices is transforming industries by enabling innovative solutions to complex challenges. However, while the nexus between AI and economic or environmental sustainability has been the subject of substantial academic inquiry, its potential role in advancing social sustainability remains comparatively underexplored. Social sustainability, encompassing critical aspects such as health and well-being, equitable access to education, and community resilience, is fundamental to the development of sustainable societies and is explicitly linked to Sustainable Development Goals (SDGs) such as SDG 3 (Good Health and Well-being), SDG 4 (Quality Education), and SDG 11 (Sustainable Cities and Communities). In the energy sector, where innovation is a primary driver, AI is increasingly employed to address issues including energy equity, workforce safety, and community development. The success of such initiatives, however, critically hinges on stakeholder perception, which influences the legitimacy and acceptance of AI-driven practices. This study aims to bridge the gap between AI applications and their social implications by examining how AI-driven innovative practices in the energy sector can enhance social sustainability and Environmental, Social, and Governance (ESG) performance. Specifically, it focuses on the role of stakeholder perception as a key determinant of the success of socially sustainable initiatives. By integrating concepts from stakeholder theory and knowledge management frameworks, this research seeks to advance theoretical understanding while offering practical strategies for achieving sustainability goals in knowledge-intensive and innovation-driven industries. The paper presents a review of the extant literature and outlines a research proposal predicated on a mixed-methods approach, focusing on case studies of energy companies implementing AI for social sustainability.

This paper examines the role of Artificial Intelligence (AI) in advancing sustainability, focusing on the intersection of AI and social sustainability. Given the substantial body of research in this field, a systematic review of over 2,000 articles was conducted. The sample was first analysed descriptively, followed by a thematic grouping based on sustainability dimensions. Notably, the social dimension of sustainability was underrepresented, prompting a more detailed exploration of AI’s role in addressing social sustainability. To explore AI’s role in advancing social sustainability, this study uses the Socio-Technical Systems (STS) framework. STS, developed by Emery and Trist (1960), examines the interplay between technology and social systems, focusing on five elements: technology, work processes, people, organizational structures, and the external environment. These elements guide the analysis of AI’s effects across sectors such as healthcare, education, and governance. The study highlights AI’s role in reshaping workflows, skill development, organizational hierarchies, and societal systems, while addressing global challenges like climate action and economic resilience.The study contributes to the field by integrating STS into AI and social sustainability, providing a structured lens to assess AI’s impact. It offers actionable insights for policymakers, organizations, and researchers on how to leverage AI responsibly, ensuring ethical governance, fairness, and inclusivity. The study emphasizes the need for frameworks that balance AI’s opportunities with potential risks, promoting responsible AI deployment across sectors.

Social sustainability is a fundamental pillar for the balanced and inclusive development of contemporary societies. It embodies the commitment to social equity, inclusion, respect for human rights, and the promotion of collective well-being. Artificial intelligence (AI), with its increasing deployment, is emerging as a key tool for addressing social challenges and promoting sustainability goals, which, to date, also involve education, following the provisions of Sustainable Development Goal 4 (SDGs 4) of the UN 2030 Agenda. The integration of artificial intelligence (AI) technology into education has introduced many possibilities. However, it also raises ethical issues that require careful consideration. This paper aims to highlight the importance of considering AI as a driver for educational inclusion, starting with an analysis of its potential. The study delves into the benefits and challenges of the introduction of a generative AI chatbot by Multiversity Group, Italy’s largest group operating in the Digital Education sector and Europe’s second largest group, which, driven by its vision of AI-enhanced education, collaborated with strategic consulting firm Bain & Company to build such a generative chatbot, leveraging OpenAI technology, to provide a better learning experience for students by fostering engagement and interaction with professors, and to combine didactic delivery and interactive assistance to learners. This paper aims to explore the emerging contribution of AI in education to promote innovative and inclusive educational delivery to reduce possible educational inequalities, considering the benefits, challenges and ethical implications of implementing the technology. AI can be an enabler for social progress, but it requires attention relative to the risks of discrimination and risks related to privacy and data security. The paper analyzes the high-impact challenges faced in developing the generative AI project to ensure that student data is securely managed in compliance with legal standards, such as GDPR 2016/679, the qualitative value of responses, the need for continuous monitoring, and overcoming any technological limitations.

