Academic literature on the topic 'AI-Driven Procurement Transformation'
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Journal articles on the topic "AI-Driven Procurement Transformation"
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Esan, Oluwafunmilayo Janet, Ogechi Thelma Uzozie, Osazee Onaghinor, Grace Omotunde Osho, and Emmanuel Augustine Etukudoh. "Procurement 4.0: Revolutionizing Supplier Relationships through Blockchain, AI, and Automation: A Comprehensive Framework." Journal of Frontiers in Multidisciplinary Research 3, no. 1 (2022): 117–23. https://doi.org/10.54660/.ijfmr.2022.3.1.117-123.
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Procurement 4.0 marks a fundamental shift in supplier relationship management by leveraging blockchain, artificial intelligence (AI), and automation to enhance transparency, efficiency, and risk mitigation. This paper provides a comprehensive framework for integrating these technologies into procurement strategies, addressing key challenges in digital transformation while maximizing operational benefits. Blockchain facilitates secure and immutable transaction records, ensuring supplier accountability and seamless contract execution through smart contracts. AI-driven predictive analytics enable data-informed supplier selection, risk assessment, and fraud detection, improving procurement decision-making. Automation, including robotic process automation (RPA), streamlines repetitive tasks, reduces procurement cycle times, and optimizes resource allocation. This study explores the theoretical foundations of Procurement 4.0, focusing on the principles driving its adoption and the impact of digital transformation on supplier relationships. It examines blockchain-enabled transparency, AI-powered risk management, and automation-driven efficiency. A structured framework is proposed to guide organizations in implementing Procurement 4.0, addressing integration challenges and strategic considerations. The paper concludes with policy recommendations and future research directions, emphasizing the need for regulatory alignment, ethical AI deployment, and continued advancements in digital procurement technologies.
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Esan, Oluwafunmilayo Janet, Ogechi Thelma Uzozie, and Osazee Onaghinor. "Procurement 4.0: Revolutionizing Supplier Relationships through Blockchain, AI, and Automation: A Comprehensive Framework." International Journal of Multidisciplinary Research and Growth Evaluation 3, no. 1 (2022): 900–906. https://doi.org/10.54660/.ijmrge.2022.3.1.900-906.
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Procurement 4.0 marks a fundamental shift in supplier relationship management by leveraging blockchain, artificial intelligence (AI), and automation to enhance transparency, efficiency, and risk mitigation. This paper provides a comprehensive framework for integrating these technologies into procurement strategies, addressing key challenges in digital transformation while maximizing operational benefits. Blockchain facilitates secure and immutable transaction records, ensuring supplier accountability and seamless contract execution through smart contracts. AI-driven predictive analytics enable data-informed supplier selection, risk assessment, and fraud detection, improving procurement decision-making. Automation, including robotic process automation (RPA), streamlines repetitive tasks, reduces procurement cycle times, and optimizes resource allocation. This study explores the theoretical foundations of Procurement 4.0, focusing on the principles driving its adoption and the impact of digital transformation on supplier relationships. It examines blockchain-enabled transparency, AI-powered risk management, and automation-driven efficiency. A structured framework is proposed to guide organizations in implementing Procurement 4.0, addressing integration challenges and strategic considerations. The paper concludes with policy recommendations and future research directions, emphasizing the need for regulatory alignment, ethical AI deployment, and continued advancements in digital procurement technologies.
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Researcher. "THE TRANSFORMATIVE IMPACT OF AI ON PROCUREMENT EXCELLENCE: A TECHNICAL ANALYSIS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 6 (2024): 475–87. https://doi.org/10.5281/zenodo.14178698.
