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Journal articles on the topic 'AI-Powered Automation'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Pamadi, Vishesh Narendra, and Dr Sandeep Kumar. "AI Powered Automation Transforming Business Processes with Machine Learning." International Journal of Research in Humanities and Social Sciences 13, no. 3 (2025): 146–67. https://doi.org/10.63345/ijrhs.net.v13.i3.9.

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AI-powered automation, particularly through the integration of machine learning (ML), has significantly transformed business processes across various industries over the past decade. From 2015 to 2024, the adoption of AI technologies has evolved from automating simple, repetitive tasks to driving strategic decision-making and enhancing operational efficiency in complex systems. Despite the considerable progress, there remain several research gaps in understanding the full potential and impact of AI-driven automation on business processes. One key area is the scalability of AI automation in sma

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Vidushi, Sharma. "AI-Powered Automation in Healthcare: Improving Patient Care and Operational Efficiency." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 7, no. 4 (2019): 1–8. https://doi.org/10.5281/zenodo.14785680.

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Artificial Intelligence (AI) and automation technologies have become pivotal in transforming the healthcare sector, offering innovative solutions that enhance both patient care and operational efficiency. The integration of AI-powered automation can address several critical challenges faced by modern healthcare systems, including rising patient demand, resource limitations, and the increasing complexity of healthcare management. AI-driven systems provide opportunities to automate routine tasks, improve diagnostic accuracy, optimize clinical workflows, and deliver personalized treatment plans b

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Ashwini Kadam, Pratik Pawar, Prachi Pawar, Revati Pandit, Ankita Phalke, and Sanjana Jagadale. "AI Powered Recruitment System." International Research Journal on Advanced Engineering Hub (IRJAEH) 3, no. 07 (2025): 3203–8. https://doi.org/10.47392/irjaeh.2025.0471.

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Artificial intelligence in recruitment provides a revolutionary answer in today's cutthroat hiring environment. An AI-Powered Recruitment System that was created in two organized stages is presented in this study. Phase 1 creates an HR dashboard and user-friendly frontend that facilitates resume uploads, candidate management, and job postings. AI-driven automation for resume parsing, aptitude test assessment, group discussion scheduling, and interview coordination is introduced in Phase 2. The solution improves the candidate experience and recruiter control by integrating real-time notificatio

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Viswanadhapalli, Vamsi. "Integrating AI and RPA in Pega for Intelligent Process Automation: A Comparative Study." International Journal of Scientific Research and Management (IJSRM) 12, no. 06 (2024): 1317–33. https://doi.org/10.18535/ijsrm/v12i06.ec11.

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The integration of Artificial Intelligence (AI) and Robotic Process Automation (RPA) within Pega’s Intelligent Process Automation (IPA) framework is fundamentally transforming enterprise workflow management. Traditional RPA, while effective in automating repetitive, rule-based tasks, lacks the adaptability and cognitive capabilities required for handling dynamic business processes. AI-enhanced RPA, on the other hand, leverages machine learning (ML), natural language processing (NLP), predictive analytics, and decision-making algorithms to enable self-learning automation systems that optimize w

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BKP, Sarma. "Revolutionizing Workplace Productivity with AI-Powered Meeting Automation." International Journal of Science and Research (IJSR) 13, no. 12 (2024): 810. https://doi.org/10.21275/sr241209144435.

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Hari, Prasad Bomma. "Revolutionizing ETL with AI Powered Automation." International Journal of Leading Research Publication 5, no. 2 (2024): 1–5. https://doi.org/10.5281/zenodo.14769769.

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In today's era of big data and digital transformation, organizations are actively seeking efficient and scalable methods to manage their data pipelines. Traditional, ETL (Extract, Transform, and Load) processes are both demanding and time consuming, requiring manual intervention at various stages. However, cloud computing and AI advancements has heralded a new era of automated ETL pipelines. These advanced systems employ machine learning and deep learning algorithms to automate the entire data processing pipeline, from extraction to feature engineering, reducing the need for manual involvement

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Mandaloju, Nagaraj, Vinod kumar Karne, Nagaraj Mandaloju, and Parameshwar Reddy Kothamali. "AI-Powered Automation in Salesforce Testing: Efficiency and Accuracy." Universal Research Reports 8, no. 1 (2021): 121–34. http://dx.doi.org/10.36676/urr.v8.i1.1365.