Business success is no longer defined solely by financial performance or the quality of goods and services provided. It is imperative for companies to embed sustainability into their strategic frameworks, embracing socially and environmentally responsible practices. Businesses must now prioritize aligning profit with ethical and sustainable practices that enhance lives, protect the environment, and foster inclusive communities.
In this new mindset, work focuses on growth as well as output, redefining productivity around well-being and sustainability in a people-centered “productive revolution.”
Emerging technologies such as artificial intelligence (AI) offer new ways of organizing work, helping companies use their resources more effectively. It is through intelligent automation that many repetitive, low-value tasks can be eliminated, freeing up time for more strategic and creative activities. This makes it possible to reduce working hours without compromising, and indeed improving, both productivity and competitiveness.
At the same time, AI plays a fundamental role in knowledge management (KM), due to its ability to collect, analyze, and organize large volumes of data, enabling the creation, sharing, and preservation of knowledge within companies.
The reduction of working hours is increasingly central to the debate on the future of work, closely linked to the issue of work-life balance. Improving the balance between private and professional life has become a priority for many companies. What experiences such as the “4 Days Week” have demonstrated in various European countries is that they can bring tangible benefits: greater well-being, motivation, productivity, and improved talent retention.
The present study aims to explore the role of AI in transforming work models, focusing in particular on the effects of reducing working hours on productivity and knowledge management. The analysis will be carried out through a theoretical-documentary research approach, based on an integrated review of scientific literature, institutional reports, and national and international business cases, with particular reference to the themes of artificial intelligence, productivity, and knowledge management.

The global imperative for sustainable development is compelling industries to reassess operations, emphasizing Environmental, Social, and Governance (ESG) criteria. The energy sector, pivotal yet environmentally impactful, faces intense pressure to innovate sustainably. Artificial Intelligence (AI) offers transformative potential, particularly its application in Knowledge Management (KM) systems to enhance information handling for superior ESG performance. However, a literature gap exists concerning the interplay between AI-driven KM, ESG outcomes, stakeholder perceptions, and corporate competitiveness in this sector. This proposal outlines a study to investigate these dynamics: how AI-driven KM influences ESG outcomes, how stakeholders perceive these innovations, and how such practices might bolster energy companies’ competitive advantage. A mixed-methods design is planned (literature review, three Italian energy sector case studies, a survey of ~150 stakeholders). Findings are expected to show a positive AI-KM impact on ESG metrics, multifaceted stakeholder perceptions (more positive externally, varied internally with concerns like job displacement), and enhanced competitiveness through innovation and efficiency. The study aims for theoretical contributions to the AI-KM-ESG nexus and practical insights for energy executives.

The growing focus on sustainability and mitigation of environmental risks has made the ESG (Environmental, Social and Governance) framework a central element in the strategic and operational management of modern organizations. In a context marked by increasingly stringent regulatory pressures – such as the Corporate Sustainability Reporting Directive (CSRD) and the recommendations of the Task Force on Climate-related Financial Disclosures (TCFD) – companies are now called upon to integrate ESG metrics into their decision-making processes, in order to address global challenges such as climate change, biodiversity loss and the necessary ecological transition. However, the fragmentation of available data and the lack of adequate predictive tools continue to hinder truly effective and future-oriented ESG management. This study proposes an innovative operating model based on the synergistic integration between Artificial Intelligence (AI) and Process Mining, with the aim of improving monitoring, automation and transparency in ESG processes. AI allows the processing of large volumes of heterogeneous and unstructured data, while Process Mining allows you to map and optimize business flows, detecting inefficiencies and ensuring traceability. The model proves to be particularly effective for financial institutions and companies operating in sectors with high climate exposure, providing concrete answers to the needs of regulatory compliance and strategic sustainability. The adoption of this approach makes it possible not only to anticipate environmental risks, but also to strengthen organizational resilience and support the transition to a “sustainability-first” paradigm. The study highlights the transformative potential of AI-driven Process Mining in ESG management, offering scalable and replicable solutions for sustainable innovation that combines efficiency, responsibility and competitiveness in the long term.

The integration of Environmental, Social, and Governance (ESG) principles into corporate strategy has emerged as a global imperative, catalyzed by regulatory frameworks, investor pressure, and increasing stakeholder expectations. However, the complexity of ESG data collection, analysis, and reporting poses significant challenges for organizations. Recent advances in Artificial Intelligence (AI) have led to the development of AI-enabled platforms, such as PlaNet, CliMax, and Choral, which promise to transform ESG management. This paper presents a comprehensive analysis of the adoption and impact of these platforms across a diverse set of Italian companies, drawing upon more than twenty real-world case studies from sectors including finance, consulting, manufacturing, events, and digital. Through a mixed-methods approach combining document analysis, platform review, and cross-case synthesis, we examine how AI supports ESG data management, stakeholder engagement, decarbonization strategies, and organizational learning. Our findings reveal sector-specific adoption patterns, highlight operational improvements, and document the emergence of new forms of transparency and cultural engagement. The study concludes with actionable recommendations for organizations seeking to leverage AI for sustainable business transformation and outlines avenues for future research on the digitalization of ESG.

