Relevant bibliographies by topics / AI-driven business solutions

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'AI-driven business solutions'

Author: Grafiati
Published: 7 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "AI-driven business solutions"

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Charllo, Bala Vignesh. "AI and the new era of business intelligence: Insights that drive growth." International Journal of Multidisciplinary Research and Growth Evaluation 6, no. 1 (2025): 2126–30. https://doi.org/10.54660/.ijmrge.2025.5.1.2126-2130.

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The convergence of Artificial Intelligence (AI) and Business Intelligence (BI) heralds a transformative era in data-driven decision-making. While traditional BI focused on descriptive analytics and historical reporting, AI-driven BI extends capabilities to predictive analytics, real-time insights, and autonomous recommendation systems. This article examines how AI enriches BI processes, enabling organizations to glean deeper, more actionable insights that propel business growth. Core AI technologies such as machine learning, natural language processing (NLP), and explainable AI empower stakeho
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Tairov, Iskren, Nadezhda Stefanova, Aleksandrina Aleksandrova, and Martin Aleksandrov. "Review of AI-Driven Solutions in Business Value and Operational Efficiency." Economics Ecology Socium 8, no. 3 (2024): 55–66. http://dx.doi.org/10.61954/2616-7107/2024.8.3-5.

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Introduction. Artificial intelligence (AI) refers to a wide spectrum of breakthroughs that offer multiple advantages to companies in terms of increased sales. Considering the abundance of data and the significant increase in computational resources, organisations have rapidly turned to artificial intelligence (AI) to create financial benefits. Nevertheless, businesses continue to discover it is challenging to implement and employ AI in their everyday activities. Therefore, a comprehensive understanding is required due to the absence of an integrated comprehension of how artificial intelligence
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Yusuf Onifade, Abiodun, Jeffrey Chidera Ogeawuchi, and Abraham Ayodeji Abayomi. "Scaling AI-Driven Sales Analytics for Predicting Consumer Behavior and Enhancing Data-Driven Business Decisions." International Journal of Advanced Multidisciplinary Research and Studies 4, no. 6 (2024): 2181–201. https://doi.org/10.62225/2583049x.2025.5.3.4269.

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The rapid advancement of artificial intelligence (AI) has transformed sales analytics, enabling businesses to predict consumer behavior with unprecedented accuracy. AI-driven sales analytics leverages machine learning, natural language processing (NLP), and predictive modeling to extract actionable insights from vast datasets, enhancing decision-making and driving revenue growth. This study explores strategies for scaling AI-driven sales analytics, focusing on key challenges, technological innovations, and the impact on data-driven business decisions. The research highlights how AI-powered mod
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Yusuf Onifade, Abiodun, Jeffrey Chidera Ogeawuchi, and Abraham Ayodeji Abayomi. "Scaling AI-Driven Sales Analytics for Predicting Consumer Behavior and Enhancing Data-Driven Business Decisions." International Journal of Advanced Multidisciplinary Research and Studies 4, no. 6 (2024): 2181–201. https://doi.org/10.62225/2583049x.2024.4.6.4269.

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The rapid advancement of artificial intelligence (AI) has transformed sales analytics, enabling businesses to predict consumer behavior with unprecedented accuracy. AI-driven sales analytics leverages machine learning, natural language processing (NLP), and predictive modeling to extract actionable insights from vast datasets, enhancing decision-making and driving revenue growth. This study explores strategies for scaling AI-driven sales analytics, focusing on key challenges, technological innovations, and the impact on data-driven business decisions. The research highlights how AI-powered mod
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Asha, Ayesha Islam, MD Sheam Arafat, Kirtibhai Desai, Mir Abrar Hossain, and Sharmin Akter. "The Role of Blockchain and AI in Revolutionizing Electronic Health Records: A Business-Driven Approach to Data Security and Interoperability." International Interdisciplinary Business Economics Advancement Journal 06, no. 05 (2025): 08–38. https://doi.org/10.55640/business/volume06issue05-02.