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This comprehensive article explores the transformative impact of Artificial Intelligence on procurement operations and strategic decision-making across global enterprises. The article examines how AI-driven solutions revolutionize traditional procurement processes through automation, predictive analytics, and data-driven supplier management. The article investigates the implementation considerations, technical requirements, and critical success factors for AI adoption in procurement. The findings demonstrate that organizations leveraging AI technologies significantly improve operational efficiency, cost reduction, and strategic value creation. The article also explores emerging trends, including the integration of blockchain, IoT, and advanced cognitive computing systems, highlighting their potential to reshape the future of procurement operations and supply chain management.
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Chandramohan, Pradeep. "Accelerating RFP Evaluation with AI-Driven Scoring Frameworks." European Journal of Computer Science and Information Technology 13, no. 30 (2025): 37–49. https://doi.org/10.37745/ejcsit.2013/vol13n303749.
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The evolution of Request for Proposal (RFP) evaluation processes has reached a pivotal moment with the integration of artificial intelligence and machine learning technologies. This advancement addresses longstanding challenges in traditional manual evaluation methods, particularly focusing on efficiency, consistency, and objectivity. Through the implementation of AI-driven scoring frameworks, organizations can now transform qualitative responses into quantifiable insights, enabling faster and more objective assessment of submissions. Natural Language Processing techniques, including named entity recognition and semantic similarity scoring, have revolutionized the extraction of key information and evaluation of alignment with RFP criteria. The integration of rule-based frameworks applies predefined logic to generate transparent scores, ensuring accountability and repeatability throughout the evaluation process. This technological transformation not only reduces evaluator fatigue but also minimizes subjective bias, contributing to fairer procurement outcomes. Additionally, the early detection of incomplete or non-compliant responses through AI systems enhances overall process efficiency. The implementation framework provides organizations with structured guidance for adopting these technologies while maintaining customizable logic, human-in-the-loop design, and compliance with procurement standards.
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Sreenivasa, Rao Sola. "ERP Cloud and Procurement: Unlocking New Levels of Automation and Integration." International Journal of Leading Research Publication 1, no. 1 (2020): 1–14. https://doi.org/10.5281/zenodo.15259058.
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The dynamics of enterprise resource planning (ERP) systems have revolutionized the manner in which organizations manage procurement processes. Oracle ERP Cloud, being one of the leading cloud-based software solutions, has ushered in advanced features that enhance procurement activities via automation, integration, and artificial intelligence (AI)-informed decision-making. This journal addresses the significant contribution of Oracle ERP Cloud applications to optimizing procurement strategies through business ability to automate procurement processes, reduce operation costs, and accelerate procurement cycle times. Levying on automated processes, AI-driven insights, and real-time data integration, companies can make better and faster procurement decisions. The journal points out meaningful features of Oracle ERP Cloud that drive automation, such as supplier collaboration portals, intelligent demand forecasting, and automated purchase order processing. In addition, the integration of machine learning and AI tools in Oracle's cloud platform enables predictive analytics, which allows procurement teams to identify potential disruptions, enhance the performance of suppliers, and steer clear of risks. From industry case studies and prior research, based on developments up to October 2020, this paper provides the actual benefits of deploying ERP cloud solutions for procurement, such as improved supplier relationship management, cost advantages, and improved decision-making capabilities. With more businesses embracing digital transformation, Oracle ERP Cloud is a major driver of efficient, integrated, and low-cost procurement operations, setting new benchmarks in procurement automation and innovation.
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Fredson, Gracetiti, Babatunde Adebisi, Olushola Babatunde Ayorinde, Ekene Cynthia Onukwulu, Olugbenga Adediwin, and Alexsandra Ogadimma Ihechere. "Enhancing Procurement Efficiency through Business Process Reengineering: Cutting-Edge Approaches in the Energy Industry." International Journal of Social Science Exceptional Research 1, no. 1 (2022): 38–54. https://doi.org/10.54660/ijsser.2022.1.1.38-54.
