Chapter

Artificial Intelligence (AI) – Page 2

Featured image for Structured Framework for AI Accountability: Governance, Data, Performance, Monitoring

Structured Framework for AI Accountability: Governance, Data, Performance, Monitoring

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.

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Generative AI Primer: Foundations, Frameworks, and Strategic Action

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.

How to Build Successful Enterprise AI Initiatives: A Step-by-Step Guide - featured iage

How to Build Successful Enterprise AI Initiatives: A Step-by-Step Guide

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.

Image: An Executive Overview of Use Cases, Strategy, and Value of AI in the Enterprise

A Strategic Analysis of Adoption, Investment, and Impact of AI in Business

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.

Tech Trends 2025: Pioneering AI, Emerging Trends, and Industry Transformations - featured image

Tech Trends 2025: Pioneering AI, Emerging Trends, and Industry Transformations

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.

AI Procurement Analysis: Overcoming Challenges and Enabling Responsible Adoption - featured image

AI Procurement Analysis: Overcoming Challenges and Enabling Responsible Adoption

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.

Leading with AI: How CIOs Can Drive Generative AI Adoption and Innovation - featured image

Leading with AI: How CIOs Can Drive Generative AI Adoption and Innovation

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.

2024 Tech Trends Analysis: AI, Innovation, and Business Transformation - featured image

2024 Tech Trends Analysis: AI, Innovation, and Business Transformation

This 2024 tech trends analysis explores the rise of AI-driven business models, the potential of spatial computing, and the critical need for responsible AI governance. The report provides insights into the evolving landscape of data privacy and cybersecurity, offering actionable recommendations for businesses navigating the AI revolution.

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The Future of Work with AI: An Inclusive Approach

This playbook offers a roadmap for organizations to harness the power of AI while prioritizing worker well-being and inclusion. It addresses key concerns like job displacement, bias, and the digital divide, providing practical guidance for a just transition to an AI-powered future of work.

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