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Artificial Intelligence and Analytics, AI and analytics or (AI&A) find diverse applications, spanning from online entertainment to healthcare, with this Special Issue aiming to explore their practical use in creating economic value, aiding decision-making, and improving organizational skills. The selected articles combine academic research and practical insights to offer valuable lessons for professionals seeking to leverage AI&A effectively.
AI and Analytics (AI&A) are driving transformative changes across diverse sectors, with a focus on achieving impactful outcomes such as resilient supply chains, improved customer experiences, and enhanced decision-making. The integration of AI&A is also seen in public services, B2B marketing practices, software development project management, and product innovation. Understanding how organizations leverage AI&A for actionable insights is crucial for maintaining a competitive edge. The impact of AI&A extends to reshaping work dynamics by augmenting and automating human activities, fostering human/AI partnerships. Successful integration requires organizational and cultural shifts, including reskilling and training. However, concerns about the ‘dark side’ of AI&A, encompassing issues like inequality and social exclusion, emphasize the need for ethical considerations and governance. Research in various sectors, including retail, banking, HR, advertising, health, start-ups, fintech, and manufacturing, is exploring theoretical aspects of AI&A. Yet, there is an emerging need for academic exploration of practitioners’ perspectives and experiences in adopting AI&A in their daily operations. The creation of research champion roles within organizations is proposed as a way to foster collaborative research between practitioners and academia. This special issue aims to contribute to practice by presenting empirical studies that highlight best practices and lessons learned in the application of AI&A across different contexts, such as telecom, high tech, and manufacturing. The studies will delve into the impact on organizational dynamics, customer relations, employee skills, management, regulatory frameworks, and lessons from actual AI&A implementation.
The Call for Papers for this issue, initiated in 2020, aimed to engage with AI and Analytics (AI&A) practitioners and researchers. All manuscripts underwent at least two rounds of peer review by domain experts, with Guest Editors actively involved in guiding authors. A total of 24 authors, hailing from diverse countries including China, France, Germany, Greece, Ireland, Italy, Kenya, South Africa, the UK, and the USA, contributed to accepted papers, half of whom are practitioners. The selected papers in the special issue, ‘Artificial Intelligence and Analytics in Practice,’ provide insights into the practical applications of AI&A in contemporary organizations, emphasizing value extraction, decision support, and organizational transformation.
The first manuscript, ‘Does AI control or support? Power shifts after AI system,’ examines two case studies, revealing unintended consequences such as reinforced managerial control and diminished employee autonomy due to AI implementation.
The second manuscript, ‘The impacts of artificial intelligence on managerial skills,’ adopts a mixed-methods approach, finding that AI enhances certain managerial skills while potentially replacing others. The study underscores the importance of cultivating both technical and non-technical managerial skills for effective AI integration.
The third manuscript, ‘The role of management in fostering analytics,’ explores how companies transition from intuition to analytics-driven decision-making. The authors identify six key factors, emphasizing the critical role of company culture in adopting analytics-driven decision support.
The fourth manuscript, ‘AI ethical biases: normative and information systems development conceptual framework,’ delves into the need for frameworks addressing AI biases, particularly in Information Systems Development. The authors propose a conceptual framework categorizing biases under data, method, and implementation scopes, offering practical solutions.
The fifth manuscript, ‘Decision support using AI: the data exploitation at telecoms in practice,’ shares the experience of OTE, Greece’s largest telecommunication provider, implementing various AI use cases. The authors discuss opportunities and challenges, presenting insights into the company’s digital transformation through AI-enabled Proof of Concepts.
The five selected manuscripts for the special issue offer diverse perspectives, empirical methods, and AI&A types. Together, they enhance our understanding of AI&A’s practical use, crucial for future IS research. The studies yield insights on incorporating AI&A in organizations, addressing ethical issues, navigating challenges, understanding power dynamics, and facilitating responsible management. Future research opportunities include developing frameworks and methodologies for AI&A aspects like ethics, biases, and transparency, exploring challenges across company sizes, and analyzing AI&A and control dynamics. Encouraging research in diverse industries beyond telecom, high tech, and manufacturing is also emphasized. The special issue aims to inspire researchers to delve deeper into AI and analytics in practice for further advancements in the field.
Source:
Anastasia Griva, Denis Dennehy, Ilias Pappas, Matti Mäntymäki, Nancy Pouloudi, Yogesh K Dwivedi & Bill Schmarzo (2023) Artificial intelligence and analytics in practice, Journal of Decision Systems, 32:3, 535-541, DOI: 10.1080/12460125.2022.2122218