In recent years, technology has a deep effect on the process and human resources practices. The purpose of the research document is to represent a review of the role of technology in human resources management. How technology plays a crucial role in human resources management. The need for technology arises the due number of limitation associated with the traditional method of human resources management, such as a) using a form of communication b) The human resources system is impersonal and liabilities c) does not always allow interpersonal interaction d) Often creates artificial distance The use of technology has caused a dramatic change in human resources management. How technology helps through automatic repetitive tasks, which allows decision making promoted by data through employee data analysis, simplifies the recruitment process, employee performance management and facilitates communication and collaboration. Ultimately, allowing human resources professionals to focus on a more strategic initiative and improve the general efficiency of the workforce. Artificial intelligence is being used to satisfy the need for employees and the application through the evolution of the talent supply applicant. The available tools and technologies for human resources can eliminate the transition and tactic load of human resources managers.

With the rise of artificial intelligence (AI), chatbots and AI-driven customer service solutions have become prevalent in various industries. This research paper compares the effectiveness of AI-driven customer service with traditional human customer care. The study examines response times, accuracy, customer satisfaction, and cost efficiency to determine which approach provides the best overall service. The findings highlight the strengths and weaknesses of each method and provide insights into the future of customer service.

With the rise of artificial intelligence (AI), chatbots and AI-driven customer service solutions have become prevalent in various industries. This research paper compares the effectiveness of AI-driven customer service with traditional human customer care. The study examines response times, accuracy, customer satisfaction, and cost efficiency to determine which approach provides the best overall service. The findings highlight the strengths and weaknesses of each method and provide insights into the future of customer service. Additionally, the paper explores the impact of Natural Language Processing (NLP), Machine Learning (ML), and Sentiment Analysis in enhancing chatbot capabilities.

Changes in education require new ideas and creativity in how we learn. With the growth of Artificial Intelligence (AI) in education, it helps with everyday tasks like teaching and learning. The goal of this study is to explore how AI is used in education, especially in the classroom. This research is based on library studies. The results show that AI is being used in various educational technologies, such as: Virtual Mentors Voice Assistants, like Google Assistant, Siri, and Cortana Smart Content Presentation Translators Personalized Learning, such as Ruangguru Educational Games Intelligent Tutoring Systems (ITS) or Intelligent Computer-Aided Instruction (ICAI). AI is about creating machines that think like humans. In the future, many tasks teachers do, such as correcting work, taking attendance, giving tests, explaining lessons, and making reports, could be done by technology. This would give teachers more time to focus on creative and meaningful work that requires human intelligence, like building character and quality in students. AI works in a systematic way, following human commands, while teachers bring new knowledge through their own thinking. So, even though AI is powerful, the intelligence of teachers is unmatched. AI is a result of human creativity and will never fully replace the role of teachers.

Artificial Intelligence (AI) is reshaping education by introducing innovative methodologies that enhance both teaching and learning. In language education, AI-driven technologies such as intelligent tutoring systems, machine translation, speech recognition, personalized learning, and chatbots have transformed traditional approaches. This article examines the impact of AI on language instruction, highlighting its advantages, challenges, and future potential. By integrating AI, language learning becomes more efficient, engaging, and tailored to individual needs. However, ethical and pedagogical considerations must be carefully addressed to ensure effective implementation.

Personal care products are directly applied to the surface of the human body frequently and relatively in large quantities which may affect the skin unpleasantly. Fragrant components are widely used in skincare products for their sensory appeal, but they are also a common cause of skin irritation and allergic reactions. This study uses Bioinformatic tools such as docking and prediction methods such as QSAR (Quantitative Structure Activity Relationship) to examine the molecular and chemical activity of fragrant compounds like linalool, eugenol, citronellol, etc with Epidermal Growth Factor (EGF) & Cytokines present in the skin that can contribute to skin sensitivity. This modelling methodology has been specifically created to maintain quality in cruelty free products.

Artificial intelligence’s application in education is radically changing the landscape of learning, research, and administrative functions. This research holds examination of historical evolution, present applications, and future course of AI in education while focusing mostly on students' and teachers' perceptions. In a systematic questionnaire-based approach, the research attempted to examine AI utility, perceptions regarding the implementation, ethical challenges, and the felt impact on academic productivity. This study indicated the requirement of a strong support for AI literacy in higher education to prepare students and teachers for AI-ready workplace.