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This study investigates the impact of AI-powered automation on Salesforce testing, focusing on improvements in efficiency and accuracy compared to traditional methods. The research addresses the challenge of ensuring robust testing processes in complex CRM environments, where conventional methods often fall short. A comparative analysis was conducted using both traditional and AI-powered testing tools, with metrics including test execution time, accuracy rates, and error detection rates. The results reveal that AI-powered tools significantly enhance testing efficiency, reducing execution time

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Sharma, Vidushi. "AI-powered RPA in healthcare: Reducing costs and improving patient outcomes." International Journal of Multidisciplinary Research and Growth Evaluation 5, no. 1 (2024): 1004–11. https://doi.org/10.54660/.ijmrge.2024.5.5.1072-1079.

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The integration of Artificial Intelligence (AI) with Robotic Process Automation (RPA) has led to significant advancements across various industries, with the healthcare sector experiencing transformative benefits. AI-powered RPA combines the decision-making abilities of AI with the efficiency of automation, offering solutions that streamline healthcare operations, reduce costs, and improve patient care. This paper explores the pivotal role of AI-driven RPA in healthcare, focusing on its applications in automating administrative tasks, clinical processes, and patient engagement. By examining it

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Ashok Manoharan. "Enhancing audience engagement through ai-powered social media automation." World Journal of Advanced Engineering Technology and Sciences 11, no. 2 (2024): 150–57. http://dx.doi.org/10.30574/wjaets.2024.11.2.0084.

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Enhancing Audience Engagement using AI-Powered Social Media Automation is a significant part of modern marketing techniques. This research addresses the application of artificial intelligence (AI) to automate social media interactions to boost audience engagement. The study dives into numerous AI approaches and algorithms applied in social media automation and assesses their success in enhancing audience participation, brand exposure, and customer happiness. The research explores the influence of AI-powered automation on multiple social media platforms. It assesses its potential to boost audie

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SERGIUS D, ROFINA. "AI-Powered Project Management and Reporting System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42174.

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Project management is a critical aspect of any organization, requiring efficient tracking of tasks, milestones, and team collaboration. Traditional project management systems often lack automation in reporting and data analysis. This paper presents an AI-powered Project Management and Reporting System that integrates MySQL for structured data storage, utilizes the LLM for AI-based report generation, and employs Python-docx for professional document creation. The system automates the generation of structured reports, enhances project tracking, and facilitates efficient communication among stake

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Kulkarni1, Niranjan. "AI-Powered Resume Parsing for Efficient Recruitment." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43332.

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The incorporation of Artificial Intelligence (AI) into Business Process Management Systems (BPMS) has significantly transformed multiple industries, particularly human resource management. A notable innovation in this domain is the AI-driven Resume Parser, which enhances the recruitment process by automating resume evaluation and candidate selection. Conventional hiring methods can be inefficient, requiring extensive time and effort while being susceptible to human bias, making it challenging to identify the best candidates effectively. The proposed system utilizes Natural Language Processing

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Musuluri, Chaitanya Teja. "AI-Powered Cloud Automation: Revolutionizing Predictive Scaling." European Journal of Computer Science and Information Technology 13, no. 10 (2025): 11–23. https://doi.org/10.37745/ejcsit.2013/vol13n101123.

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AI-powered cloud automation for predictive scaling represents a transformative advancement in cloud computing resource management. The integration of artificial intelligence and machine learning has revolutionized how organizations handle cloud resources, moving beyond traditional reactive scaling methods to proactive, intelligent systems. By leveraging sophisticated algorithms and real-time data analysis, predictive scaling solutions enable organizations to optimize resource allocation, reduce operational costs, and enhance application performance. These systems process multiple metrics simul

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Shravan Kumar Amjala. "AI-Powered Cloud Automation: A Scholarly Perspective." World Journal of Advanced Engineering Technology and Sciences 15, no. 2 (2025): 2664–72. https://doi.org/10.30574/wjaets.2025.15.2.0845.