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Advanced technological solutions need to address critical data security problems and interoperability issues that emerge from EHR systems developing in complexity. This document evaluates the combination of Blockchain technology and Artificial Intelligence tools for EHR system transformation from a business analytical standpoint. Blockchain technology maintains a secure environment through its indestructible record system and distributed computing framework that locks out breaches and unlawful data modifications thus meeting healthcare requirements of HIPAA and GDPR. AI-driven predictive analy
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Hossain, Mir Abrar, MD Sheam Arafat, Kirtibhai Desai, Sharmin Akter, and Ayesha Islam Asha. "The Economic Impact of AI-Driven Remote Patient Monitoring: A Business Intelligence Perspective on Healthcare Cost Optimization." International Interdisciplinary Business Economics Advancement Journal 06, no. 05 (2025): 39–67. https://doi.org/10.55640/business/volume06issue05-03.

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Healthcare cost optimization has improved through the implementation of Artificial Intelligence in remote patient monitoring because it increases operational efficiency and predictive analytics and allows immediate patient care management. This paper examines AI-powered RPM's economic value by showing its capacity to decrease hospital admissions together with reducing healthcare expenses while directing resources effectively. Business intelligence tools with AI help RPM systems create predictive intervention strategies for better patient results without affecting operational costs. This resear
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Calvo, Jorge. "High-Tech Start-Ups in Japan: Cogent Labs, AI-OCR Solutions for Automated Business Process Outsourcing." International Journal of Entrepreneurial Knowledge 6, no. 2 (2018): 12–31. http://dx.doi.org/10.2478/ijek-2018-0011.

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Abstract This business research case introduces Cogent Labs, a Japanese high-tech start-up that provides AI-driven technologies, is making the critical transition from an entrepreneur-driven to a mature management-run organization, the company’s business context and technology development. That requires to harmonize the entrepreneurial and managerial capacity, by a collaborative approach integrating cross-functional product teams. The high-tech start-up has demonstrated ability to overcome the transitional stage of the first entrepreneurship to stability and sustainability through the manageme
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Arif, Md, Md Parvez Ahmed, Abdullah Al Mamun, et al. "DYNAMIC PRICING IN FINANCIAL TECHNOLOGY: EVALUATING MACHINE LEARNING SOLUTIONS FOR MARKET ADAPTABILITY." International Interdisciplinary Business Economics Advancement Journal 05, no. 10 (2024): 13–27. http://dx.doi.org/10.55640/business/volume05issue10-03.

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The rapid advancement of technology has transformed the financial services sector, leading to the rise of fintech companies that leverage cutting-edge tools such as artificial intelligence (AI) and machine learning (ML) to offer innovative solutions. One area where fintech is particularly impactful is dynamic pricing, which involves adjusting prices in real-time based on market conditions, user behavior, and external factors. The ability to optimize pricing in response to fluctuating conditions is critical for maximizing profitability, improving customer satisfaction, and maintaining competiti
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Researcher. "HOW AI IMPROVES DATA QUALITY FOR BETTER BUSINESS INSIGHTS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 590–601. https://doi.org/10.5281/zenodo.14197959.

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In today's rapidly evolving digital landscape, organizations face unprecedented challenges in managing and maintaining data quality across their enterprise systems. This comprehensive article explores how Artificial Intelligence (AI) revolutionizes data quality management, offering sophisticated data cleaning, validation, and enrichment solutions. The article examines the current state of data quality challenges, presents AI-powered solutions, and demonstrates their impact through real-world applications in the financial services and manufacturing sectors. Through detailed case studies and ind
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Aladebumoye, Tolulope. "Integrating AI-Driven Tax Technology into Business Strategy." International Journal of Research and Review 12, no. 1 (2025): 224–31. https://doi.org/10.52403/ijrr.20250128.

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The integration of Artificial Intelligence (AI) into tax technology presents transformative potential for enhancing business strategies by significantly improving efficiency, accuracy, and compliance. This paper delves into these advancements and critically evaluates their strategic implications across various sectors, providing a thorough analysis of how AI-driven innovations are reshaping tax practices. It highlights the dual role of AI in not only simplifying and automating complex tax operations but also in enabling businesses to navigate the increasingly complex maze of global tax regulat
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Dissertations / Theses on the topic "AI-driven business solutions"

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Jonsson, Hanna, and Luyolo Mazomba. "Revenue Generation in Data-driven Healthcare : An exploratory study of how big data solutions can be integrated into the Swedish healthcare system." Thesis, Umeå universitet, Företagsekonomi, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-161384.