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The energy industry operates in a highly dynamic environment, requiring robust procurement systems to ensure efficiency, cost-effectiveness, and alignment with sustainability goals. However, traditional procurement methods often fail to address emerging challenges such as fluctuating energy markets, supply chain disruptions, and increasing regulatory demands. This study explores the transformative potential of Business Process Reengineering (BPR) in enhancing procurement efficiency within the energy sector. By rethinking and redesigning procurement processes, BPR offers a systematic framework for eliminating inefficiencies, reducing operational costs, and optimizing resource utilization. The study examines cutting-edge approaches such as process automation, digital procurement platforms, data-driven decision-making, and artificial intelligence (AI) integration, which are increasingly being adopted to streamline procurement workflows and improve supplier collaboration. Through an in-depth analysis of case studies and empirical data, the research highlights how energy companies leveraging BPR strategies achieve greater agility and resilience in their procurement operations. Key findings reveal that implementing AI-powered tools for demand forecasting, blockchain for transparent supplier transactions, and digital dashboards for real-time tracking significantly enhances procurement performance. Additionally, the study underscores the importance of fostering organizational culture shifts, change management strategies, and cross-functional collaboration to ensure the successful adoption of reengineered processes. This paper further identifies critical success factors for implementing BPR in the energy sector, including top management support, employee training, and investment in scalable digital infrastructure. It also discusses the role of sustainability in procurement transformation, emphasizing green procurement practices that align with global energy transition goals. By offering actionable insights, this research provides a roadmap for energy companies to achieve procurement excellence, drive operational efficiency, and remain competitive in an evolving market.
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Bhavikatta, Naga Bharadwaj. "THE INTELLIGENT SUPPLY CHAIN: LEVERAGING AI AND ML FOR OPERATIONAL EXCELLENCE." International Journal of Computer Science and Mobile Computing 14, no. 6 (2025): 56–66. https://doi.org/10.47760/ijcsmc.2025.v14i06.007.
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In an increasingly volatile and globalized marketplace, traditional supply chains are under immense pressure to deliver higher efficiency, agility, and resilience. The concept of the intelligent supply chain has emerged as a strategic imperative, driven by the need for real-time insights, adaptive decision-making, and predictive capabilities. Artificial Intelligence (AI) and Machine Learning (ML) are at the forefront of this transformation, enabling end-to-end automation, enhanced forecasting accuracy, and intelligent optimization across procurement, logistics, inventory, and production planning. This study explores the multifaceted role of AI and ML in modernizing supply chain operations, identifying the technological enablers, use cases, and organizational benefits associated with their adoption. Through an in-depth review of current literature, market implementations, and case studies from industry leaders such as Amazon, Maersk, and Unilever, the paper demonstrates how AI-driven systems improve demand forecasting, reduce operational costs, and increase supply chain responsiveness. The findings suggest that the integration of intelligent technologies not only supports operational excellence but also equips enterprises to navigate disruptions with greater strategic foresight.
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Rainy, Tahmina Akter, and Abdur Razzak Chowdhury. "THE ROLE OF ARTIFICIAL INTELLIGENCE IN VENDOR PERFORMANCE EVALUATION WITHIN DIGITAL RETAIL SUPPLY CHAINS: A REVIEW OF STRATEGIC DECISION-MAKING MODELS." American Journal of Scholarly Research and Innovation 01, no. 01 (2022): 220–48. https://doi.org/10.63125/96jj3j86.