The past decades have witnessed a surge of research interest in academic engagement, largely focusing on academic entrepreneurship. However, academics also engage through other forms of knowledge application, broadly referred to as academic engagement. Drawing on the domain of academic engagement, in the last years arise an innovative form named Proof-of-concept (PoC) characterized by the interaction between many actors coming from different contexts, as researchers, professionals, managers and entrepreneurs.
This paper aims to review and analyze organizational mechanisms in proof-of-concept projects (PoCP). It develops the theoretical literature on PoC, particularly in the context of university-industry relations in academic engagement. Through a systematic literature review (SLR), the paper examines 85 published articles.
Findings show that literature on PoC is fragmented; various definitions of PoC are used and different typologies of PoC need the adoption of different organizational mechanisms. The research identifies areas that are currently underdeveloped. While the knowledge management framework is lacking in the reviewed literature, our findings highlight a growing interest in this area.
Recent studies reveal a call from the literature to identify knowledge integration issues and mechanisms for successful PoCP in academic engagement field. This paper provides an overview of the current state of research on PoCP and outlines new research opportunities, focusing on underexplored areas within the academic engagement field.

In the management of public sector, digital transformation is supposed to lead to new and better service delivery by increasing efficiency and transparency, and by improving accountability. The complexity of the transformation process increases, in terms of actors involved and effects on working practice and way of interacting and offering services. The pressure is more and more on the response to the changing needs and aspirations of the society, supporting self-governance for local communities to be able to govern themselves with no or little interference from government. This process is still ongoing, requiring a great effort from academics and practitioners to understand different dynamics. This paper copes with a case of organizational change “triggered” by a process of digital transformation. We are specifically engaged in the change management of INPS concerning the potential development of a technological application for managing disputes under the jurisdiction of the Court of Auditors, with the objective of monitoring the recovery of state damages caused by the fraudulent actions of public employees.
In this setting, the focus is on the analysis of the reengineered business process in the effort to analyse jointly the digital transformation project and the organizational change. The paper may be located within emergent digital transformation literature.

This paper explores the concept of knowledge ecosystem created by Treedom, a pioneering B-Lab certified startup at the intersection of technology and environmental conservation. This research aims to provide a comprehensive understanding of how organizational dimensions play a role in a knowledge ecosystem settings where multiple logics coexist. In particular, we adopt the experience of a consultancy project carried out by ALTIS Advisory , a consultancy spin-off of Università Cattolica del Sacro Cuore devoted to promoting sustainability in established organizations and new entrepreneurial initiatives. This empirical study was based on a qualitative investigation. We carried out the analysis iteratively using a semi-grounded approach, and our data informed the selection of theories. Three data collection techniques were used: documentary analysis, participant observation and semi-structured interviews (one of the authors was part of the consultancy team during the project). The combination of social purpose and commercial strength equips Treedom to sustain, scale, and amplify the benefits generated throughout the ecosystem. Within this ecosystem, knowledge operates as a strategic asset that underpins the shared objectives of Treedom and its stakeholders. The social‑impact assessment carried out by ALTIS Advisory thus became a collective learning exercise, enabling every actor to acquire deeper insight into their own capabilities, those of their counterparts, and the project as a whole.

Over time, the evolution of digital technologies has enabled a new perspective on knowledge as a collaborative and dynamic process, shaped through interactions among multiple stakeholders. These technologies facilitate real-time information sharing and support continuous knowledge creation and management in flexible, adaptive ways. Organizations increasingly rely on these digital tools to harness internal and external collective intelligence, fostering innovative knowledge practices. Particularly in project-oriented environments—characterized by complexity and constant change—digital platforms are essential to centralize information, promote collaboration, and enhance knowledge traceability and adaptability.
In this context, emerging platforms such as the metaverse reshape how work and collaboration occur. No longer limited to science fiction, the metaverse now provides immersive, interactive, and collaborative environments enabled by Virtual, Augmented, and Mixed Reality technologies. These digital spaces allow human resources to engage in work, learning, and social interaction in new ways. The metaverse, therefore, offers a promising environment for supporting knowledge management (KM) processes across organizations.
Despite growing interest in virtual environments for learning and communication, the implications of the metaverse for knowledge management remain underexplored. In particular, little attention has been given to how the metaverse affects the various dimensions of knowledge—from tacit to explicit, individual to collective, and from creation to application—especially in project-driven settings. This study addresses this gap by investigating the metaverse as a platform for KM, with a focus on how it facilitates the conversion of knowledge across these dimensions.
Using a qualitative methodology based on multiple case studies, the research examines how immersive virtual environments can enhance knowledge sharing, visualization, and decision-making in complex projects. Findings reveal that the metaverse enables the transition between tacit and explicit knowledge, supports real-time collaboration across distributed teams, and creates value at both individual and organizational levels. Features such as virtual prototyping, scenario planning, and real-time interaction with data and workflows improve communication, alignment, and coordination in project teams.
In conclusion, the metaverse offers a transformative opportunity to address the challenges of knowledge management in dynamic, project-based environments. This study provides insights that could be relevant to both scholars and practitioners in the fields of Human Resource Management and Information Technology.

