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Deploying Ai In The Enterprise


Deploying Ai In The Enterprise
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Deploying Ai In The Enterprise


Deploying Ai In The Enterprise
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Author : Eberhard Hechler
language : en
Publisher: Apress
Release Date : 2020-09-30

Deploying Ai In The Enterprise written by Eberhard Hechler and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-30 with Computers categories.


Your company has committed to AI. Congratulations, now what? This practical book offers a holistic plan for implementing AI from the perspective of IT and IT operations in the enterprise. You will learn about AI’s capabilities, potential, limitations, and challenges. This book teaches you about the role of AI in the context of well-established areas, such as design thinking and DevOps, governance and change management, blockchain, and quantum computing, and discusses the convergence of AI in these key areas of the enterprise. Deploying AI in the Enterprise provides guidance and methods to effectively deploy and operationalize sustainable AI solutions. You will learn about deployment challenges, such as AI operationalization issues and roadblocks when it comes to turning insight into actionable predictions. You also will learn how to recognize the key components of AI information architecture, and its role in enabling successful and sustainable AI deployments. And you will come away with an understanding of how to effectively leverage AI to augment usage of core information in Master Data Management (MDM) solutions. What You Will Learn Understand the most important AI concepts, including machine learning and deep learning Follow best practices and methods to successfully deploy and operationalize AI solutions Identify critical components of AI information architecture and the importance of having a plan Integrate AI into existing initiatives within an organization Recognize current limitations of AI, and how this could impact your business Build awareness about important and timely AI research Adjust your mindset to consider AI from a holistic standpoint Get acquainted with AI opportunities that exist in various industries Who This Book Is For IT pros, data scientists, and architects who need to address deployment and operational challenges related to AI and need a comprehensive overview on how AI impacts other business critical areas. It is not an introduction, but is for the reader who is looking for examples on how to leverage data to derive actionable insight and predictions, and needs to understand and factor in the current risks and limitations of AI and what it means in an industry-relevant context.



Ai Blueprints


Ai Blueprints
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Author : Dr. Joshua Eckroth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-12-31

Ai Blueprints written by Dr. Joshua Eckroth and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-31 with Computers categories.


The essential blueprints and workflow you need to build successful AI business applications Key FeaturesLearn and master the essential blueprints to program AI for real-world business applicationsGain insights into how modern AI and machine learning solve core business challengesAcquire practical techniques and a workflow that can build AI applications using state-of-the-art software librariesWork with a practical, code-based strategy for creating successful AI solutions in your businessBook Description AI Blueprints gives you a working framework and the techniques to build your own successful AI business applications. You’ll learn across six business scenarios how AI can solve critical challenges with state-of-the-art AI software libraries and a well thought out workflow. Along the way you’ll discover the practical techniques to build AI business applications from first design to full coding and deployment. The AI blueprints in this book solve key business scenarios. The first blueprint uses AI to find solutions for building plans for cloud computing that are on-time and under budget. The second blueprint involves an AI system that continuously monitors social media to gauge public feeling about a topic of interest - such as self-driving cars. You’ll learn how to approach AI business problems and apply blueprints that can ensure success. The next AI scenario shows you how to approach the problem of creating a recommendation engine and monitoring how those recommendations perform. The fourth blueprint shows you how to use deep learning to find your business logo in social media photos and assess how people interact with your products. Learn the practical techniques involved and how to apply these blueprints intelligently. The fifth blueprint is about how to best design a ‘trending now’ section on your website, much like the one we know from Twitter. The sixth blueprint shows how to create helpful chatbots so that an AI system can understand customers’ questions and answer them with relevant responses. This book continuously demonstrates a working framework and strategy for building AI business applications. Along the way, you’ll also learn how to prepare for future advances in AI. You’ll gain a workflow and a toolbox of patterns and techniques so that you can create your own smart code. What you will learnAn essential toolbox of blueprints and advanced techniques for building AI business applicationsHow to design and deploy AI applications that meet today’s business needsA workflow from first design stages to practical code solutions in your next AI projectsSolutions for AI projects that involve social media analytics and recommendation enginesPractical projects and techniques for sentiment analysis and helpful chatbotsA blueprint for AI projects that recommend products based on customer purchasing habitsHow to prepare yourself for the next decade of AI and machine learning advancementsWho this book is for Programming AI Business Applications provides an introduction to AI with real-world examples. This book can be read and understood by programmers and students without requiring previous AI experience. The projects in this book make use of Java and Python and several popular and state-of-the-art opensource AI libraries.



