Embedding Artificial Intelligence Into Erp Software
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Embedding Artificial Intelligence into ERP Software
This book explains how to embed artificial intelligence in digitized business processes of ERP software by solving the two related substantial challenges: how can artificial intelligence be systematically integrated into ERP business processes for ease of consumption, and how can artificial intelligence be made enterprise-ready by covering ERP qualities like compliance, lifecycle management, extensibility, or scalability? As a general introduction, the first part of this book takes the reader through a historical journey towards intelligent ERP systems. In addition, reference processes and a reference architecture for ERP systems are proposed which build the foundation for the suggested subsequent solution concept, including a method for operationalizing intelligence for ERP business processes. Subsequently, in the second part detailed concepts of embedding artificial intelligence into ERP software are proposed. In this context the suggested solution architecture is depicted, and specific topics are resolved like data integration, model validation, explainability, data protection and privacy, model degradation and performance. In the last part an implementation framework is suggested which enables the previously introduced concepts and harmonizes the development and operations of artificial intelligent ERP applications. This part concludes with case studies considering artificial intelligence scenarios of SAP S/4HANA in the areas of logistics, finance and sales which apply the defined solution approach and shows its real-world feasibility. This book is written for professionals who want to implement (as developers) or exploit (as business analysts or consultants) or consider/plan the implementation/exploitation (as managers) of artificial intelligence in business information systems.
International Conference on Advanced Intelligent Systems for Sustainable Developent (AI2SD 2024)
This book provides a dynamic platform for exploring groundbreaking advancements in intelligent systems for sustainable development. It offers readers’ access to the latest technologies and innovative solutions that address global challenges. Bringing together leading academics, pioneering researchers, and industry leaders fosters knowledge exchange across various fields such as health, education, agriculture, energy, and security. It enables readers to gain valuable insights, build strategic partnerships, and contribute to shaping a more sustainable future. This book bridges scientific research with practical applications and is ideal for researchers, practitioners, and decision-makers, driving progress across multiple disciplines.
Ensuring Secure and Ethical STM Research in the AI Era
As artificial intelligence (AI) is integrated into scientific, technical, and medical (STM) research, ensuring security and ethical standards becomes more critical. AI tools play a transformative role in data analysis and research methods, to peer reviews and publication, raising complex questions around data privacy, algorithmic bias, intellectual property, and research integrity. The rapid pace of innovation also introduces risks like the misuse of generative models, vulnerabilities in automated systems, and challenges in maintaining transparency and accountability. To navigate this landscape, a proactive approach is essential, combining governance frameworks, interdisciplinary collaboration, and ethical oversight. By prioritizing these elements, the scientific community can harness the full potential of AI while safeguarding integrity and societal trust in STM research. Ensuring Secure and Ethical STM Research in the AI Era explores the convergence of AI, ethics, and cybersecurity within the context of STM innovation. It examines addresses the secure and ethical deployment of AI in scientific research, development, and discovery. This book covers topics such as biomedicine, cloud technology, and data privacy, and is a useful resource for business owners, computer engineers, academicians, researchers, and scientists.