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The digital transformation of retail supply chains has fundamentally reshaped how organizations evaluate, manage, and engage with their suppliers. In this context, artificial intelligence (AI) has emerged as a transformative enabler, offering sophisticated tools for enhancing vendor performance evaluation through intelligent automation, predictive modeling, and real-time decision-making support. This systematic review critically examines the integration of AI technologies—such as supervised and unsupervised machine learning, natural language processing (NLP), and deep learning algorithms—into vendor performance assessment frameworks within digital retail ecosystems. Drawing on an analysis of 86 peer-reviewed journal articles, industry white papers, and technical reports published between 2015 and 2022, the study identifies and categorizes the predominant AI-driven models employed to assess key supplier attributes, including reliability, quality assurance, compliance with contractual obligations, cost-efficiency, and operational risk. The review further investigates how these AI tools enable real-time vendor monitoring, dynamic anomaly detection, and the automation of adaptive performance scorecards. Evidence from the literature demonstrates that AI-enabled evaluation systems can significantly enhance the precision, objectivity, and scalability of vendor assessments, while reducing human bias and manual inefficiencies in procurement processes. However, the adoption of AI in this domain is not without challenges. Common barriers include fragmented data architectures, difficulties in integrating AI tools with legacy enterprise systems, concerns over the interpretability and ethical transparency of algorithmic decisions, and a lack of standardization in AI governance practices. In response to these challenges, the review also identifies emergent research opportunities aimed at improving the accountability, fairness, and sustainability of AI applications in retail supply chains. Future research directions include the development of hybrid models combining human expertise with machine learning, reinforcement learning-based adaptive evaluation systems, and the incorporation of ESG (environmental, social, and governance) metrics into AI-based vendor assessments. This review contributes to the growing discourse on AI’s role in shaping agile, data-driven, and ethically sound vendor management practices within the evolving digital retail ecosystem. By synthesizing current findings, the review highlights critical implementation bottlenecks and knowledge gaps in the field, and proposes future research directions for developing explainable, secure, and ethically sound AI solutions that align with sustainable procurement goals and evolving retail strategies.
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Katuri, Desi Ramananda Kishore. "Streamlining Procure-to-Pay Processes in Large-Scale Companies with ERP Finance Systems." European Journal of Computer Science and Information Technology 13, no. 38 (2025): 174–90. https://doi.org/10.37745/ejcsit.2013/vol13n38174190.
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This article examines how Enterprise Resource Planning (ERP) finance systems transform procure-to-pay (P2P) processes in large-scale organizations across various industries. Traditional P2P operations often suffer from inefficiencies including manual data entry, disjointed systems, approval bottlenecks, and limited visibility into spending patterns. ERP solutions address these challenges by integrating procurement with financial operations, automating workflows, and enhancing transparency throughout the P2P lifecycle. It explores implementation across retail, financial services, and educational institutions, highlighting how each sector leverages ERP features to meet unique requirements. Key transformative capabilities discussed include intelligent invoice processing, real-time analytics, and supplier collaboration portals. The article identifies critical implementation challenges—data fragmentation, user resistance, and legacy system integration—along with proven strategies to overcome them. Best practices for P2P excellence are presented, focusing on process standardization before automation, strategic supplier segmentation, and continuous improvement frameworks. Looking ahead, the article examines emerging trends that will shape future P2P transformation: AI-driven procurement intelligence, blockchain for secure transactions, and embedded ESG (Environmental, Social, Governance) considerations. It provides organizations with a roadmap for leveraging ERP finance systems to transform procurement into a strategic asset that delivers operational efficiency, enhanced compliance, and sustainable cost savings.
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Erceg, Aleksandar, and Santhosh Joseph. "Sourcing efficacy – The role of supportive intelligence." Ekonomski vjesnik 38, no. 1 (2025): 133–49. https://doi.org/10.51680/ev.38.1.10.
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Purpose: Globalization has increased the importance of sourcing and procurement strategies and factbased negotiation (FBN). Technological advances such as machine learning (ML) and artificial intelligence (AI) and their integration in FBN are significant transformative steps. The paper explores ML and AI’s role in improving FBN processes that traditionally rely on data-driven perceptions.Methodology: The research used in the paper used a multi-method approach with quantitative and qualitative elements. This research design was chosen to explore the complexity of integrating AI and ML in FBN and to obtain the impact this integration has on sourcing processes in different industries. The research results are based on a survey of 210 participants and 33 in-depth interviews.Results: The research showed that companies use FBN and see it as a beneficial approach to increasing negotiation efficacy. AI and ML integration in FBN significantly improves the negotiation process since it provides predictive modeling and real-time data analysis.Conclusion: The paper’s results align with current scientific studies highlighting the opportunities and barriers to AI and ML integration in negotiation processes. Companies must prioritize planning, education and organizational alignment for further development and optimization of these tools. With this, it is possible to fully realize the possibilities that integrating AI and ML into FBN can bring to the transformation of sourcing processes and the company’s competitiveness.