Healthcare today more than ever is supported by technological innovation that has allowed the improvement of the standards of diagnosis and treatment but also the enhancement of the collection of anamnestic information and monitoring of the treatment path. The new digital health technologies (DHT) and the use of algorithms based on machine learning and artificial intelligence have improved the integration and analysis of data from different sources, becoming a driving force for network collaborations both for research purposes and for healthcare. Moreover, the innovative solutions resulting from the integration between technology and healthcare, aiming at strengthening health services efficiency and patient outcomes, involve the need to integrate complex technologies and specific skills in the design of instruments, devices, specialized health care services. In this context, the theme of co-designing healthcare services comes into play, and it involves a due analysis of the challenges to be faced in implementing co-design architecture.
The aim of the paper is to identify and analyse the coverage of the body of literature on the implication of DHT implementation in the co-design of healthcare services and give a trustworthy indication of the bulk of studies available as well as an overview of the key issues analysed. A scoping review is carried out to map the research done in this field and to identify critical themes and challenges.
The results of this work allow us to outline a cognitive map of the “areas of involvement” and to understand which challenges have already been faced and which are rising. Several interesting theoretical and managerial implications emerge.

This paper explores the development and implementation of a digital knowledge-action platform designed to embed and translate the SoPHIA (Social Platform for Holistic Impact Assessment) method—a multidimensional framework for evaluating cultural heritage initiatives—into an accessible and participatory digital environment. Building on the Horizon 2020-funded SoPHIA project, the SoPHIA for CHANGES initiative, led by Roma Tre University and funded under Italy’s Next Generation EU program, sought to address this gap by creating a digital platform grounded in the participatory ethos of the original SoPHIA method. The research employed a Participatory Action Research (PAR) approach, involving iterative cycles of collaboration between academic researchers, digital developers, and cultural heritage stakeholders. This methodology ensured that the platform was not merely a technical artefact but a co-created tool for reflexive learning, action, and knowledge transfer.
The research makes several significant contributions. Firstly, it enhances our understanding of how digital platforms function as socio-technical infrastructures for knowledge creation and dissemination within the cultural sector. It highlights a shift from static information repositories to dynamic, reflexive systems that actively engage and empower users. Secondly, the study introduces a process model for designing a comprehensive heritage impact assessment platform grounded in participatory knowledge management. This model offers valuable guidance for developing future knowledge-action platforms in cultural management and other complex, interdisciplinary domains. Ultimately, this project sheds light on how cultural heritage impact assessment can be disseminated and sustained through digital means without losing the critical reflexivity and human judgment that define meaningful heritage work. It demonstrates that digitalization, when rooted in participatory principles, can enhance—not replace—human creativity, sense-making, and collective action.

This study explores how Artificial Intelligence is reshaping managerial competencies in modern organizations. While much of the literature emphasizes technological capabilities, we adopt a human-centric perspective to map the evolving competencies, skills, knowledge, and responsibilities that managers must acquire to navigate the evolving technological landscape. The analysis is grounded in a Systematic Literature Review conducted in accordance with the PRISMA framework. A total of 92 peer-reviewed academic articles were examined using a hybrid methodology that combines Large Language Model-assisted content extraction with structured human coding. The resulting taxonomy groups these competencies into four macro-areas: (1) strategic and decision-making competencies, (2) technical and analytical skills, (3) ethical and legal regulatory knowledge, and (4) leadership and change management. Each category includes specific sub-competencies reflecting the complex, interdisciplinary nature of AI adoption. The findings reveal a predominance of studies focused on tertiary industries and a strong reliance on qualitative research designs. A fit score was applied to assess each contribution’s alignment with the review’s objectives. By mapping the evolving skillset required for AI readiness, the study offers both theoretical insights and practical orientation for managers, educators, and policymakers seeking to navigate digital transformation responsibly and effectively.

