NOLEGEIN- Journal of Management Information Systems

AI In Modern Marketing: Driving Personalization and Predictive Analytics

R. SIVALINGAM — Mon, 01 Sep 2025 00:00:00 +0000

Artificial intelligence (AI) is transforming the way businesses operate, bringing human-like intelligence to machines and unlocking new possibilities across industries. From voice and image recognition to advanced decision-making, machine learning, and semantic search, AI is reshaping the marketing landscape. This paper explores the current and future potential of AI in marketing, combining secondary research with real-world examples of early adopters. By examining how leading firms leverage AI-powered technologies, we aim to demonstrate how these innovations enhance marketing performance and drive business transformation. In addition to secondary research, this study also incorporates primary research to assess AI’s broader impact on marketing strategies and consumer engagement. Finally, we identify the industries that have been most receptive to AI-driven marketing and highlight sectors poised to benefit the most from these advancements. Through this exploration, we aim to provide marketers with valuable insights into how AI can be a game-changer in their field. Additionally, this paper highlights the industries that have shown the highest adoption of AI-driven marketing strategies and predicts the sectors likely to gain the most from these innovations in the near future as shown in fig 1. By integrating conceptual analysis with real-world data, the research provides meaningful insights for marketers, industry professionals, and academics aiming to comprehend AI’s transformative impact on modern marketing practices.
Figure 1 Human and AI collaboration symbolized through a handshake,

Consumer Experience in a Digital World: Transforming the Indian Future Market

Nitin Kumar Jain, Meghna Jain — Mon, 01 Sep 2025 00:00:00 +0000

India's digital revolution is reshaping its consumer landscape at an unprecedented pace. The digital revolution is reshaping consumer experiences at a fundamental level, especially in emerging economies like India. With rapid advancements in technology, including mobile connectivity, e-commerce, social media, and digital payment systems, Indian consumers are increasingly engaging with brands through digital platforms. This paper explores the evolving concept of consumer experience (CX) within the Indian digital context, focusing on its transformative impact on the future market. By integrating primary insights from surveys and secondary data on India's digital ecosystem, we examine the role of digital platforms, the benefits of optimized CX, and the unique challenges faced in this diverse market. market. We analyze how personalized experiences, regional language content, and seamless digital payments are crucial for building customer loyalty and driving market growth. The paper also examines how companies are utilizing technologies such as artificial intelligence and data analytics to improve customer satisfaction and strengthen brand loyalty. The findings highlight the challenges and opportunities faced by businesses in catering to a digitally empowered consumer base and offer strategic insights into the future of marketing in India’s digital landscape. The study concludes with recommendations for businesses to leverage digital CX for sustained success in the rapidly evolving Indian market.

Revolutionizing HR: How AI Is Transforming Human Resources and Powering Business Growth

Saswati Jena — Sat, 30 Aug 2025 00:00:00 +0000

Artificial Intelligence (AI) is an advanced technology is helpful to analyze, interpret, recommend, solve problem as well as make decision for various fields including Human Resource (HR). The study of HR focuses on the human resources that are present in a company. It justifies some responsibilities like recruitment, compensation benefits, performance appraisal, training and development, payroll scheme, employee relations etc. In today’s era. AI is serving an important role associated with HR practices to simplify data collection, recording keeping as well as processing the better outcomes. Research gap is lac of comprehensiveness on the impact of AI on the employee experience as well engagement in the field of HR. Its an ambiguity how AI-driven tools can be used to personalize employee development, address potential biases, and foster a positive workplace culture while still maintaining human interaction in critical situations. Aim of this paper is to find out how the AI is replacing the manual or traditional methods of HR works, which consequently helps to achieve success. Also, to extract the interdependency of today’s business requirement with smart work. This paper aims to investigate the ways in which AI is transforming and replacing conventional, manual HR processes, as well as to assess how this transformation impacts organizational success. It also seeks to examine the relationship between contemporary business demands and the integration of intelligent, AI-driven work practices. By highlighting the opportunities, challenges, and ethical implications of implementing AI in HR, the study intends to offer valuable insights to help organizations maintain an optimal balance between technological efficiency and human-centered management.