This research paper is being dealt with the growing or developing quickly role of Artificial Intelligence (AI) as a significant changer for economic growth in India, specifically analysing its impact on Gross Domestic Product (GDP), productivity, and the critical education sector. to make beneficial data from the National Statistical Office (NSO), this study quantifies Artificial intelligence's contribution to crucial aspects relates to economic indicators of Indian economy and make adequate study of trans-formative potential across diverted industries. We study how Artificial Intelligence applications are being utilized to optimize and to make ideal resource allocation, automate complex tasks, and enhance decision-making processes across various sectors. This all study is examined with the proper implementation of AI powered analytical findings for forecasting to maintain manufacturing sector , AI-driven fraud or malpractices detection in financial services, and AI-enhanced supply chain management in logistics. These applications lead to significant improvements in operational efficiency, cost reduction, and the acceleration of innovation cycles. Streamline processes, and drive innovation, thereby boosting productivity. A significant focus is placed on the education sector, a cornerstone of India's demographic dividend. We investigate the implementation of AI-driven tools in Indian educational institutions, including personalized learning platforms, intelligent tutoring systems, and automated administrative processes. The analysis shows in assessment how these technologies are improving learning outcomes, expanding access to quality education, and addressing the challenges of a adequate and diverted educational scenario. Understanding upon case studies from institutions like IITs, IIMs, and emerging Ed-Tech start-ups, we illustrate the practical applications of AI in enhancing pedagogical practices and student engagement. Further in next study this paper analyses the chronological arrangement of AI initiatives with national strategies such as "Digital India" and the "National Education Policy (NEP) 2020," which emphasize technology integration for inclusive and equitable growth. By examining the correlation between AI adoption and GDP growth using NSO data, we provide empirical evidence of AI's economic contribution. The study also exhibits SWOT ANALYSIS, it is associated with scaling adoption of artificial intelligence. it is on large scale in all segmented beneficiaries in education , including infrastructure development, skill gaps, and data privacy concerns. Research is aims to provide a comprehensive understanding of AI’s trans-formative potential in the Indian context, contributing to informed policy-making and fostering sustainable economic development through strategic technological advanced development.

Artificial Intelligence (AI) has vast potential in marketing. It aids in proliferating information and data sources, improving software's data management capabilities, and designing intricate and advanced algorithms. AI is changing the way brands and users interact with one another. The application of this technology is highly dependent on the nature of the website and the type of business. Marketers can now focus more on the customer and meet their needs in real time. By using AI, they can quickly determine what content to target customers and which channel to employ at what moment, thanks to the data collected and generated by its algorithms. Users feel at ease and are more inclined to buy what is offered when AI is used to personalise their experiences. AI tools can also be used to analyse the performance of a competitor's campaigns and reveal their customers' expectations. Machine Learning (ML) is a subset of AI that allows computers to analyse and interpret data without being explicitly programmed. Furthermore, ML assists humans in solving problems efficiently. The algorithm learns and improves performance and accuracy as more data is fed into the algorithm. For this research, relevant articles on AI in marketing are identified from Scopus, Google scholar, ResearchGate and other platforms. Then these articles were read, and the theme of the paper was developed. This paper attempts to review the role of AI in marketing. The specific applications of AI in various marketing segments and their transformations for marketing sectors are examined. Finally, critical applications of AI for marketing are recognised and analysed.