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This article explores the transformative integration of artificial intelligence and machine learning into cloud infrastructure, creating a paradigm shift in enterprise IT operations. As organizations increasingly migrate to distributed cloud environments, the inherent complexity demands sophisticated automation beyond traditional manual capabilities. AI-powered cloud automation addresses these challenges through intelligent orchestration, predictive resource scaling, and autonomous optimization mechanisms. The synergistic relationship between AI and cloud technologies enables self-optimizing s

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Sadikova, Munira. "APPLICATION OF ARTIFICIAL INTELLIGENCE DEVICES IN MANUFACTURING." Al-Farg'oniy avlodlari 1, no. 4 (2023): 286–90. https://doi.org/10.5281/zenodo.10339180.

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The integration of Artificial Intelligence (AI) in manufacturing processes has revolutionized the industry, enabling businesses to enhance productivity, improve efficiency, and achieve higher levels of automation. This paper provides an overview of AI-powered devices in manufacturing, highlighting their applications, benefits, and challenges. It explores key areas where AI is being leveraged, such as predictive maintenance, quality control, robotic automation, and supply chain management. The paper also discusses the advantages of AI-powered devices, including increased operational efficiency.

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D S, Harrini. "E-COURT WITH AI POWERED LEGAL ASSISTANT." International Scientific Journal of Engineering and Management 04, no. 05 (2025): 1–9. https://doi.org/10.55041/isjem03602.

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Abstract - The traditional legal system in many countries faces challenges such as case backlogs, delayed hearings, and limited accessibility to legal resources. The E-Court System with AI-Powered Legal Assistant addresses these issues by digitizing and automating key judicial processes. Through a secure web-based platform, users including citizens, lawyers, and judges can file cases online, monitor case progress, participate in virtual hearings via WebRTC, and seek assistance from an AI-based legal chatbot. Integrating Artificial Intelligence (AI), Natural Language Processing (NLP), and real-

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Dixit, Varun. "PromptX: An AI-Powered Personal Assistant." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 201–6. https://doi.org/10.22214/ijraset.2025.69750.

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This paper introduces PromptX as an advanced AI- powered personal assistant framework which addresses complex challenges in multimodal task automation. The system addresses essential problems through its combination of Large Language Models (LLMs) and specialized agents and privacy-preserving mechanisms to achieve cross-modal alignment and dynamic tool routing and transparent decision-making. The architecture uses Gemini for intent analysis and LangChain for workflow orchestration and Qdrant for document indexing and OpenAI’s API for fallback reasoning to provide a unified solution for email m

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Sai, Sneha. "Leveraging AI in RPA: The Future of Intelligent Automation." International Journal of Leading Research Publication 5, no. 12 (2024): 1–5. https://doi.org/10.5281/zenodo.14982420.

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Artificial Intelligence (AI) is transforming Robotic Process Automation (RPA) by enabling automation solutions that are more intelligent, adaptive, and capable of handling unstructured data. Un- like traditional rule-based RPA, AI-powered automation leverages machine learning (ML), natural language processing (NLP), and computer vision to enhance decision-making, automate complex tasks, and improve efficiency. This paper explores how AI enhances RPA, from intelligent document processing and predictive analytics to AI- driven chatbots and cybersecurity. Organizations adopting AI in RPA have rep

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Ramesh Pingili. "AI-driven intelligent document processing for banking and finance." International Journal of Management & Entrepreneurship Research 7, no. 2 (2025): 98–109. https://doi.org/10.51594/ijmer.v7i2.1802.

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The banking and finance industry is buried in paperwork—loan applications, compliance reports, risk assessments, and fraud investigations. Manual processing and outdated automation slow operations, increase costs and expose institutions to compliance risks (Vaultedge, 2023). AI-driven Intelligent Document Processing (IDP) is changing this by automating document workflows, accelerating approvals, and enhancing fraud detection. AI-powered IDP integrates machine learning, NLP, and RPA to reduce verification times, reduce errors, and strengthen compliance monitoring. Banks using AI-driven document

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Agustin, Vivien A., Jonilo Mababa, Vilma A. Dela Cruz, et al. "AI-Driven Innovations in System Reliability, Government Automation, and Personalized Learning." International Journal of Research and Innovation in Applied Science X, no. III (2025): 762–69. https://doi.org/10.51584/ijrias.2025.10030056.