Deploying Artificial Intelligence To Achieve The Un Sustainable Development Goals


Deploying Artificial Intelligence To Achieve The Un Sustainable Development Goals
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Author : Arthur Guseni Oliver Mutambara
language : en
Publisher: Springer Nature
Release Date : 2025-07-01

Deploying Artificial Intelligence To Achieve The Un Sustainable Development Goals written by Arthur Guseni Oliver Mutambara and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Technology & Engineering categories.


This book provides research insights into how Artificial Intelligence (AI) can be used to achieve the UN’s Sustainable Development Goals (SDGs) – 17 interconnected goals designed to address the world’s most pressing challenges by 2030. It reviews the SDGs and discusses why progress has been mixed and uneven across different countries, regions and goals. The book posits that attaining the SDGs will depend on enhanced global cooperation, increased funding, improved infrastructure, public-private partnerships, regional/continental integration, addressing the climate crisis, inclusive economic transformation, and visionary leadership. More specifically, the publication advocates leveraging innovative and transformative technologies, particularly the deployment of AI. The research acknowledges the risks of digital imperialism, data colonialism and technological exclusion, especially in emerging and least industrialised economies. Hence, in deploying AI to achieve the SDGs, the book puts a premium on decoloniality in AI systems and democratising AI technology. Provides a critique of the current SDGs approach by reframing the goals as a comprehensive risk assessment of humanity’s most pressing threats in the 21st century; Features broad and holistic interventions to accelerate the attainment of the SDGs; Provides a comprehensive but accessible introduction to AI concepts and advanced innovations such as AlphaFold, ChatGPT-4, DeepSeek-R1, Grok 3, and autonomous vehicles (drones and driverless cars); Discusses the AI strategies of leading economies and assesses the impact of AI on geopolitics; Provides a comprehensive critique of global AI efforts by the UN and African Union, while proffering alternative paradigms and frameworks; Presents the enablers, drivers and strategic framework of AI deployment to achieve the SDGs; Develops and presents details of six distinct but related components of a novel Strategic Framework for developing and adopting AI – Vision, Strategy, Policy, Governance, Legislation/Regulations, and Implementation Matrix; Outlines specific ways that AI can be deployed to achieve each of the 17 SDGs and reviews seven countries’ experiences; Explores an innovative, forward-looking, and technology-driven framework for equitable global socio-economic transformation to succeed the SDGs post-2030.



Responsible Ai In The Enterprise


Responsible Ai In The Enterprise
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Author : Adnan Masood
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-07-31

Responsible Ai In The Enterprise written by Adnan Masood and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-31 with Computers categories.


Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfalls Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn ethical AI principles, frameworks, and governance Understand the concepts of fairness assessment and bias mitigation Introduce explainable AI and transparency in your machine learning models Book DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations. By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.What you will learn Understand explainable AI fundamentals, underlying methods, and techniques Explore model governance, including building explainable, auditable, and interpretable machine learning models Use partial dependence plot, global feature summary, individual condition expectation, and feature interaction Build explainable models with global and local feature summary, and influence functions in practice Design and build explainable machine learning pipelines with transparency Discover Microsoft FairLearn and marketplace for different open-source explainable AI tools and cloud platforms Who this book is for This book is for data scientists, machine learning engineers, AI practitioners, IT professionals, business stakeholders, and AI ethicists who are responsible for implementing AI models in their organizations.



Enterprise Artificial Intelligence Transformation


Enterprise Artificial Intelligence Transformation
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Author : Rashed Haq
language : en
Publisher: John Wiley & Sons
Release Date : 2020-06-23

Enterprise Artificial Intelligence Transformation written by Rashed Haq and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-23 with Business & Economics categories.