Book chapters on the topic "AI-Driven Procurement Transformation"
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Pesqueira, Antonio, and Noah Barr. "Reimagining E-Government." In Startup-Driven E-Government. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-0817-3.ch013.
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The public sector is undergoing an unprecedented transformation driven by the need for sustainable and efficient practices in waste management and procurement. This chapter explores how e-government initiatives can leverage digital symbiosis, dynamic capabilities (DC), and Six Sigma methodologies to address systemic inefficiencies and foster innovation. Integrating these frameworks enables public entities to align operations with sustainability goals through improved decision-making and resource optimization. A theoretical model demonstrates synergies between digital technologies and DC, offering practical pathways for agile and effective public waste management and procurement strategies. This chapter synthesizes literature and proposes actionable approaches, including AI-driven predictive analytics and Six Sigma tools, to operationalize sustainable innovation in public governance.
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Tariq, Muhammad Usman. "Digital Accountability." In Enhancing Public Sector Accountability and Services Through Digital Innovation. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9251-5.ch004.
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Digital accountability changes public sector transparency and service delivery by leveraging advanced technologies to improve governance, efficiency, and public trust. Innovations such as artificial intelligence, blockchain, and real-time data analytics are transforming financial reporting, fraud prevention, and decision-making procedures. Digital tools authorize governments to make data-driven policies, enhance resource allocation, and deliver inclusive and accessible services to citizens. Open data initiatives and e-government mediums foster transparency, allowing citizens to examine government performance and be involved in decision-making. Case studies emphasize effective applications, such as blockchain for secure procurement and AI-driven fraud recognition, demonstrating the potential for transformative impact. Despite issues like the digital divide, cybersecurity risks, and resource limitations, strategic investments, and inclusive policies pave the way for effectual digital transformation.
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Krishna Pasupuleti, Murali. "Blockchain for Transparent Governance: Securing Public Services in the Digital Era." In Blockchain in Government: Tools for Transparent Governance and Secure Public Services. National Education Services, 2024. http://dx.doi.org/10.62311/nesx/905704.
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Abstract: This chapter explores the transformative role of blockchain technology in enhancing transparency, security, and efficiency in governance. By addressing the challenges inherent in traditional governance systems—such as lack of transparency, inefficiencies, corruption, and data security—blockchain offers a decentralized and immutable solution that can revolutionize public service delivery. The chapter provides an in-depth analysis of the core components of blockchain-driven governance, including decentralized public records management, smart contracts, and secure digital identities. It also examines real-world case studies from Estonia, Dubai, and Brazil, demonstrating how blockchain has been successfully implemented to improve public services. Additionally, the chapter discusses the challenges and considerations in adopting blockchain for governance, such as regulatory, technical, and social issues, and explores future trends, including the integration of blockchain with AI and IoT. Ultimately, this chapter offers valuable insights for policymakers, government officials, and technology developers on leveraging blockchain to build more transparent, accountable, and secure governance systems in the digital era. Keywords: Blockchain, Transparent Governance, Public Services, Decentralized Public Records, Smart Contracts, Digital Identity, Public Procurement, Blockchain Integration, AI and IoT, Regulatory Challenges, Governance Innovation, Sustainability in Governance, Trust in Government, Digital Transformation.
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Pamisetty, Avinash. "Agentic Intelligence and Cloud-Powered Supply Chains: Transforming Wholesale, Banking, and Insurance with Big Data and Artificial Intelligence." In Deep Science Publishing. Deep Science Publishing, 2025. https://doi.org/10.70593/978-93-49307-44-5.