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This study demonstrates how Generative AI (GenAI) may improve productivity, accuracy, and workflow optimization in a variety of applications, including autonomous snowcat navigation, government report automation, and AI-powered personalized e-learning. AI-powered data visualization and extraction expedites government reporting while lowering human error and intervention. AI-powered path optimization, obstacle recognition, and sensor fusion enhance autonomous snowcat navigation’s adaptability and safety in challenging environments. Machine learning algorithms make predictive analytics, adaptive

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K., Mukilan, and Anbumalar V. "AI Powered Innovation Manufacturing: A Review." Advancement in Mechanical Engineering and Technology 8, no. 2 (2025): 11–22. https://doi.org/10.5281/zenodo.15552326.

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<em>The industrial sector is undergoing a transformation thanks to artificial intelligence (AI), which is bringing revolutionary changes to a number of areas like robots and automation, supply chain efficiency, predictive maintenance, and quality control and assurance. This thorough analysis investigates AI's significant influence on contemporary manufacturing procedures. Artificial Intelligence (AI) improves machine capabilities in robotics and automation, creating more intelligent and flexible systems. Robots can now complete complicated tasks with more flexibility and precision thanks to AI

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Thikare, Vijay P., and Prutha S. Pathak. "Decoding Tomorrows Biotechnology: AI and Machine Learning Unveiled." International Journal for Research in Applied Science and Engineering Technology 12, no. 2 (2024): 727–42. http://dx.doi.org/10.22214/ijraset.2024.58430.

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Abstract: This review paper explores the impact of AI and ML on biotechnology, focusing on drug discovery, protein prediction, automation, and ethics.AI and ML are transforming drug discovery by automating tasks, identifying new drug targets, and designing more effective drugs. AI-powered languages and functional genomics are being used to accelerate drug discovery processes. AI tools such as AlphaFold are being used to predict protein structures and functions. Biotechnology automation is being used to improve efficiency in laboratory settings. The use of AI and ML in biotechnology raises ethi

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K S, Nikhil. "AI-Powered Legal Documentation System." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47956.

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Abstract- The increasing complexity and volume of legal documentation necessitate innovative solutions to enhance accuracy, efficiency, and accessibility within the legal domain. An AI-powered Legal Documentation System leverages advanced technologies such as natural language processing (NLP), machine learning, and intelligent automation to streamline the creation, review, and management of legal documents. This system is designed to assist legal professionals in generating contracts, agreements, and other legal texts with reduced time and error rates, while ensuring compliance with current la

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Kalathot, Rambabu. "Automation of Procurement Processes in Oracle ERP Using AI." International Journal of Humanities and Information Technology 7, no. 03 (2025): 01–07. https://doi.org/10.21590/ijhit.07.03.03.

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AI-powered automation in procurement systems has emerged as a transformative force in streamlining and optimizing supply chain management. Oracle ERP, with its integrated suite of applications, offers a robust framework for implementing AI-powered automation in procurement processes, driving efficiency, accuracy, and cost savings across organizations. This research paper explores the key aspects of integrating artificial intelligence into Oracle ERP’s procurement systems and the benefits it brings to modern enterprises. The procurement function is fundamental to an organization’s operational s

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Success Ugbaja, Unomah, Uloma Stella Nwabekee, Wilfred Oseremen Owobu, and Olumese Anthony Abieba. "The Impact of AI and Business Process Automation on Sales Efficiency and Customer Relationship Management (CRM) Performance." International Journal of Advanced Multidisciplinary Research and Studies 4, no. 6 (2024): 1829–41. https://doi.org/10.62225/2583049x.2024.4.6.4156.

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The integration of Artificial Intelligence (AI) and Business Process Automation (BPA) has revolutionized sales efficiency and Customer Relationship Management (CRM) performance across industries. AI-driven automation enables organizations to optimize sales operations, enhance customer interactions, and streamline workflows, resulting in improved productivity and revenue growth. This study examines the impact of AI and BPA on sales efficiency and CRM performance, highlighting the role of predictive analytics, chatbots, natural language processing (NLP), and robotic process automation (RPA) in d

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Manevannan Ramasamy. "AI-powered network automation: Emerging trends and applications." World Journal of Advanced Research and Reviews 26, no. 2 (2025): 1443–49. https://doi.org/10.30574/wjarr.2025.26.2.1691.

