Ulteriori informazioni
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.
Sommario
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.
Info autore
Dr. Sunil Gregory is a leader with over two decades of experience in digital transformation, technology consulting, and business development. He has a proven track record of driving large-scale technology transformation initiatives for Fortune 500 clients across industries. Sunil is passionate about the role of AI in shaping the future of societies. He consults Technology companies on setting up AI Governance Offices, as a dedicated function to overseeing Enterprise AI adoption.
Prof. (Dr.) Anindya Sircar is currently IPR Chair Professor at NALSAR University of Law, Hyderabad, engaged in consulting, strategizing, teaching, and training programs. He is an Industry veteran in setting up and streamlining all IP activities in multiple industry domains. Formerly, he was the Global IPR Head of Biocon and Head of IP Cell at Infosys. He has figured in Lex Witness's Hall of Fame – Top 50 as a prominent player in India's legal sector in 2010. He was featured in IAM Strategy 300 – The World's Leading IP Strategists from 2017 to 2023.
Riassunto
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.