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Abstract The purpose of this study is to investigate how big data solutions in the Swedish healthcare system can generate a revenue. As technology continues to evolve, the use of big data is beginning to transform processes in many different industries, making them more efficient and effective. The opportunities presented by big data have been researched to a large extent in commercial fields, however, research in the use of big data in healthcare is scarce and this is particularly true in the case of Sweden. Furthermore, there is a lack in research that explores the interface between big data
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Books on the topic "AI-driven business solutions"

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Malmqvist, Lars. Architecting AI Solutions on Salesforce: Design Powerful and Accurate AI-Driven State-of-the-art Solutions Tailor-made for Modern Business Demands. Packt Publishing, Limited, 2021.

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Verdegem, Pieter, ed. AI for Everyone? Critical Perspectives. University of Westminster Press, 2021. http://dx.doi.org/10.16997/book55.

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We are entering a new era of technological determinism and solutionism in which governments and business actors are seeking data-driven change, assuming that Artificial Intelligence is now inevitable and ubiquitous. But we have not even started asking the right questions, let alone developed an understanding of the consequences. Urgently needed is debate that asks and answers fundamental questions about power. This book brings together critical interrogations of what constitutes AI, its impact and its inequalities in order to offer an analysis of what it means for AI to deliver benefits for ev
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Book chapters on the topic "AI-driven business solutions"

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Mock, Moritz, Jorge Melegati, and Barbara Russo. "Generative AI for Test Driven Development: Preliminary Results." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-72781-8_3.

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AbstractTest Driven Development (TDD) is one of the major practices of Extreme Programming for which incremental testing and refactoring trigger the code development. TDD has limited adoption in the industry, as it requires more code to be developed and experienced developers. Generative AI (GenAI) may reduce the extra effort imposed by TDD. In this work, we introduce an approach to automatize TDD by embracing GenAI either in a collaborative interaction pattern in which developers create tests and supervise the AI generation during each iteration or a fully-automated pattern in which developer
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Zillner, Sonja. "Business Models and Ecosystem for Big Data." In The Elements of Big Data Value. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68176-0_11.

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AbstractWith the recent technical advances in digitalisation and big data, the real and the virtual worlds are continuously merging, which, again, leads to entire value-added chains being digitalised and integrated. The increase in industrial data combined with big data technologies triggers a wide range of new technical applications with new forms of value propositions that shift the logic of how business is done. To capture these new types of value, data-driven solutions for the industry will require new business models. The design of data-driven AI-based business models needs to incorporate
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Fraser, Steven D., and Dennis Mancl. "XP 25th Anniversary Workshop and Panel Report: Innovating Software Solutions – Past, Present, and Future." In Lecture Notes in Business Information Processing. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-72781-8_30.

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AbstractSoftware practitioners have adopted many new ways of working over the past 25 years. Change has been driven by a diverse and global community of users, practitioners, researchers, and vernacular programmers. What have we learned over the past 25 years? What skills will software researchers and practitioners need in the future? Will AI or other emerging technologies offer opportunities for greater achievements, or will they become an obstacle to the human touch needed to develop software products? This paper reports on a combined workshop and panel organized and facilitated by Steven Fr
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Lampathaki, Fenareti, Evmorfia Biliri, Tasos Tsitsanis, Kostas Tsatsakis, Dimitris Miltiadou, and Konstantinos Perakis. "Toward an Energy Data Platform Design: Challenges and Perspectives from the SYNERGY Big Data Platform and AI Analytics Marketplace." In Data Spaces. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98636-0_14.

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AbstractToday, the need for “end-to-end” coordination between the electricity sector stakeholders, not only in business terms but also in securely exchanging real-time data, is becoming a necessity to increase electricity networks’ stability and resilience while satisfying individual operational optimization objectives and business case targets of all stakeholders. To this end, the SYNERGY energy data platform builds on state-of-the-art data management, sharing, and analytics technologies, driven by the actual needs of the electricity data value chain. This paper will describe the layered SYNE
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Jampala, Mrs Swathi. "Enhancing Workplace Sustainability: AI-Driven HR Management Solutions." In Interdisciplinary Research on Sustainability of Business. Iterative International Publishers, Selfypage Developers Pvt Ltd, 2024. https://doi.org/10.58532/nbennurirch15.