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This article provides a comprehensive analysis of artificial intelligence applications in network automation, examining how machine learning techniques are revolutionizing traditional network management approaches. Through systematic examination of supervised, unsupervised, and reinforcement learning methodologies, the article demonstrates the transformative impact of AI on routing optimization, anomaly detection, and adaptive network control systems. The comparative article reveals significant performance advantages of AI-driven methods over traditional approaches, including faster fault dete

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Ricca, Filippo, Boni García, Michel Nass, and Mark Harman. "Next-Generation Software Testing: AI-Powered Test Automation." IEEE Software 42, no. 4 (2025): 25–33. https://doi.org/10.1109/ms.2025.3559194.

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Kiran, Konakalla. "AI-Driven Customer Service Automation in Insurance: Leveraging Salesforce Einstein Chat Bots and GTM Apps." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 10, no. 2 (2024): 1–4. https://doi.org/10.5281/zenodo.14203682.

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In today's digital landscape, insurance companies are utilizing AI-driven automation to streamline their customer service operations. Salesforce Einstein Chat Bots and GTM Apps integrated with Service Cloud provide robust tools for automating common customer interactions, pulling knowledge articles, creating cases, and automating surveys. These chatbots, powered by machine learning, reduce the burden on customer service agents by handling routine inquiries and freeing agents to handle more complex cases. This paper explores the configuration of these chatbots in Salesforce Service Cloud, offer

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Shahrukh, Saifi, and al. et. "AI- Powered Student Assistance ChatBot." International Journal of Computational Learning & Intelligence 4, no. 4 (2025): 823–31. https://doi.org/10.5281/zenodo.15483879.

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In the rapidly evolving digital education landscape, students require instant, accurate, and accessible academic and administrative support. This paper presents the design and implementation of an AI-powered Student Assistance Chatbot, tailored to serve institutions like REVA University and the Department of Technical Education, Government of Rajasthan. The chatbot leverages Natural Language Processing (NLP), a custom-trained dataset, and live data scraping to address queries related to admissions, fees, scholarships, placements, and more, across English and regional languages. The system aims

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Perla, Srikanth. "Software Quality Engineering: Salesforce, AI, and Test Automation." International Journal on Recent and Innovation Trends in Computing and Communication 8, no. 12 (2020): 94–98. https://doi.org/10.17762/ijritcc.v8i12.11572.

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Software quality engineering plays a critical role in ensuring that customer relationship management (CRM) applications like Salesforce are reliable, efficient, and scalable. Test automation, powered by artificial intelligence (AI), has revolutionized the way software quality is maintained, especially in complex systems such as Salesforce. Salesforce, as one of the leading CRM platforms globally, requires rigorous testing to maintain its functionality, scalability, and security across multiple modules. AI and test automation technologies such as machine learning (ML), natural language processi

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H N, Tasmiya Anjum. "IOT and AI–Powered Personalized Guest Engagement." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47774.

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In order to improve guest reception at institutional events, this paper introduces an AI and IoT-based guest inter- action system that uses personalized, touchless, and intelligent interactions. The system recognizes faces using MTCNN and a pretrained FaceNet model, uses sensors to detect presence, and uses a webcam to take pictures of faces. Using text-to-speech technology and an LED display, recognized guests are given a personalized welcome. An Arduino-controlled robotic arm with servo motors makes gestures like passing a rose. Python is used to integrate all functions, and RealVNC is used

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Islam, Md Zahirul, Prottoy Khan, and Sazib Hossain. "AI-Powered Automation in Business Operations for the Future." American Journal of Smart Technology and Solutions 4, no. 1 (2025): 49–58. https://doi.org/10.54536/ajsts.v4i1.4495.

