Artificial Intelligence (AI) stands out as a revolutionary force driving profound shifts in strategic decision-making processes. This paper embarks on a comprehensive exploration of the transformative role of AI in strategic management. Beginning with an analysis of AI’s evolution, we delve into its integration into business strategy formulation, juxtaposing traditional strategic paradigms with AI-infused approaches. A sector-specific investigation highlights industries significantly altered by AI, underscoring its pervasive influence across diverse sectors. We also explore real-world scenarios, recording AI-enhanced success stories and revealing the inherent challenges businesses face during AI’s integration. To effectively navigate this terrain, it’s crucial for businesses to ensure transparency and explainability in AI systems (Castelvecchi, 2016) [9], maintain rigorous audit trails (Brundage et al., 2018) [4], actively avoid biases (Buolamwini & Gebru, 2018) [7], and promote inclusive development (Knight, 2017) [18]; (O’Neil, 2017) [24]; (West, 2018) [23]; (Wirtz, Weyerer, & Geyer, 2019) [14]. Understanding AI’s limitations (Brynjolfsson & McAfee, 2014) [5], championing continuous learning (Davenport & Ronanki, 2018) [11], adopting a collaborative approach (Agrawal, Gans, & Goldfarb, 2022) [1], prioritizing security (Zhu & Liu, 2018) [12], and engaging stakeholders are key in AI-driven strategic formulation (Fountaine, McCarthy, & Saleh, 2019) [13]. Beyond its practical implications, AI’s strategic dominance raises complex ethical dilemmas. This research clarifies the multifaceted ethical challenges posed by AI-driven decision-making, with a focus on biases inherent to algorithmic predictions and regulatory challenges. By integrating AI’s evolutionary path, tangible business impacts, ethical considerations, and best practices, this paper offers an enlightening journey through the AI-augmented strategic landscapes of contemporary businesses.

This research explores the potential of conversational artificial intelligence (AI) as a tool to support children and young adults with Attention Deficit Hyperactivity Disorder (ADHD), compulsive disorders, and other mental health challenges, particularly in educational settings. Recognizing the unique difficulties this demographic faces, the study aims to investigate how conversational AI can provide structured daily assistance, improve mental well-being, and enhance academic performance. The research draws on various interdisciplinary studies, including those focused on empathy-driven AI, AI in psychiatry, and chatbots in mental health. Through a systematic analysis of existing literature and case studies, this research endeavors to provide a comprehensive understanding of the effectiveness of conversational AI in supporting youth with ADHD and related disorders, offering insights into future developments in this field.

This review explores the integration of conversational AI, particularly chatbots like ChatGPT, in problem-based teaching methodologies within diverse educational settings. The rapid advancement in AI technology offers unique opportunities for addressing the challenges faced by students from varied cultural and linguistic backgrounds. By focusing on problem-based learning (PBL) strategies enhanced by conversational AI, this paper examines how AI tools can facilitate personalized learning experiences, promote cultural understanding, and overcome language barriers. The review synthesizes current research findings, highlighting the effectiveness of AI in creating inclusive and adaptive learning environments. Special attention is given to the potential of these technologies in fostering critical thinking, collaboration, and problem-solving skills among students with diverse needs. The paper also addresses the ethical considerations and challenges in implementing AI in educational contexts.

This study aims to explore the efficacy of conversational AI technologies in assisting adults living with ADHD, diagnosed or undiagnosed, in coping with daily challenges and improving social skills. While ADHD is often associated with youth, many adults also struggle with its symptoms, which can include disorganization, impulsivity, and difficulties in maintaining relationships. This research will investigate how AI chatbots, through personalized interactions and behavioral modification strategies, can aid in managing these symptoms. The study will also consider factors to increase accessibility and engagement with these AI tools among adults with ADHD, addressing potential stigmas and technological barriers. Through a systematic review of current literature and case studies, this research aims to provide insights into the development of AI tools tailored for adult ADHD support, contributing to their social and functional well-being.

In the era of rapid digital transformation, the integration of Federated Learning (FL) with Edge Computing in 5G networks emerges as a pivotal innovation, offering a new paradigm for data processing and intelligence distribution. This paper delves into the core concepts of FL and its symbiotic relationship with Edge Computing within 5G infrastructures. We examine the unique challenges such as data privacy, computational resource management, and network reliability, alongside the dynamic opportunities that this integration presents. Through a comprehensive review of current research and developments, this study not only highlights the technological advancements but also sheds light on the socioeconomic impacts of FL in 5G Edge Computing. By offering perspectives from both industry and academia, the paper aims to chart a course for future research and implementation strategies, paving the way for a more connected and intelligent world.

The accelerating integration of Artificial Intelligence (AI) within business operations has culminated in a paradigmatic shift, ushering in new horizons of efficiency and strategic advantage. This paper delves deeply into three pivotal domains where AI is orchestrating operational transformation. Firstly, we explore the realm of Supply Chain Management, where AI’s predictive capabilities are enhancing strategies from inventory management to last-mile logistics optimization, as evidenced by narratives from Agrawal, Gans, & Goldfarb (2022) [1] and Köhler et al. (2020) [22]. Through illuminative case studies, we showcase transformative narratives where AI has been the anchor in renovating supply chain dynamics. Transitioning to the critical arena of fraud detection, the paper highlights the evolution and efficacy of AI-empowered algorithms. We spotlight AI’s indispensable role in real-time monitoring, underscored by the study from Bao, Hilary, & Ke (2021) [4]  and Wang et al. (2014) [2], and its promise to reduce fraudulent activities. Lastly, we probe the synergy between humans and AI, emphasizing the transformative potential of their collaboration in sectors like manufacturing, as documented by Davenport & Ronanki (2018) [10] and Bahrin et al. (2016) [3]. This collaboration is not only enhancing operational efficiencies but also redefining roles and decision-making processes, as elaborated upon by LaValle et al. (2020) [23] and Leitão, Saleiro, & Figueiredo (2022) [24]. By encompassing these transformative domains, this paper provides a panoramic view of AI's indelible imprint on modern business operations, emphasizing the need for organizations to embrace, adapt, and strategically integrate AI to harness its full potential.