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In an era defined by exponential technological advancement, the convergence of artificial intelligence, big data, and cloud computing is reshaping the global economic landscape. Industries long regarded as traditional—wholesale, banking, and insurance—are undergoing rapid transformation as they adapt to the demands of a hyper-connected, data-driven world. This book explores the transformative potential of agentic intelligence—AI systems capable of autonomous decision-making—and the pivotal role of cloud-powered supply chains in driving efficiency, resilience, and innovation across sectors. As businesses face increasingly complex market dynamics, the ability to harness real-time data and deploy intelligent systems is no longer optional; it is essential for survival and growth. From the optimization of procurement and logistics in wholesale markets to risk modeling and fraud detection in banking, and from personalized policy offerings to automated claims processing in insurance, the fusion of advanced analytics and AI is unlocking unprecedented opportunities. Cloud infrastructure, meanwhile, enables scalability, security, and global accessibility, empowering organizations to reimagine traditional operations and deliver value at a new scale. This book serves as a comprehensive guide for leaders, practitioners, and scholars seeking to understand the strategic and operational implications of these emerging technologies. Through case studies, conceptual frameworks, and forward-looking analysis, we offer insights into how agentic intelligence and cloud ecosystems are not only enhancing business performance but also redefining the future of enterprise. As we stand on the brink of the next digital revolution, the pages that follow will illuminate the pathways through which technology can be harnessed not just to keep pace with change, but to lead it.
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Yogeshwaran, S., and P. Nandhini. "Green Library Metrics." In Advances in Library and Information Science. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2782-1.ch009.
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Libraries are moving towards sustainability through the adoption of modern technologies in an era of growing environmental consciousness. “Green Library Metrics” introduces an innovative framework for quantifying and mitigating the environmental impact of library operations, using the power of AI technology. This research focuses on developing standardized metrics that encompass energy efficiency, waste reduction, and sustainable procurement. The integration of AI enhances the precision of assessments, enabling data-driven decision-making for resource optimization. Energy efficiency metrics delve into electricity consumption, HVAC systems, and lighting practices, while waste reduction metrics evaluate waste management and recycling initiatives Sustainable procurement metrics focus on environmentally friendly sourcing with AI-driven supplier evaluations. This holistic approach is not only an expression of libraries' environmental responsibilities, but also a reflection on the transformative potential of AI to advance sustainable practices in community institutions.
Conference papers on the topic "AI-Driven Procurement Transformation"
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Iders-Bankovs, Martins, Viktorija Politika, Jelena Pundure, Marina Jarvis, and Maris Ziemelis. "Public procurement in age of AI: challenges and opportunities." In 24th International Scientific Conference Engineering for Rural Development. Latvia University of Life Sciences and Technologies, Faculty of Engineering and Information Technologies, 2025. https://doi.org/10.22616/erdev.2025.24.tf198.
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This study explores the transformative potential of artificial intelligence (AI) in public sector procurement, emphasizing efficiency, transparency, and regulatory compliance. By examining AI-driven innovations, the research highlights their ability to automate market analysis, optimize the preparation of technical specifications, and improve procurement process management while addressing legal and ethical considerations. A mixed-methods research approach was employed, incorporating quantitative and qualitative surveys, a detailed comparative analysis of international best practices, and an experimental “Centralized Procurement Support and Review Model”. Data collection included expert interviews, legal framework analysis, and practical tests comparing AI-supported and traditional procurement methods. The experimental findings indicate that AI integration in procurement reduces execution time by up to 50%, improves supplier selection accuracy by 25%, and strengthens compliance with procurement regulations and policies. Additionally, results from a targeted survey among procurement officers indicate a high level of readiness to adopt AI solutions, with 92% expressing interest in AI-assisted decision-making. The pilot project demonstrated a 20% reduction in administrative burden and significantly enhanced process transparency. Furthermore, practical tests revealed that AI-driven specification drafting could reduce preparation time from two hours to 30 minutes, significantly streamlining procurement operations. A comparative study of AI-based procurement solutions in the United Kingdom and Estonia suggests that the proposed model is tailored to Latvia's regulatory environment, ensuring alignment with the European Union's digital transformation objectives. Successful implementation of AI solutions in public procurement requires a practical deployment strategy, which includes enhancing employee qualifications, developing advanced data management systems, and effectively integrating regulatory requirements into procurement processes. Furthermore, this study emphasizes the importance of continuous monitoring and improvement of AI systems to ensure that procurement processes remain efficient, fair, and adaptable to evolving market dynamics and legal frameworks.
