Conference Agenda

Digital transformation has become crucial for contemporary business competitiveness. This study focuses on the digital transformation journey of a Brazilian agribusiness company, using the Management Excellence Model (MEG). The MEG assesses eight key criteria, including systemic thinking, organizational learning, and transformative leadership. The digital transformation project comprises five stages: initial diagnosis, definition of objectives and indicators, implementation of digital transformation, assessment of digital maturity, and continuous improvement. The first two stages have already been completed, resulting in an average of 48.5% in the MEG criteria, indicating an intermediate level of management maturity but with predominantly analog processes. Key sectors for initiating digitization have been identified, with goals and indicators established. Thus, the MEG serves as a fundamental tool for guiding and measuring the company's performance towards success in the digital age, directing it towards achieving excellence in management in an increasingly digitized and dynamic business environment.

According to a 2024 report from the World Economic Forum, the risk of Generative Artificial Intelligence (AI) is 53%, surpassing the risks from cyberattacks (39%), cost of living (42%), and political polarization (46%). Specific to this risk is its impact on the spread of misinformation and disinformation, which can increase public health issues, violence, and undermine trust. Hence, we empirically examine the impact of Generative AI on the spread of misinformation and disinformation. We use social media data from various platforms from the onset of OpenAI’s ChatGPT until December 2023. Based on the results of the study, we propose an AI Ethics awareness program. The notion is that in the same way that employees are encouraged to participate in cybersecurity awareness training, AI Ethics awareness training will have a similar effect in educating individuals on how to detect and mitigate risks.

It is important that faculty equip students to responsibly utilize generative artificial intelligence (AI). In three 2023 MBA course sections, students submitted a 3000-4000 word paper analyzing the leadership style of a leader of their choosing, with instructions that AI should not be used. Following submission, students were given the next assignment requiring a paper on the same topic using AI. These successive assignments ensured that students were informed about the topic and thus able to critically evaluate the AI-generated output. Two-thirds of students had no prior experience with AI. Student survey responses indicated that 93% felt this assignment changed their understanding of AI, and how they might use AI in their profession and their graduate studies. Students were impressed with the content generated by AI, but noted lack of a clear voice, errors in content, redundancies, and deficient citations and references. Subsequent class discussion generated additional reflection.

This paper examines recent publications investigating various artificial intelligence (AI) topics in the Western Balkans region. The study uses the Latent Dirichlet Allocation (LDA) topic modeling technique to extract topics from the corpus of about 92 articles downloaded from various online sources. The preliminary analysis reveals several major topics influencing the development of AI in the region. The study calculates the frequency of these topics throughout the articles. Then, it uses the topics as input for further exploratory and confirmatory factor analysis. As a result, the paper synthesizes four overarching themes that characterize the nature of AI development in the Western Balkans. Policymakers in the region can use the findings to tailor strategies that bolster AI innovation; universities can leverage this knowledge to align their AI curricula with emerging AI trends, and organizations and practitioners can better understand the market dynamics and opportunities for commercial AI applications.