Enterprise Artificial Intelligence Transformation AI is everywhere. From doctor's offices to cars and even refrigerators, AI technology is quickly infiltrating our daily lives. AI has the ability to transform simple tasks into technological feats at a human level. This will change the world, plain and simple. That's why AI mastery is such a sought-after skill for tech professionals. Author Rashed Haq is a subject matter expert on AI, having developed AI and data science strategies, platforms, and applications for Publicis Sapient's clients for over 10 years. He shares that expertise in the new book, Enterprise Artificial Intelligence Transformation. The first of its kind, this book grants technology leaders the insight to create and scale their AI capabilities and bring their companies into the new generation of technology. As AI continues to grow into a necessary feature for many businesses, more and more leaders are interested in harnessing the technology within their own organizations. In this new book, leaders will learn to master AI fundamentals, grow their career opportunities, and gain confidence in machine learning. Enterprise Artificial Intelligence Transformation covers a wide range of topics, including: Real-world AI use cases and examples Machine learning, deep learning, and slimantic modeling Risk management of AI models AI strategies for development and expansion AI Center of Excellence creating and management If you're an industry, business, or technology professional that wants to attain the skills needed to grow your machine learning capabilities and effectively scale the work you're already doing, you'll find what you need in Enterprise Artificial Intelligence Transformation.



Enterprise Ai For Dummies


Enterprise Ai For Dummies
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Author : Zachary Jarvinen
language : en
Publisher: John Wiley & Sons
Release Date : 2020-08-17

Enterprise Ai For Dummies written by Zachary Jarvinen and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-17 with Business & Economics categories.


Master the application of artificial intelligence in your enterprise with the book series trusted by millions In Enterprise AI For Dummies, author Zachary Jarvinen simplifies and explains to readers the complicated world of artificial intelligence for business. Using practical examples, concrete applications, and straightforward prose, the author breaks down the fundamental and advanced topics that form the core of business AI. Written for executives, managers, employees, consultants, and students with an interest in the business applications of artificial intelligence, Enterprise AI For Dummies demystifies the sometimes confusing topic of artificial intelligence. No longer will you lag behind your colleagues and friends when discussing the benefits of AI and business. The book includes discussions of AI applications, including: Streamlining business operations Improving decision making Increasing automation Maximizing revenue The For Dummies series makes topics understandable, and as such, this book is written in an easily understood style that's perfect for anyone who seeks an introduction to a usually unforgiving topic.



Ai Deployment And Adoption In Public Administration And Organizations


Ai Deployment And Adoption In Public Administration And Organizations
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Author : Sart, Gamze
language : en
Publisher: IGI Global
Release Date : 2025-04-02

Ai Deployment And Adoption In Public Administration And Organizations written by Sart, Gamze and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-02 with Political Science categories.


The deployment of AI in public administration and organizations has the potential to revolutionize decision-making, improve efficiency, and enhance service delivery. By automating routine tasks and analyzing vast amounts of data, AI can streamline operations, reduce costs, and enable faster responses to societal challenges. Its adoption also raises critical questions about ethics, transparency, and inclusivity, as organizations must ensure AI technologies are implemented responsibly and equitably. Addressing these challenges can pave the way for more effective governance and innovation, benefiting society at large. AI Deployment and Adoption in Public Administration and Organizations explores the transformative potential of AI in public administration and organizational settings, highlighting its role in enhancing efficiency, decision-making, and service delivery. It delves into practical applications, case studies, and frameworks that guide organizations in leveraging AI to address complex challenges and improve outcomes. Covering topics such as customer relationship management systems, machine learning, and unemployment, this book is an excellent resource for public administration professionals, organizational leaders, policymakers, researchers, technology specialists, academicians, and more.



Ai Driven Enterprise Architecture From Data Engineering To Generative Ai 2025


Ai Driven Enterprise Architecture From Data Engineering To Generative Ai 2025
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Author : Author:1- Bhanuvardhan Nune, Author:2-Dr. Gaurav Kumar
language : en
Publisher: RAVEENA PRAKASHAN OPC PVT LTD
Release Date :

Ai Driven Enterprise Architecture From Data Engineering To Generative Ai 2025 written by Author:1- Bhanuvardhan Nune, Author:2-Dr. Gaurav Kumar and has been published by RAVEENA PRAKASHAN OPC PVT LTD this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.