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AI and RPA technologies has become the latest trends in the business world that have revolutionized the business sectors at an unprecedented pace. Even though, nowadays AI technologies apply to manufacturing, logistics, supply chain management industries and others, the extent of their benefits on operational capabilities, decision-making procedures, and organizational performance still does not receive enough empirical research attention. To this end, this paper seeks to fill this gap by explaining how AI and automation, more specifically RPA and cognitive automation are changing business pro

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John, Selvaraj Arulappan. "AI in Payroll: Unlocking Efficiency through Process Discovery and Automation Workflows." International Journal of Innovative Science and Research Technology (IJISRT) 10, no. 1 (2025): 1615–18. https://doi.org/10.5281/zenodo.14792213.

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The application of Artificial Intelligence (AI) in payroll systems is revolutionizing traditional workflows by enabling process discovery and automation. AI-driven tools analyze operational data to identify inefficiencies, uncover hidden patterns, and streamline payroll processes. Through intelligent automation, tasks such as payroll calculations, tax compliance, and error detection are executed with greater speed and accuracy, reducing manual interventions and associated costs. Advanced algorithms facilitate real-time monitoring and optimization, ensuring compliance with evolving regulations

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Kristombu, Shanka, Baduge Sadeep Thilakarathne, Shalitha Perera, et al. "AI-powered smart recycling: turning plastic trash into treasure." Bolgoda Plains 3, no. 2 (2023): 20–22. http://dx.doi.org/10.31705/bprm.v3(2).2023.4.

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In a world grappling with environmental challenges posed by plastic waste, innovative solutions are emerging to address the pressing issue of plastic recycling. Among these solutions, Smart AI-enabled automation and Upcycling stand out as promising technologies that offer the potential to revolutionize the way we handle and repurpose plastics. These technologies harness the power of artificial intelligence (AI) and automation to streamline the recycling process and transform discarded plastic materials into valuable products.

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Sonali Bhanudas Mali and Akanksha Ramesh Solankurkar. "VistronAI: Unlocking the Future of AI-Powered Multimedia Interaction." International Journal of Scientific Research in Science, Engineering and Technology 12, no. 2 (2025): 786–95. https://doi.org/10.32628/ijsrset25122200.

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The integration of Large Language Models (LLMs) into various applications occurs because of increasing demands for intelligent automation and real-time decision-making. LLMs power extensive business potential which enables operational improvements along with workflow streamlining and productivity improvements for various industries. VistronAI aims to develop a suite of six LLM-based applications designed to tackle challenges in areas such as data analysis, content generation, and automation. VistronAI addresses these challenges by integrating applications for audio, video, document, URL analys

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Anjum H N, Tasmiya. "IOT And AI – Powered Personalized Guest Engagement." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem45003.

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In order to improve visitor engagement and event customisation, this paper describes the design and implementation of a virtual concierge system based on AI and IoT. The system incorporates a chatbot driven by Natural Language Processing (NLP) for real-time communication, IoT sensors to detect the presence of guests, and facial recognition technologies to identify guests. Additionally, it uses cloud storage to synchronize data in real-time and actuators to carry out physical tasks like presenting guests with roses. Key technologies include OpenCV for image processing, Convolutional Neural Netw

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Vissarapu, Srikanth. "Generative AI in Cloud-Native Development: Automating Code, Configs, and Deployment." European Journal of Computer Science and Information Technology 13, no. 38 (2025): 145–56. https://doi.org/10.37745/ejcsit.2013/vol13n38145156.

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Generative AI is transforming cloud-native development through sophisticated automation capabilities across the software engineering lifecycle. By leveraging large language models and AI-powered tools, organizations can accelerate infrastructure provisioning, optimize application configurations, and enhance deployment reliability. This article explores how AI technologies are revolutionizing code generation, configuration management, and deployment orchestration in cloud environments. The integration of natural language processing, code understanding, and pattern recognition capabilities enabl

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Chandra, Prakash Singh. "Intelligent Evolution: AI-Powered Feedback Loops in DevOps." International Journal on Science and Technology 16, no. 1 (2025): 1–6. https://doi.org/10.5281/zenodo.14802819.

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DevOps, an amalgamation of "development" and "operations," represents a transformative approach in software engineering, emphasizing collaboration, automation, and iterative improvement across the software development lifecycle (SDLC). Since its inception in the early 2000s, DevOps has become a pivotal methodology for delivering high-quality software efficiently and reliably. By bridging the traditional gap between development and operations teams, DevOps fosters a culture of shared responsibility and continuous enhancement.Building on this foundation, Artificial Intelligence (AI) introduces a

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Honmane, Nilam, Pratik Bagal, Jagdish Butte, Rohan Gogawale, and Mahesh Indalkar. "Smart Travel Planner." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42872.