Virtual reality (VR) has become a game-changing technology in personalised marketing, transforming how companies interact with their target audience. This study investigates how virtual reality (VR) can be used to develop highly customised marketing strategies, improve customer satisfaction, and influence purchasing decisions. VR gives marketers the ability to customise content according to user demographics, tastes, and behaviours by providing immersive and interactive worlds. Virtual showrooms, product trials, and immersive storytelling are examples of personalised virtual reality experiences that let customers interact closely with brands, increasing brand loyalty and emotional connection. This study looks at how consumer perception, decision-making, and satisfaction are affected by VR-driven personalised marketing. It emphasises important technologies that improve VR personalisation, like machine learning and AI-driven analytics. The report also looks into how VR-based customisation is changing marketing tactics in the fashion, automobile, real estate, and e-commerce industries. Despite the many advantages of virtual reality, issues such high implementation costs, technological obstacles, and data protection concerns still exist. possible answers to these problems and the possible applications of virtual reality in marketing are covered in the study. Research indicates that VR-powered personalisation boosts conversion rates, brand memory, and customer engagement. Understanding VR's function in personalisation is essential for gaining a competitive edge as companies continue to use technology into marketing initiatives. In the end, this study reshapes consumer-brand interactions in the digital age by offering insights to researchers, companies, and marketers on how to use VR technology to create engaging and customised marketing strategies.

This research paper explores the potential of Artificial Intelligence (AI) in digitizing and preserving tribal heritage and culture, with a specific focus on Warli art and painting. Warli art, an ancient tribal art form from India, is a vital part of the cultural identity of the Warli community. However, this art form faces threats due to industrialization, urbanization, modernization, and lack of documentations. This study employs AI-powered techniques, including image processing, machine learning, and computer vision, to digitize and analyse Warli art and painting. The aim of this research is to develop a digital repository of Warli art, create a classification system for Warli art motifs, and design a predictive model for the conservation of art. The findings of this study demonstrate the effectiveness of AI in preserving tribal heritage and culture. The digital repository created can serve as a valuable resource for art historians, researchers, and for the Warli community to preserve their original culture to transform for the next generation. The classification system and predictive model can aid in art conservation and restoration efforts. The findings of this study demonstrate the effectiveness of AI in preserving tribal heritage and culture.

Artificial Intelligence (AI) is revolutionizing numerous sectors, and one area where its impact is profoundly felt is in music education. This paper explores the role of AI in music education, highlighting its potential to enhance learning, improve accessibility, and personalize music instruction. The paper discusses various applications of AI, including intelligent tutoring systems, AI-driven music composition tools, music theory analysis software, and AI-based performance feedback systems. Furthermore, the paper examines the benefits, challenges, and ethical considerations of AI in music education. In doing so, it provides a comprehensive analysis of how AI is transforming music education and shaping the future of music learning.

Emergence of AI powered technologies has a huge impact on Code generation and debugging. This research paper gives an insight on Evolution of software engineering landscape due to AI-driven tools, such as code completion systems, bug detection frameworks, and refactoring engines. Through various case studies the paper gives an overview of evolving AI powered technologies which has been a milestone in code generation and debugging. This research has found Through various surveys how it has impacted code generation and debugging. The software development field is going through a change due to artificial intelligence (AI), especially in the domains of code emergence and debugging. The development of artificial intelligence ("AI") has shifted the way developers approach their work, improving efficiency, and may even be changing the course of programming itself in the future. This explores AI4s diverse role in mainstream software development. Artificial Intelligence (AI) is revolutionizing the software development landscape, particularly in the realms of code writing and debugging. As AI technologies continue to advance, they4re reshaping how developers approach their work, boosting productivity, and potentially altering the future of programming

AI is making noteworthy steps across various scientific disciplines. These advancements are paving the way for a greener chemical industry by aligning with the 12 principles of green chemistry. Green chemistry is branch of Chemistry which specially focused on designing chemical products and processes that reduce or eliminate the use of hazardous substances. AI is revolutionary tool for altering the approach scientists for research, more efficient, making discoveries faster, and often uncovering visions that were previously unbelievable.

This study glances at the Maharashtra State Archives in Mumbai's existing archive management and preservation situation as well as the possible ways artificial intelligence (AI) may improve archival procedures. According to the report, the Maharashtra State Archives in Mumbai have a wealth of historical documents, but they also suffer difficulties with accessibility, preservation, and discovery. The study offers suggestions for putting AI-powered solutions into practice and implies that archival management and preservation might be enhanced by utilizing AI-powered tools and procedures.