Enhancing Demand Forecasting in Supply Chains Through Deep Learning Techniques

Mohamed Safar Niyas S, Sipisuhav G, Rubesh K K, Ms.Akila K — Thu, 24 Jul 2025 00:00:00 +0000

Demand forecasting is critical in supply chain management, particularly for perishable goods, where inaccurate predictions can lead to significant financial losses and wastage. This paper explores the application of advanced deep learning techniques for food demand forecasting to optimize inventory management, reduce stockouts and overstock situations, and improve overall supply chain efficiency. By employing architectures such as LSTM, Bi-LSTM, Stacked-LSTM, and Transformer-based models, this research demonstrates the transformative potential of these methods in capturing complex temporal relationships, seasonal trends, and external factors influencing demand. Additionally, hybrid approaches integrating wavelet transforms and LSTM are examined to address unique challenges such as seasonality and multivariate dependencies. The outcomes highlight deep learning’s capacity to enhance decision-making, reduce costs, and increase customer satisfaction while paving the way for future innovations in supply chain forecasting. The results indicate that deep learning models greatly surpass conventional forecasting methods in terms of accuracy, flexibility, and scalability. These technological improvements contribute to more informed decision-making processes, decreased operational expenses, minimized food wastage, and higher levels of customer satisfaction. The study underscores the critical role of incorporating AI-based forecasting solutions into contemporary supply chain operations and highlights their potential to drive ongoing advancements and research in the field of predictive analytics.

Redefining Management through Digital Transformation: Strategies for Sustainable Innovation

Vaishnavi Jagdish Sahu — Wed, 23 Jul 2025 00:00:00 +0000

Management methods are changing significantly in the ever-changing digital world of today. This research investigates how businesses are redefining leadership and promoting sustainable innovation by utilizing digital technology. The study's three main goals are to determine the main forces behind sustainable innovation, comprehend how digital tools affect management procedures, and investigate the difficulties encountered during digital shifts. It is based on data gathered from 104 managers and executives. The results emphasize important success variables such organizational agility, digital capabilities, adaptable leadership, and successful technology integration. Interestingly, 78% of respondents saw a shift toward more flexible and cooperative team structures, and 72% of respondents reported better innovation outcomes when digital activities were in line with sustainability goals. Despite advancements, issues like cybersecurity and change aversion persist. Even with advancements, obstacles like change aversion and cybersecurity worries continue to be major obstacles. The paper suggests a useful framework—Digital-Enabled Sustainable Innovation—to address these issues, emphasizing the alignment of long-term resilience and innovation goals with digital transformation initiatives. These observations can help companies that want to successfully negotiate the challenges of the digital era. The Digital-Enabled Sustainable Innovation framework emphasizes the integration of long-term innovation and resilience planning with digital transformation strategies. It provides practical guidance for organizations aiming to succeed in the digital era while promoting sustainable development.

Effect of AI Application on Decision-Making Efficiency in Public Hospitals of Hawassa City, Ethiopia

Yared Alemu, Navneet Seth — Sat, 21 Jun 2025 00:00:00 +0000

The investigation analyzes the effects of AI applications on decision-making efficiency in public hospitals in Hawassa City, Ethiopia. Employing an explanatory design and quantitative analysis, the research collected data from 316 workers who were working in various departments of public hospitals through self-administered questionnaires. The data analyzed using multiple linear regression techniques to explore the relationship between AI applications and decision-making efficiency. The findings reveal that AI applications facilitate the dissemination of medical knowledge, clinical guidelines, and best practices among medical professionals, helping them enhance decision-making with greater accuracy, insight, and speed in treating patients. Additionally, the study shows that AI aids in automating and optimizing healthcare workflows, which reduces operational inefficiencies, minimizes human errors, and improves overall productivity. AI’s ability to monitor and manage healthcare operations in real-time allows for proactive interventions, anticipating potential issues before they escalate, and facilitating optimized resource allocation. The result also showed that the use of AI technologies in decision-making processes can improve healthcare service delivery, reduce wait times, enhance patient satisfaction, and support evidence-based practices. In conclusion, public hospitals may improve operational effectiveness and offer society better care by utilizing AI. In addition, incorporating AI into healthcare decision-making processes has demonstrated significant improvements in key performance metrics related to service delivery. These advancements include shorter patient wait times, enhanced efficiency in diagnostic and treatment procedures, higher levels of patient satisfaction, and a broader implementation of evidence-based medical practices within clinical environments. By leveraging AI, hospitals cultivate a data-centric culture in which decisions are grounded in analytical evidence rather than relying solely on intuition or prior experience.