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AI is rapidly transforming numerous sectors and sustainability is no exception. It provides novel ways through which AI can be used to maximize resource utilization, minimize waste as well as evaluate likely environmental impacts. In this study, we adopt a descriptive approach where we explore different artificial intelligence tools and techniques that can be integrated into management systems to promote sustainability. Different publications from different industries demonstrate the potential of AI for inclusion in management processes aimed at promoting sustainability
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Karulkar, Yashodhan, Arshi Shah, and Rishab Naik. "AI-Powered Business Evolution." In Advances in Business Information Systems and Analytics. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-4187-2.ch003.

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This chapter, as per the authors, examines the multidimensional function of artificial intelligence (AI) in many industries, focusing on its strategic integration for organizational success, decision-making improvement, and data management efficiency. The chapter examines how AI-driven solutions are altering old processes and catalyzing innovation in the logistics, aeronautics, agriculture and the banking industry. In logistics, AI enables predictive analytics and route optimization, resulting in better supply chain management and operational efficiency. AI in aeronautics improves safety measu
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Sharma, Deepa. "Cases on AI-Driven Solutions to Environmental Challenges." In Practice, Progress, and Proficiency in Sustainability. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-1917-9.ch008.

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Entrepreneurs today rely heavily on AI-powered decision support systems to help them make decisions about resource allocation, opportunity discovery, risk management, and other areas of their business. Artificial intelligence is crucial in managing customer relationships, monitoring employees, organizing and interpreting financial data, and predicting future growth to help firm's better plan for scaling. AI has a huge impact on the startup environment, offering hitherto unseen opportunities for expansion, creativity, and revolutionizing traditional business strategy. The revolutionary potentia
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Mathur, Kshitij, and Satyam Sinha. "Data-Driven Supply Chain Revolution." In Advances in Business Strategy and Competitive Advantage. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-4433-0.ch018.

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In an era where data is the new oil, supply chains are undergoing a fundamental transformation. The chapter ” Data-Driven Supply Chain Revolution: Metamorphosize through Science” aims to provide a deep understanding of the synergy between AI/ML and supply chain management. This chapter will explore the strategies, technologies, and best practices necessary for organizations to harness generative AI and ML for Supply Chain Innovation projects. This chapter starts with the reference of the five core SCM processes of the SCOR model and then elaborates how gen AI and ML solution can address the ke
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Ahmad, Tanzeem. "Artificial Intelligence and ICT: Unlocking New Potentials in Education." In Business Analytics. San International Scientific Publications, 2025. https://doi.org/10.59646/ict/317.

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The rapid advancement of Artificial Intelligence (AI) and Information and Communication Technology (ICT) is transforming every facet of human life, and education is no exception. As the world embraces digital transformation, AI-driven solutions are reshaping traditional teaching and learning paradigms, unlocking new potentials for both educators and learners. This book, Artificial Intelligence and ICT: Unlocking New Potentials in Education, explores the profound impact of AI and ICT on modern education, highlighting their applications, challenges, and future directions.
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Al-Said, Nidal. "Integrating Business Intelligence and AI for Collaborative Leadership in Organizations." In Embracing the Cloud as a Business Essential. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9581-3.ch011.

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Organizational collaborative leadership is being revolutionized by the integration of artificial intelligence (AI) and business intelligence (BI), which makes data-driven decision-making possible. To improve leadership collaboration, one of the best strategies is to create an AI-driven BI ecosystem that makes use of automation, real-time insights, and predictive analytics. Organizations may automate data analysis, produce actionable insights, and make it easier for leadership teams to communicate with one another by utilizing AI-powered BI solutions like Microsoft Power BI. Leaders may use pre
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Conference papers on the topic "AI-driven business solutions"

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Sasane, Jairaj J., Arvind L. Burande, Sanket Charkha, Dhanajay M. Jadhav, and Vijay Dhole. "AI-Driven Business Transformation: Leveraging Machine Learning for Enhanced Decision-Making." In 2025 International Conference on Frontier Technologies and Solutions (ICFTS). IEEE, 2025. https://doi.org/10.1109/icfts62006.2025.11031982.