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Artificial intelligence (AI) has revolutionized travel planning by automating itinerary generation, optimizing routes, and personalizing travel experiences. AI-powered trip planners integrate machine learning (ML), natural language processing (NLP), and real-time data analytics to recommend destinations, accommodations, and activities based on user preferences. These systems address common travel concerns, such as budget constraints, time limitations, and changing travel conditions. Various approaches, including large language models (LLMs), automated planning algorithms, recommendation engine

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Upasana, Ranjan Singh Ashish, Raj Ritik, Raj Ritik, and Singh Satyarth. "Next Gen: AI Powered ERP." Recent Innovations in Wireless Network Security 7, no. 2 (2025): 26–35. https://doi.org/10.5281/zenodo.15300471.

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<em>Enterprise resource planning (ERP) systems have become essential tools for organizations looking to streamline, integrate, and improve decision-making. The program explores the development and implementation of an ERP system based on the organization’s needs, using technologies such as artificial intelligence (AI) to improve operations. The ERP system is intended to integrate key processes such as resource management, financial operations, human resources, student management, and educational planning into a user-friendly platform at its core. AI-enabled features such as process autom

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Chandra, Prakash Singh. "AI-Powered Test Automation: Enhancing Quality Assurance in Agile Development." Journal of Advances in Developmental Research 14, no. 2 (2023): 1–5. https://doi.org/10.5281/zenodo.14615845.

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AI-powered test automation is revolutionizing the landscape of quality assurance (QA) in agile development environments. By integrating artificial intelligence into defect detection, regression testing, and continuous integration processes, organizations can significantly enhance efficiency, accuracy, and scalability. This white paper explores the transformative impact of AI-driven automation in QA, outlining its benefits, challenges, and best practices for implementation in agile methodologies.

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Sreenivasa, Rao Sola. "The Future of ERP Cloud Functional Processes: AI-Driven Automation and OIC Integration." International Journal of Leading Research Publication 5, no. 7 (2024): 1–13. https://doi.org/10.5281/zenodo.15259105.

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The emerging role of Artificial Intelligence (AI) in Enterprise Resource Planning (ERP) Cloud and Oracle Integration Cloud (OIC) is revolutionizing functional procedures across various industries. Automation by AI enhances operational effectiveness with speeded-up workflows, business pattern forecasts, and enabling real-time decision-making. The current article explores how AI is incorporated into ERP Cloud platforms to maximize data management, predictive analytics, and business intelligence optimization. It also explores how companies are confronted with the implementation of AI-powered clou

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Ahmed, Sufyaan. "AI-Powered Legal Documentation Assistant Software." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem47421.

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Abstract—This paper presents the development and implemen- tation of an AI-powered Legal Documentation Assistant Software using the MERN (MongoDB, Express.js, React.js, Node.js) stack. The proposed system revolutionizes legal case management by providing structured case input categorization, AI-driven legal pathway recommendations, and automated generation of sup- porting legal documents. This research evaluates the system performance compared to existing legal documentation tools, highlighting the advantages of a modern web-based system integrated with AI capabilities. The paper also discusse

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Mohammed, Zubair, Naveed Uddin Mohammed, Akheel Mohammed, Shravan Kumar Reddy Gunda, and Mohammed Azmath Ansari. "AI-Powered Energy Efficient and Sustainable Cloud Networking." Journal of Cognitive Computing and Cybernetic Innovations(JCCCI) 1, no. 1 (2025): 31–36. https://doi.org/10.21276/jccci/2025.v1.i1.6.

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The exponential growth of cloud computing has led to significant energy consumption, raising environmental and economic concerns. This study explores the role of artificial intelligence (AI) in enhancing energy efficiency in cloud networking. AI-driven approaches such as machine learning, deep learning, and reinforcement learning optimize resource allocation, workload balancing, and power management to minimize energy waste while maintaining performance. AI-powered predictive analytics enable real-time power demand forecasting, adaptive cooling, and efficient routing, contributing to reduced c

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Patel, Hrishitva. "Balancing Act: Automated GenAI Outputs and Their Impact on Social Media Ecosystems." ACM SIGCAS Computers and Society 53, no. 1 (2025): 8–12. https://doi.org/10.1145/3749886.3749889.

