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Purpose: In the contemporary knowledge economy, organisations mainly derive a competitive advantage by leveraging their intangible assets. Competent and motivated employees are the primary strategic resources to attain innovation and business continuity. Consequently, workplace learning and development (L&D) is at the forefront of the human resource management (HRM) discipline. At the same time, with the changing technology landscape, organisations are transforming their L&D function to be sustainable. Against this backdrop, the main objective of this chapter is to illustrate how artificial intelligence (AI) contributes to a specific HRM sub-function, that is, workplace L&D.

Design/Methodology/Approach: Grounded on intense scrutiny of literature, this chapter construes AI as intelligent machines that think and work like humans and have the potential for enhancing learning processes. Different themes have been presented, which suggest the capabilities of AI systems to fuel employee learning at the workplace.

Findings: Findings demonstrate that AI-enabled workplace learning is rooted in improved knowledge management (KM) capabilities, developmental feedback, personalised education, learning for a diverse pool of learners, virtual mentoring, and chatbot-based learning.

Research Limitations/Implications: This conceptual study suffers from a lack of empirical support.

Practical Implications: This chapter contributes to expanding scholarship on integrating AI and the HRM domain, particularly L&D. Further, it highlights how L&D professionals should integrate AI into employee learning journeys to evoke effective learning outcomes.

Originality/Value: This chapter provides a gestalt approach to integrating AI with employee L&D

This study proposes targeted modernization of the Department of Defense (DoD's) Joint Forces Ammunition Logistics information system by implementing the optimized innovative information technology open architecture design and integrating Radio Frequency Identification Device data technologies and real-time optimization and control mechanisms as the critical technology components of the solution. The innovative information technology, which pursues the focused logistics, will be deployed in 36 months at the estimated cost of $568 million in constant dollars. We estimate that the Systems, Applications, Products (SAP)-based enterprise integration solution that the Army currently pursues will cost another $1.5 billion through the year 2014; however, it is unlikely to deliver the intended technical capabilities.

The present study discusses the benefits and importance of sociotechnical thinking for the integration of industry 4.0 (I4.0), and their subsequent usefulness in analyzing the value-added activities and related quality issues, and their implications in the quality 4.0 (Q4.0), product-service systems (PSS) in the organization level/complex systems in the era of I4.0. I4.0 pushed the traditional manufacturing models toward product-service systems; for this transition, social and economic factors influence more, and technological advancements are going more rapidly than the social developments needed for the transition. The integration of social-technical system perspective with I4.0 technologies adoption would improve the value cocreation of PSS. The balance among the sociotechnical systems theory (STST) and I4.0 technologies are necessary for production and logistics organizations. This can be attained by sociotechnical systems thinking because it gives a comprehensive overview for integrating I4.0 and related quality issues in the production and logistics service systems.

In the age of data, enterprises have more information available to them than ever before, yet many organizations still struggle to harness its full potential. In this chapter, we explore the data value equation and how it translates into an end-to-end data management strategy that enables enterprises to turn their business data into business value. Starting with the concept of “amount,” the chapter looks at the challenge of storing big data. The second element of the equation relates to the “quality” of data and its fundamental role in enabling confident decision-making. Finally, the third element of the equation focuses on the importance of the consumption of that data in analytics tools that not only visualize the data but proactively help users uncover, explore, and act on insights. By yielding the highest value at every stage of this equation, businesses can see more, understand more, and do more with their data.

Food supply chain transparency and traceability is very important to address the issue regarding quality and safety. In traditional tracing system, with increasing the complexity of supply chain making product recalls difficult to manage and putting human lives at risk. To eliminate such types of risks, blockchain technology gives more efficient and reliable system for food tracing. Recently, there is an exponential rise in adoption of blockchain technology and most disparate IOT (Internet of things) devices in agriculture and food supply chain. It is an evolving technology that comforts the food supply chains by providing transparent data records and manage the food movement in the chain using distributed (P2P) network. That is more secured and there's no need for third party verifications. Our focus in this research will be on the Indian wheat supply chain and issues related to food losses caused by a lack of transparency and traceability. In order to improve the transparency of the wheat supply chain, we created an end-to-end smart wheat supply chain solution that combines blockchain technology, NFC tags, IoTs, and smart contracts. The solution is supported by entity relationship diagrams, information and money flow sequence diagrams, and a blockchain network diagram. We also used a security algorithm and the “NFC-Tag writer by NXP” program to validate and assess our system. This work could serve as a springboard for more in-depth research in this area. Depending on the existing situation in the industry, this research can also advise corporate procedures to deploy blockchain-based applications in the supply chain and logistics industry.