The increasing integration of artificial intelligence (AI) into decision-making processes represents a fundamental lever for competitive positioning, especially for start-ups operating in innovative ecosystems such as Rome Technopole (RT). This paper analyzes whether and how RT startups adopt AI to support decision-making and knowledge management processes, basing these processes on ethical and human-centric principles.
After the preliminary reconstruction of the conceptual framework, using a qualitative-quantitative approach based on semi-structured interviews and questionnaires aimed at innovative startups and SMEs, the study shows that AI solutions are used for big data analysis, simulation of future scenarios and optimization of business strategies. Technologies, in fact, enhance the effectiveness of decisions through predictive analysis and automation, without ever replacing the critical contribution of the human element, which remains guaranteed through feedback, periodic meetings and mentorship sessions. At the same time, transparent and secure data management is essential to establish a climate of trust with stakeholders.
In addition, the adoption of AI is integrated with economic, social, and environmental sustainability criteria, directing innovation towards ethical and responsible business models, in line with the 17 Sustainable Development Goals and Environmental, Social, and Governance (ESG) standards.
The results indicate that, while still in its infancy, the use of AI in RT startups offers significant opportunities for growth and competitiveness, if the integration between advanced technology and human resources is strengthened.

The rise of Artificial Intelligence (AI) in the visual arts represents a significant shift in contemporary creative practices, prompting urgent questions about the nature of art, the role of the artist, and the boundaries of human-machine collaboration (Cetinic & She, 2023; Rooij, 2024). This paper investigates how generative AI technologies are reshaping the visual arts, with a particular focus on their influence on the creative process (Miller 2019), the attribution of authorship, and audience perception.
Adopting a thematic literature review methodology within an interdisciplinary framework—spanning art theory, media studies, and cognitive science—the research synthesizes key developments from 1975 to 2024. The literature covers a temporal span from the earliest seminal explorations of computer-aided art (Molnar, 1975) to the most recent advances in generative AI technologies and critical discourse (Chiodo, 2024; Messer, 2024). This diachronic range enables a comprehensive understanding of both the historical evolution and the contemporary debates surrounding AI’s role in the visual arts.
This research identifies and analyses three core conceptual themes emerging in the discourse. First, the ontology of AI-generated art interrogates the core concepts that address the definition of art, AI, and the links between them. Following a logical progression, the second theme that emerged presents the critical debates revolving around three central issues: authorship, originality, and intentionality (Floridi, 2021; Hertzmann, 2018; Chiodo, 2024). Finally, the review addresses the issue of audience perception, with particular attention to the cognitive bias that emerges when individuals evaluate artworks produced by AI (de Roji, 2024). This final theme is crucial for understanding not only how AI artworks are judged aesthetically but also how deep-rooted expectations about human creativity influence the reception of machine-generated art.
By drawing a historical parallel to the initial resistance faced by photography in the 19th century (Hertzmann, 2001), the paper contextualizes the current scepticism toward AI art as part of a broader cultural negotiation of new media. The findings suggest that AI is not displacing human creativity but rather expanding its modalities—offering novel pathways for artistic exploration and expression.
This study contributes to the academic debate by moving beyond polarized narratives of celebration or rejection, and instead, provides a nuanced, evidence-based reflection on the evolving dynamics between artists, machines, and audiences.

To celebrate the anniversary of the Dayton agreements after the Sarajevo war (1992-1995), a phygital exhibition Sarajevo, from war to peace thirty years later is going to be launched between Bari and Sarajevo, inspired by the Ars Aevi project and celebrated through words and experiences of many protagonists, from local to Italian authorities, from children of yesterday to the adults of today.
Born as a political and peaceful artistic action in response to the war, conceived and realized by Enver ‘Enjo’ Hadžiomerspahić, the project started in 1992 from the Michelangelo Pistoletto’s donation of his artwork Porta allo Specchio. Become one of the greatest contemporary art collections, Ars Aevi will find its definitive location in the new Museum of Contemporary Art designed by Renzo Piano in 2005, donated to Sarajevo and just presented according to its executive design. The collection can be known and enjoyed thanks to the website, the online catalogue and a virtual exhibition, a sort of demo preview of the new Sarajevo Museum.
The project of the Sarajevo, from war to peace thirty years later exhibition, realized through the collaboration of the University of Bari “Aldo Moro”, many Italian and Bosnian institutions and the partnership of the Ars Aevi Museum, aims to promote intercultural dialogue and peace, through an exhibition combining stories and contents, in a physical, digital, interactive and immersive way, by using different digital tools, such as an interactive ‘augmented’ catalogue and a VR exhibition on ArtSteps.