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Dreyling Iii, Richard, Regina Erlenheim, Tanel Tammet, and Ingrid Pappel. "AI Readiness Assessment for Data-driven Public Service Projects: Change Management and Human Elements of Procurement." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003894.
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As technology moves forward at a breakneck pace, governments are attempting to adopt technologies in their services that are complex and have unknown ramifications, like artificial intelligence (AI). Academic research and literature regarding change management and digital transformation discusses the necessity to have agreement within an organization on the technology project that the organization is considering adopting. One method of ensuring agreement within the socio-technical system is to conduct the appropriate planning prior to procurement. This also helps to avoid starting a project without having the required technological or human capabilities within the organization. Although the motives of private and public sector organizations are different when initiating projects, the human element of data-driven projects is still key to success. With the use of AI maturity models, feasibility studies and readiness assessment methods during the planning phase, public sector organizations exploring deployment of AI solutions in their public services could be able to avoid major pitfalls of projects that do not succeed. This paper’s contribution in to investigate and analyze existing methods of feasibility studies and readiness assessments through literature and document review to see how they may be applied to evaluating AI-related projects within the context of public service delivery. With the proper AI feasibility study and readiness assessment methods in place during the planning phase, public sector organizations exploring deployment of AI solutions in their public services will be able to avoid major pitfalls of piloting projects that do not succeed. This paper’s contribution in to investigate and analyze existing methods of feasibility studies and readiness assessments through academic literature and professional document review to see how they may be applied to evaluating AI-related projects within the context of public service delivery.
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Tiwari, Srijan, and Krishnan Balasubramanian. "Digitalizing Trust: Advancing Standardization and Traceability in NDE Workflows under NDE 4.0." In DGZfP-Jahrestagung 2025, 26.– 28. Mai 2025 in Berlin. NDT.net, 2025. https://doi.org/10.58286/31289.
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The Non-Destructive Testing (NDT) industry is expected to grow from $16.4 billion in 2024 to $35.4 billion by 2032, driven by increasing demands in infrastructure, energy, and manufacturing. Despite this, the industry remains constrained by fragmented data management, manual inspection reporting, and disjointed workflows across procurement, certification, and talent development. This article highlights the need for digital transformation in NDE workflows aligned with Industry 4.0 principles. A review of industry reports and stakeholder surveys reveals critical inefficiencies: 70% of firms experience procurement delays, 60% report certification inconsistencies, and 52% of job seekers face mismatches between skills and job roles. A key issue stems from the variability in inspection reports—shaped by inspector subjectivity, device dependence, and inconsistent data capture—which hinders traceability and audit readiness. This research advocates for the adoption of a unified, digital framework that addresses these inefficiencies through standardized inspection templates, cloud-based data traceability, and AI-powered credential validation. Compliance with global standards such as ISO 17020 and ASME Section V is emphasized. The framework promotes the use of QR codes for immutable report verification, APIs for interoperability between systems, and AI-based tools for structured CV building and role matching. Furthermore, collaboration with regulatory bodies and targeted training programs are essential to drive adoption and consistency in practice. By embedding digital infrastructure into core NDE processes, the industry can significantly improve operational efficiency, minimize errors, and enable intelligent decision-making.