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Stukalina, Yulia, and Olga Zervina. "BUSINESS DIGITAL TRANSFORMATION IN THE DATA-DRIVEN ECONOMY: ENHANCING VALUE WITH AI SERVICES." In 13th International Scientific Conference „Business and Management 2023“. Vilnius Gediminas Technical University, 2023. http://dx.doi.org/10.3846/bm.2023.955.

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The purpose of the paper is to explore cutting-edge AI-based solutions applied for providing a multi-business company with the capability to increase business value in the agenda of digital transformation. The main elements of a scale-up business strategy, where AI creates business value, are identified and described. The methodology includes secondary research involving reviewing and interpretation of secondary data, analysis of publicly available statistical data, and a case study for providing factual evidence from a specific example – the company, which is one of the best illustrations of
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Kumar, Devesh. "Harnessing Artificial Intelligence for Global Sustainability: A Systematic Review of Applications, Challenges, and Future Directions." In 7th World Conference on Business, Management, Finance, Economics, and Marketing. Eurasia Conferences, 2025. https://doi.org/10.62422/978-81-981590-7-6-001.

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Artificial Intelligence (AI) has emerged as a transformative force in addressing global sustainability challenges, offering innovative solutions for energy optimization, environmental conservation, waste management, and smart urban development. This systematic review critically examines the role of AI in advancing sustainability initiatives by synthesizing peer-reviewed literature published between 2015 and 2024. The study explores how AI-driven technologies, including machine learning, deep learning, and big data analytics, contribute to improving energy efficiency, optimizing resource utiliz
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Alzeqri, Aziz. "Artificial Intelligence in Non-Clinical Functions: A Strategic Framework for Healthcare Organizations." In The Integration of AI and Technology in Modern Business Practices. SBS Swiss Business School, 2024. http://dx.doi.org/10.70301/conf.sbs-jabr.2024.1/1.4.

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Artificial Intelligence (AI) has demonstrated significant potential in healthcare, particularly in clinical applications such as diagnostics and personalized treatment. However, the application of AI in non-clinical areas, such as operational efficiency, data governance, and data monetization, remains underexplored. This paper addresses this gap by proposing an AI-driven framework for healthcare organizations, synthesizing existing literature on AI applications and data management. Using a qualitative approach, this study identifies six key areas where AI can enhance non-clinical operations: d
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Alan Tshinkobo, Matanda, John Ikome, and Ibrahim Idowu. "Enhancing E-commerce Efficiency: AI Solutions for Last-Mile Delivery in Johannesburg." In 16th International Conference on Applied Human Factors and Ergonomics (AHFE 2025). AHFE International, 2025. https://doi.org/10.54941/ahfe1006451.

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In the South African context, Johannesburg has become the hub of economic activities and the case of e-commerce expansion comes with a problem of last mile delivery. The challenges caused by the void in artificial intelligence (AI) literature are well known, but such application in Johannesburg’s logistical environment where there is a high level of traffic, poor infrastructure and even laws is lacking.This study seeks to bridge that gap by employing a quantitative approach, drawing on statistical data from a variety of sources, including academic journals, industry reports, and case studies o
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Nair, Krishnakumar. "Interventions and Iterations to Fortify Small Business Resilience." In InSITE 2025: Informing Science + IT Education Conferences: Hiroshima. Informing Science Institute, 2025. https://doi.org/10.28945/5533.

