AI Governance Handbook

£89.50

AI Governance Handbook

A Practical Guide for Enterprise AI Adoption

Business ethics and social responsibility Corporate governance: role and responsibilities of boards and directors Artificial intelligence

Authors: Sunil Gregory, Anindya Sircar

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Collection: Professional Practice in Governance and Public Organizations

Language: English

Published by: Springer

Published on: 14th August 2025

Format: LCP-protected ePub

ISBN: 9783031892660


Enterprise AI and Its Impact

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.

Challenges and Risks

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

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.

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