Deploying Ai In The Enterprise
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Deploying AI in the Enterprise
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
Author: Dr. Joshua Eckroth
language: en
Publisher: Packt Publishing Ltd
Release Date: 2018-12-31
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
Author: Arthur Guseni Oliver Mutambara
language: en
Publisher: Springer Nature
Release Date: 2025-07-01
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.