AI Governance Handbook A Practical Guide for Enterprise AI Adoption /

Bibliographic Details
Main Authors: Gregory, Sunil (Author), Sircar, Anindya (Author)
Corporate Author: SpringerLink (Online service)
Summary:XXVII, 271 p. 12 illus.
text
Language:English
Published: Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edition:1st ed. 2025.
Series:Professional Practice in Governance and Public Organizations,
Subjects:
Online Access:https://doi.org/10.1007/978-3-031-89266-0
Format: Electronic Book

MARC

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505 0 |a Chapter 1: Artificial Intelligence: A foundation -- Chapter 2: Artificial Intelligence and the Rule of Law -- Chapter 3: Enterprise AI: Strategic Guardrail -- Chapter 4: Enterprise AI: Ethical Guardrail -- Chapter 5: Enterprise AI: Legal Guardrail -- Chapter 6: Enterprise AI: Regulatory Guardrail -- Chapter 7: Conclusion. 
520 |a Enterprise AI represents a transformative moment in technology, empowering businesses to unlock the potential of data, automation, and advanced analytics. It drives innovation, streamlines operations, and amplifies competitiveness in an increasingly digital economy. Yet, as promising as this technology is, adopting Enterprise AI is no simple feat. It demands a strategic alignment of AI initiatives with organizational goals while addressing many complex risks and challenges. Businesses face a new frontier of operational dilemmas, from algorithmic bias and data privacy concerns to the legal and ethical quandaries of AI-generated content. Questions of accountability for AI actions, intellectual property rights, and the threat of data laundering or AI hallucinations further complicate the landscape. Amid these challenges, enterprises are tasked with navigating a "pre-regulatory era," where global authorities are racing to establish policies and frameworks for a trustworthy and lawful AI ecosystem. The AI Governance Handbook is a comprehensive guide tailored for stakeholders at the forefront of AI adoption—executives, managers, data scientists, engineers, and compliance professionals. This essential resource provides the knowledge, tools, and strategies to lead organizations through the complexities of implementing AI responsibly and effectively. Packed with actionable insights, the handbook explores critical topics such as aligning AI strategies with organizational objectives, managing ethical dilemmas, adhering to emerging regulations, and fostering transparency in AI operations. It offers readers a roadmap to build a resilient and dependable AI framework prioritizing fairness, accountability, and innovation. 
532 8 |a Accessibility summary: This PDF has been created in accordance with the PDF/UA-1 standard to enhance accessibility, including screen reader support, described non-text content (images, graphs), bookmarks for easy navigation, keyboard-friendly links and forms and searchable, selectable text. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. Please note that a more accessible version of this eBook is available as ePub. 
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