Artificial Intelligence (AI) is a category within our CIO Reference Library that focuses on developing and applying intelligent computer systems capable of understanding, learning, reasoning, and problem-solving. This category is designed to provide CIOs and other IT executives with valuable articles, documents, and resources related to AI and its integration into various industries and applications.
Key topics within the Artificial Intelligence category include:
The Artificial Intelligence category aims to provide CIOs and IT executives with the knowledge and resources they need to successfully navigate the rapidly evolving landscape of AI and its integration into their organizations’ strategies and operations.
This AI Adoption Framework outlines clear governance roles, ethical guidelines, and practical lifecycle stages—Ideation, Proof of Concept, Piloting, Scaling, and Monitoring—to help senior IT leaders adopt AI securely, ethically, and effectively across diverse industries.
This strategic AI adoption guide helps business leaders understand what AI really is, why it matters now, and how to approach it effectively. Learn how to identify suitable use cases, assess your data and readiness, and take the first steps toward real-world AI deployment—without hype, jargon, or unnecessary complexity. Perfect for executives, CIOs, and change leaders in any industry. Excellent Read! (50+ pages)
This AI strategy roadmap example shows how to build and govern AI adoption with clarity and care. Learn from real-world use cases—like audit automation, document analysis, and training programs—to create your own responsible, phased roadmap. Includes structure, risk mitigation tactics, tooling strategy, and deployment guidance.
This AI accountability framework provides a clear, actionable structure to govern and evaluate AI systems. Covering governance, data, performance, and monitoring, it equips organizations with the tools to independently verify, audit, and improve AI usage. Use it to define roles, assess bias, track model drift, and align AI systems with organizational values, laws, and ethics.
This clear, practical primer on generative AI explains how it works, where it fits, and how to think critically about its role in strategy and operations. It explains LLMs, introduces frameworks like CIDI for prompt engineering, and explores real-world use cases—from education and development to productivity and assessment redesign.
This comprehensive guide walks through building successful enterprise AI initiatives, covering how to identify high-value use cases, prioritize opportunities, and create a clear, executable plan. Packed with real-world strategies, templates, and practical advice, this guide helps IT leaders drive measurable value from AI investments.
This strategic analysis explores how artificial intelligence delivers value across sectors, what drives adoption, where investments flow, and how CIOs can lead transformation. With cross-industry case examples and data-backed insights, this is an essential guide for AI-driven business strategy.
These Tech Trends 2025 reports highlight how artificial intelligence (AI) and cutting-edge technologies are shaping industries, transforming businesses, and addressing societal challenges. Dive into key insights on AI’s evolving role, from autonomy to practical applications, and discover how businesses can leverage this for innovation, efficiency, and growth.
This AI procurement analysis addresses the main challenges organizations face in acquiring and integrating AI solutions responsibly. It explores key issues like data governance, vendor management, and ethical considerations, providing actionable recommendations to help organizations enhance their AI strategies.
This AI leadership guide offers an in-depth roadmap for integrating Generative AI within an organization. Covering strategic approaches to drive AI adoption, it explores how to align AI initiatives with business objectives, enhance workplace productivity, ensure data security, and facilitate cross-departmental collaboration.