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Generative AI is reshaping social media by automating content creation, personalization, and distribution. While it enhances accessibility and engagement, it also raises concerns around misinformation, bias, and reduced human oversight. A case study using a Twilio-powered WhatsApp bot for NASA's Astronomy Picture of the Day highlights both the potential and the limitations of AI-generated captions. Balancing automation with human judgment is essential to ensure ethical, inclusive, and trustworthy digital ecosystems.

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Govindharaju, Karthi, Rajarajachozhan C, Mirudhula D, and Janani R. "AI-Twin: AI-Powered Digital Twin for Personalized Assistance and Predictive Decision- Making." International Journal of Research and Scientific Innovation XII, no. III (2025): 609–17. https://doi.org/10.51244/ijrsi.2025.12030045.

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AI-driven digital assistants are vital for automating operations and optimizing user interactions, but current systems tend to lack adaptability, contextuality, and real-time learning. AI Twin is a future-generation digital twin created with the intent of personalized assistance and predictive decision-making. With the use of reinforcement learning, it learns and adjusts to user actions in real-time, fine-tuning responses and enhancing decision-making capabilities with the passage of time. As opposed to traditional AI assistants, AI Twin focuses on privacy using local data processing, minimizi

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Monisa Aqvin Rodrigues. "Integration of Artificial Intelligence with Robotic Process Automation: Advances, Challenges, and Future Directions." Voice of Creative Research 7, no. 2 (2025): 135–42. https://doi.org/10.53032/tvcr/2025.v7n2.16.

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The integration of the Artificial Intelligence (AI) and Robotic Process Automation (RPA) is transforming industries by enabling intelligent automation beyond rule-based processes. This paper explores the evolution of AI-powered RPA, highlighting its uses in a variety of industries, including healthcare, smart cities, finance, and software development. By analysing recent advancements, we identify how AI enhances RPA by incorporating cognitive abilities like machine learning, predictive analytics, and natural language processing. The study further investigates hybrid intelligence systems that i

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Kacheru, Goutham. "AI-POWERED TEST AUTOMATION FRAMEWORKS: CHOOSING THE RIGHT TOOLS." INTERNATIONAL JOURNAL OF ARTIFICIAL INTELLIGENCE & MACHINE LEARNING 3, no. 2 (2025): 221–30. https://doi.org/10.34218/ijaiml_03_02_018.

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Siva Krishna Jampani. "Revolutionizing Penetration Testing: AI-Powered Automation for Enterprise Security." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 10, no. 6 (2024): 1562–69. https://doi.org/10.32628/cseit241061201.

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This article explores the transformative impact of artificial intelligence and machine learning technologies on enterprise security through automated penetration testing frameworks. The article presents a comprehensive article analysis of an AI-powered penetration testing system, examining its architecture, implementation methodology, and performance metrics in real-world enterprise environments. The article findings demonstrate significant improvements in testing efficiency, with automated systems achieving superior vulnerability detection rates while substantially reducing testing time and r

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Perla, Srikanth. "AI-POWERED TEST AUTOMATION IN SALESFORCE: OPPORTUNITIES AND CHALLENGES." INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY 16, no. 1 (2025): 1413–30. https://doi.org/10.34218/ijcet_16_01_106.

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Kolli, Bhanu Prakash. "AI-Powered DevOps: Enhancing Cloud Automation with Intelligent Observability." European Journal of Computer Science and Information Technology 13, no. 4 (2025): 85–94. https://doi.org/10.37745/ejcsit.2013/vol13n48594.

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This article explores the transformative impact of AI-powered observability on cloud operations and DevOps practices. It examines how intelligent monitoring systems are revolutionizing infrastructure management, deployment strategies, and incident response through advanced anomaly detection, predictive resource allocation, and automated remediation workflows. The integration of technologies like OpenTelemetry, Prometheus, and commercial AIOps platforms enables organizations to shift from reactive to proactive operational models, significantly enhancing system reliability and performance. The a

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