This study aims to provide an overview of the increasing role of artificial intelligence in accounting and auditing. This is supported by the expertise of the accounting and auditor profession which has evolved with advances in technology from the use of pencil and paper to calculators, and eventually spreadsheets and accounting software. This study uses a conceptual approach and semi-systematic review in analyzing published relevant articles. The main results of this study explain that interdisciplinary collaboration is a must with respect to research conducted in the field of AI in accounting and auditing. Wider application of AI in the accounting and auditing professions is expected to deliver greater efficiency, productivity and accuracy benefits while burdening with the challenges of income and wealth inequality, traditional job extinction and an unskilled workforce. Careful preparation is needed on the part of educators, regulators and professional bodies by overcoming paradigm shifts and preparing future students, policymakers and professionals to face the challenges of a world full of big data, blockchain technology, artificial intelligence to deliver success in facing the fourth industrial revolution.

The impact of AI in data science is beneficial through its sophisticated prediction and decision-making systems. These systems enable organizations to analyze vast amounts of data more reliably and faster, they may also deliver complex tasks with less human involvement. This lets firms spend more time on the strategic intent, while then letting automated algorithms handle any data-heavy processes. AI-based decision-making typically fuses multiple sources of information, ranging from structured data, such as databases, to terabytes of unstructured text. The organizations use the AI along with the analytic tools to generate the actionable results. Encoding- Models minimizes the amount of errors / faults of interpreting the data. Predictive Algorithms allow companies to get insights into consumer behavior, market changes, and interruptions in the supply chain. Socioeconomic factors influence AI adoption in forecasting and decision-making. Large firms with resources build sophisticated actual AI systems, small don't know much, so they iterate to make their models better. Businesses leverage AI models to increase customer personalization, optimize resources, and enhance service. AI-powered systems are also working towards waste reduction and process optimization across sectors. Similar economic considerations come into play when devising the role of AI within data science. Corporations pursuing aggressive growth heavily invest in artificial intelligence powered technologies, favoring implementations with a higher price tag, but smaller businesses are taking a more tempered approach with more cost-effective implementations. Data-based scalable solutions make AI-driven decision-making possible which enhances industry-wide competitiveness. Fast-paced, data-hungry worldOrganization is developing advance forecasting methodologies, optimize risk management and decision making to keep up에 with competition. 201 people from data science sector were surveyed to know different roles of AI in data science: predictive analysis and decision making and concludes that AI plays significant role in data science: predictive analysis and decision making.

Artificial Intelligence (AI) continues to make significant strides in various sectors, powering innovation across industries. The integration of AI into cloud computing and edge computing systems is shaping a new era of intelligent solutions. Cloud computing provides the computational power and storage necessary for AI applications, while edge computing facilitates real-time, low-latency data processing at the source of data generation. This research paper examines the symbiotic relationship between AI, cloud computing, and edge AI, explores emerging trends, and identifies challenges and future research directions in this interdisciplinary domain.

Maharashtra, a state in western India, boasts a rich cultural heritage, featuring numerous historical sites, monuments, and artifacts that date back centuries. However, many of these sites face threats from natural disasters, human activities, and climate change, which can result in irreversible damage or loss. This research paper explores how artificial intelligence (AI) can be applied to preserve and restore cultural heritage sites recognized by UNESCO in Maharashtra. This study focuses on digital preservation and restoration techniques, including 3D modeling, virtual reality, and machine learning. The researcher has conducted a comprehensive review of existing literature and case studies on AI-based preservation and restoration of cultural heritage sites in Maharashtra. The researcher also collaborated with experts from the field of archaeology; data collected through the questionnaire related to the preservation, restoration, and conservation of cultural heritage sites, and AI to gather insights on the potential and limitations of AI in preserving the chosen cultural heritage sites for the study. The researcher highlights the potential of AI in preserving and restoring cultural heritage sites in Maharashtra, including the Ajanta and Ellora caves, the Raigad Fort, Shaniwar Wada, Kanheri caves, and other heritage sites recognized by UNESCO. Out of these sites, the researcher has chosen Raigad Fort as a case study for this research. The researcher demonstrates how AI can be used to create detailed 3D models of the chosen sites, simulate restoration scenarios, and monitor the condition of the sites over time. This study contributes to the growing body of research on the application of AI in historical and cultural heritage preservation and provides insights for policy makers, conservators, and researchers working in this field.