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Aim/Purpose Globally, small businesses are experiencing alarmingly high failure rates. The Business Failure Modes and Effects Analysis (BFMEA) framework was developed as a proactive solution to address this challenge, specifically targeting small technology enterprises representing approximately one-third of the small enterprises sector. This research illustrates how targeted practitioner interventions and iterative refinements, guided by the elaborated Action Design Research (eADR) methodology, significantly enhanced the effectiveness of the BFMEA worksheet – evolving it into a structured, pr
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Milić, Bojana, Jelena Spajić, Dunja Bošković, Ksenija Mitrović, and Danijela Lalić. "AI VS. HUMAN DESIGNERS: EVALUATING THE EFFECTIVENESS OF AI-GENERATED VISUAL CONTENT IN DIGITAL MARKETING." In INTERNATIONAL SYMPOSIUM ON GRAPHIC ENGINEERING AND DESIGN. UNIVERSITY OF NOVI SAD FACULTY OF TECHNICAL SCIENCES DEPARTMENT OF GRAPHIC ENGINEERING AND DESIGN 21000 Novi Sad, Trg Dositeja Obradovića 6, 2024. http://dx.doi.org/10.24867/grid-2024-p42.

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In the rapidly evolving landscape of digital marketing, the quest for more effective and engaging visual content is relentless. With artificial intelligence (AI) making significant strides, an important question arises: Can AI tools for design surpass the creativity and effectiveness of human graphic designers? This intriguing inquiry forms the cornerstone of our study. We aimed to evaluate the effectiveness of AI- generated versus human-designed advertisements through a practical approach. In the first phase, both a human graphic designer and an AI tool were given identical tasks and prompts
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Ifalade, Oluwajuwon, and Opeyemi Adeleke. "Driving Profitability in Oil and Gas production Operations by Leveraging on Business Process Automation Solutions: The AI Journey." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2024. http://dx.doi.org/10.2118/221760-ms.

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Abstract The Oil and Gas industry, traditionally non-digital native, is experiencing a significant uptick in the adoption of technology throughout its value chain. This paper unveils a compelling use case of the Microsoft Power series—Power BI, specifically—in revolutionizing reporting, streamlining approval processes, and optimizing for maximum economic outcomes. NNPC E & P Limited (NEPL) is the upstream operating subsidiary of the national oil company, NNPC Limited. This role presents a unique challenge of managing assets across various operational models. This raises the question of fin
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Grumadaitė, Kristina, Sebin Thomas Babu, and Sonny Jose. "Tourism and Sustainability: Exploring the Role of AI-Driven Tourism Practices in Shaping Consumer Sustainable Behaviour." In 9th FEB International Scientific Conference. University of Maribor Press, 2025. https://doi.org/10.18690/um.epf.5.2025.57.

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The actors of the tourism industry worldwide keep implementing more digital solutions into the tourism services, including artificial intelligence (AI) tools to improve travel planning, pricing, marketing and other business functions, and to increase the quality of tourism experience. Sustainability, on the other hand, is of significant importance in order to maintain economic efficiency, social equity and ecological consideration. However, various gaps and inconsistencies between providing and using AI and sustainable tourism services are noticed. Thus, this paper aims to analyse the scope of
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Interdonato, Antonino. "ARTIFICIAL INTELLIGENCE FOR IMPROVING DECISION-MAKING PROCESSES IN PUBLIC ADMINISTRATION." In Eighth International Scientific Conference Contemporary Issues in Economics, Business and Management [EBM 2024]. Faculty of Economics, Kragujevac, 2025. https://doi.org/10.46793/ebm24.085i.

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The integration of artificial intelligence (AI) in public administration represents one of the most promising innovations for enhancing the efficiency and effectiveness of decision-making processes. This study focuses on AI applications to optimize decision-making within public institutions, with particular focus on resource management, strategic planning, and emergency response. Using a multidisciplinary approach, the research analyses case studies of public administrations that have implemented AI-based solutions, highlighting the benefits achieved and the challenges encountered. Through the
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Reports on the topic "AI-driven business solutions"

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Pasupuleti, Murali Krishna. Empathetic AI in Action: Transforming Customer Service with Emotional Intelligence. National Education Services, 2025. https://doi.org/10.62311/nesx/rr725.

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Abstract: This article explores the transformative impact of Emotionally Intelligent AI on customer service, focusing on how AI systems are designed to understand and respond to human emotions with empathy and precision. It delves into the core technologies, such as sentiment analysis, emotion recognition models, and reinforcement learning, that enable AI to provide emotionally aware interactions. Practical applications are discussed, including AI-powered customer support, personalized experiences, and crisis management solutions. The Article also covers the psychological foundations of AI-dri
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