PREFACE In the rapidly evolving landscape of technology, enterprises are increasingly turning to artificial intelligence (AI) to drive innovation, efficiency, and growth. The integration of AI into enterprise architecture has shifted from a trend to an essential strategy for businesses looking to maintain a competitive edge. AI-Driven Enterprise Architecture: From Data Engineering to Generative AI is written to explore the transformative impact of AI across all layers of enterprise systems, from data engineering and analytics to innovative generative AI technologies that are reshaping industries. In today’s digital age, businesses face an explosion of data that is often unstructured, decentralized, and sold. For AI to truly revolutionize enterprise systems, there must be a solid architecture that not only supports large-scale data processing but also enables the seamless integration of AI technologies into every corner of the organization. This book takes a comprehensive approach to AI-driven enterprise architecture, focusing on the technical, strategic, and operational challenges and opportunities associated with AI adoption. The journey from data engineering to generative AI requires a solid foundation of data management and processing capabilities. The book begins by discussing the critical importance of data engineering, the practice of building robust systems for collecting, storing, and transforming data into actionable insights. Understanding how to build and maintain efficient data pipelines, databases, and data lakes forms the backbone of AI integration in an enterprise. This foundational understanding sets the stage for deploying machine learning (ML) models and AI-driven tools, which require sophisticated infrastructure to function on a scale. The integration of machine learning and AI models into enterprise architecture is the central focus of this book. As businesses recognize the value of AI in improving decision-making, automation, and customer experiences, this book guides readers through how to implement AI across multiple enterprise functions. From predictive analytics and automation to natural language processing (NLP) and computer vision, we will examine how these AI technologies interact with existing enterprise systems to create smarter, more efficient business operations. One of the most exciting and rapidly advancing fields in AI is generative AI—a technology that can create new data, designs, or content based on learned patterns. Generative AI tools like GPT-3, DALL-E, and stable diffusion models are now being used to generate text, images, code, and even video. The power of these models lies in their ability to produce new, high-quality content that can be harnessed for marketing, customer engagement, product development, and innovation. This book explores how generative AI fits within the broader enterprise architecture and how businesses can leverage these capabilities to unlock new value streams, foster creativity, and enhance productivity. AI-Driven Enterprise Architecture: From Data Engineering to Generative AI is designed for business leaders, data engineers, architects, and AI practitioners who are looking to understand the potential of AI in their organizations. Through real-world case studies, best practices, and technical insights, this book aims to provide a holistic view of how AI-driven enterprise architecture can deliver long-term strategic value. The book also delves into the challenges and ethical considerations of AI implementation, particularly with regard to data privacy, algorithmic bias, and governance, ensuring that AI is deployed responsibly and sustainably. As businesses embrace AI technologies, it is clear that the future of enterprise architecture will be driven by data-centric, AI-powered models that allow organizations to be more adaptive, responsive, and innovative. This book offers a roadmap for navigating that future, helping organizations transform their architecture to support the AI-driven, intelligent enterprise of tomorrow. We invite you to embark on this journey through the evolving world of AI-driven enterprise architecture, where the combination of data engineering, machine learning, and generative AI is shaping the future of businesses across the globe. Authors



Embedding Artificial Intelligence Into Erp Software


Embedding Artificial Intelligence Into Erp Software
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Author : Siar Sarferaz
language : en
Publisher: Springer Nature
Release Date : 2024-05-30

Embedding Artificial Intelligence Into Erp Software written by Siar Sarferaz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-30 with Computers categories.


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.



Artificial Intelligence In Business


Artificial Intelligence In Business
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Author : Pavankumar Gurazada & Seema Gupta
language : en
Publisher: Vikas Publishing House
Release Date :

Artificial Intelligence In Business written by Pavankumar Gurazada & Seema Gupta and has been published by Vikas Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.


Artificial Intelligence in Business is transforming the way organizations operate—driving innovation, increasing efficiency, and enabling smarter, data-driven decision making. Yet for many professionals and students, the gap between complex technical concepts and practical business applications can feel overwhelming. This book bridges that gap with clarity, relevance, and purpose. Designed for MBA students, business leaders, and aspiring AI practitioners, Artificial Intelligence in Business cuts through the hype to provide a grounded, accessible, and actionable guide to real world AI. From foundational principles like machine learning and deep learning to advanced applications in marketing, finance, supply chain, and HR, each chapter offers practical insights supported by real-world use cases and code implementations. Whether you're aiming to enhance customer engagement, streamline operations, or manage risk more effectively, this book equips you with the knowledge and tools to apply AI strategically in a business context.