The integration of artificial intelligence (AI) in business processes has revolutionized many industries by automating tasks, improving decision-making processes, and enhancing customer experiences. This review article examines the impact of AI in business areas, including its applications, challenges, limitations, current trends, and future work. The article begins with defining the importance of AI in business, followed by an overview of its applications in various sectors, such as customer service, marketing, finance, healthcare, manufacturing, logistics, and human resources. The advantages and benefits of AI implementation are explored, along with the examples of successful AI implementation and changes in business processes. The challenges and limitations of AI technology, such as ethical concerns, data privacy and security issues, technical expertise and knowledge, and high implementation costs, are explained. Current trends in AI integration, such as the integration of AI with other technologies, the growing demand for AI skills, and the development of more advanced and sophisticated AI algorithms, are presented. The review concludes with recommendations and predictions for the future of AI in business areas and proposes strategies for successful AI implementation while reflecting on ethical and social considerations. Our analysis in this article points to various open research areas and improves the understanding of AI in the business field.

This research used a quantitative approach to explore the impact of social media marketing on consumer purchase intention. Due to the technological development of social media platforms in the recent past, as well as the addition of several functionalities to these platforms, the way that consumers and firms engage has changed dramatically in the current competitive market. To understand the influence of social media marketing and the important role of influencer marketing in consumer purchase intention, a cross-sectional analysis was performed. Data from 210 participants were used for this study. Furthermore, a comprehensive and critical analysis of the existing research on social media marketing was also undertaken. The results reveal that there is a significant positive relationship between social media marketing and purchase intention.

Generative Artificial Intelligence (GenAI) is rapidly transforming the beverage industry by fundamentally reshaping innovation pipelines, optimizing product development processes, and redefining consumer engagement strategies. This comprehensive review synthesizes evidence from 40 academic and industry studies to systematically map GenAI’s current applications, critically evaluate prevalent implementation challenges, and identify future opportunities for growth. Our key findings reveal that advanced GenAI models, including transformer architectures, generative adversarial networks (GANs), and multimodal AI systems, are driving significant advancements across three core areas: (1) Product Innovation, where AI accelerates processes such as flavor profiling, recipe optimization, and virtual prototyping, exemplified by AI-designed non-alcoholic spirits and precision-engineered reduced-sugar formulations; (2) Operational Efficiency, demonstrated through IoT-integrated AI enhancing quality control, facilitating predictive maintenance, and reducing waste in complex processes like brewing and fermentation; and (3) Marketing Personalization, leveraging tools like ChatGPT and DALL·E for dynamic content generation, granular sentiment analysis, and the execution of hyper-targeted campaigns.

Cross-cultural work on food choice has expanded considerably over the past few decades; however, studies that compare East Asian student groups are still relatively low. This study compared the food choice motivations of Chinese (N = 105) and Korean (N = 92) university students living in Korea by using the Food Choice Questionnaire (FCQ). Data were analyzed with a 2 (culture: Chinese × Korean) × 2 (sex: male × female) factorial ANOVA. The result shows a significant difference between Korean students and Chinese students in terms of health as one of the main effects of culture, where Korean students rated it higher than their Chinese peers (Mean difference = 0.45; F(1, 193) = 28.20, p < .001, partial η² = .13, a large effect). Sex demonstrated significant main effects across six distinct factors, specifically, natural content, price, ethical concern, religion, familiarity, and weight control with men consistently exhibiting higher scores than women in each instance. Mood, convenience, and sensory appeal each showed a significant culture-by-sex interaction. Collectively, these findings appear to suggest a discernible role for culture and gender as joint determinants in the approach to dietary selections among university students within this East Asian context.

This research paper used a mixed method approach to provide a new perspective on the impact of social media marketing and consumer purchase intention. Due to the technological development and addition of several functionalities to the social media platform in the recent past, the way consumers and firms engage has changed dramatically in this current competitive market. Earlier several papers used quantitative methods to understand the effect of social media marketing on consumer purchase intention. But huge criticism had been voiced against heavily used quantitative methods. Hence to encounter this criticism and better understand social media marketing as a tool to lure consumers both empirical study as well as a systematic literature review method were employed. At the first section of the research a systematic literature review method had been pursued followed by quantitative method to verify our finding using frequency distribution, factor analysis and Pearson Correlation test. The research results from this mixed method reveal that there is a significant positive relationship between social media marketing and purchase intention.