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Islam S: AI Prompt Playbook for Internal
Auditors

AI Prompt Playbook for Internal Auditors

250 Ready-to-Use Prompts for Audit Planning, Risk Assessment, Fraud Detection, Data Analytics, Fieldwork and Reporting

Build an AI security operating model that manages risk, strengthens governance and enables AI to scale securely. AI Risk Management is a practical guide for AI risk owners, GRC managers, AI governance managers and technology risk professionals responsible for managing the security risks of AI.Written by security expert Rafah Knight, this book shows how to make AI security operational, measurable and embedded into existing business processes. It provides practical guidance on establishing ownership and accountability for AI risk, designing effective governance structures, implementing policies and controls and managing third-party AI vendor exposure.Drawing on real-world examples from financial services, retail, the public sector and healthcare, learn how to: - Build an effective AI security operating model - Establish clear ownership and accountability for AI risk - Design AI governance policies, controls and assurance processes - Measure AI security and operational risks effectively - Manage third-party AI vendor exposure at scaleAI Security gives you the practical structures and controls to operationalize AI assurance, strengthen AI governance and support secure AI adoption at scale.Themes include: AI security, AI risk management, AI governance, GRC, AI assurance, third-party AI risk

How to Scale AI Securely

AI Risk Management

Principles of Auditing & Other Assurance Services: 2027 Release

A clear, thoughtful, and practical guide to writing in the age of generative AI. AI and Writing is an indispensable guide to composing with generative AI. Sidney I. Dobrin prepares students to use GenAI effectively, ethically, and critically--skills now essential for academic and professional success. The book tackles core questions: What tasks do these tools best support? Where do they fall short? How are they used responsibly? Dobrin focuses on durable, transferable writing practices, as well as the real-world issues raised by AI, including authorship, plagiarism, copyright, bias, and the material consequences of AI. "Provocations" boxes spark critical engagement, and each chapter concludes with a sequence of exercises and activities that move students from analysis to hands-on experimentation and reflection.

AI and Writing - Second Edition

Turn AI investment into scalable business impact by enabling your workforce to build the solutions they actually need. From AI Users to Solution Builders is a strategic guide for senior AI, technology, and transformation leaders who want to move beyond underperforming, centralized AI initiatives, and unlock real enterprise value. As organizations struggle to translate AI into measurable results, this book shows how shifting from top-down deployment to workforce-led solution building creates faster adoption, stronger ROI, and sustained innovation. Written by experienced AI leader Wei Manfredi, this book combines strategic insight with practical execution. It draws clear parallels between failed digital transformation efforts and current AI adoption challenges, while demonstrating how natural language interfaces are reshaping access to AI. By enabling non-technical professionals to design their own tools, organizations can embed AI directly into workflows, decision-making, and daily operations. You'll learn how to: - Shift from centralized AI models to workforce-driven innovation - Enable employees to build AI solutions for real workflows - Design scalable infrastructure for AI solution development - Apply change management to overcome resistance and drive adoption &gt;Featuring real-world examples from organizations including Lululemon, Google, Oracle, and JPMorgan Chase, this book provides a proven framework for embedding AI into everyday collaboration, accelerating innovation, and future-proofing your organization's competitive advantage. Themes include: AI strategy, AI adoption, workforce transformation, AI governance, enterprise AI, change management

Scaling AI Across Your Organization

From AI Users to Solution Builders

Security, Audit and Leadership Series

Turning Life’s Deficiencies into Unique Value Propositions

One Line at a Time

Loose Leaf for Principles of Auditing & Other Assurance Services: 2027 Release

A practical guide to writing with AI that puts students' questions, judgment, and learning at the center of the process. Generative AI is changing how people write and how writing is taught. How can students use it thoughtfully while developing their own ideas and abilities? Writing with AI: Literacy in the Digital Age brings the longstanding values of Writing Studies to this question, offering accessible guidance for students and their instructors. The book moves beyond treating AI as a vending machine for finished text. It shows students how to investigate a writing task, ask useful questions, evaluate responses, and revise with a purpose. Throughout, students remain responsible for what they write and for deciding whether, when, and how AI can support their work. A flexible, four-part framework, Question, Assemble, Improve, Deliver (QAID), helps students navigate writing projects, returning to earlier steps as their understanding develops. Designed for classroom use, the book includes explanations, examples, and activities that help students: Develop questions and prompts grounded in purpose, audience, and context Assess AI-generated content for accuracy, relevance, and usefulness Develop and organize ideas while making deliberate choices about revision Consider ethical questions, recognize limitations, and decide when to proceed without AI Prepare writing for readers and explain the role AI played in its development Writing with AI helps students approach an evolving technology with curiosity and critical judgment. Its focus is on the work of writing: asking questions, developing ideas, revising, and taking responsibility for what they share.

Literacy in the Digital Age

Writing with AI

Explore the mathematical foundations driving artificial intelligence and generative AI&nbsp; The Mathematics of AI: Theory and Application for Investors by Miquel Noguer Alonso provides a rigorous examination of the mathematical principles underlying modern artificial intelligence. From linear algebra and probability theory to optimization and statistical learning, this book connects foundational mathematical concepts directly to practical AI applications, offering readers a structured path through the quantitative reasoning that powers today's most advanced generative models and algorithms.&nbsp; The Mathematics of AI covers the core mathematical building blocks that drive machine learning and generative AI systems. Readers gain a thorough grounding in the theoretical frameworks behind neural networks, deep learning architectures, and generative modeling techniques. Each topic is presented with the analytical depth needed to understand how mathematical structures translate into functioning AI systems used across finance and other industries.&nbsp; Readers will also find:&nbsp; <ul> <li>Detailed coverage of linear algebra, calculus, and probability as they apply directly to modern machine learning algorithms&nbsp;</li> </ul> <ul> <li>A rigorous treatment of the optimization methods that are central to training neural networks and deep learning architectures&nbsp;</li> </ul> <ul> <li>Thorough analysis of generative model mathematics, including the underlying theory behind variational autoencoders and related techniques&nbsp;</li> </ul> <ul> <li>Practical connections between abstract mathematical frameworks and real-world artificial intelligence applications across the finance industry&nbsp;</li> </ul> <ul> <li>A carefully structured progression from foundational mathematical concepts through to advanced topics in modern generative AI&nbsp;</li> </ul> The Mathematics of AI is written for quantitative professionals, data scientists, financial engineers, and advanced students seeking a rigorous mathematical understanding of artificial intelligence. It serves anyone who needs to move beyond surface-level AI knowledge into the quantitative depth that underpins modern generative systems. &nbsp;

Theory and Application for Investors

The Mathematics of AI

Routledge Studies in Accounting

Generative and agentic AI are transforming accounting, not just by automating routine tasks, but by reshaping the structure and strategy of roles, teams, and decisionmaking across the profession.This book explores how these rapidly evolving technologies are already being applied in audits, financial reporting, advisory services, and internal controls. It offers a clear, nontechnical overview of large language models (LLMs), generative and agentic AI systems, alongside practice- based insights into adoption trends, implementation strategies, and evolving governance practices. Readers will gain practical tools to evaluate risk, ethical considerations, talent readiness, and organizational fit. The book also examines where these technologies create value, how to implement them responsibly, and what educators must do to prepare the next generation of accountants. It concludes with a forward- looking discussion on how the profession can lead, rather than simply react to this era of AI- driven change.Drawing on emerging research, professional practice insights, and interviews with firm leaders, the book translates complex developments into actionable frameworks. It bridges the gap between innovation and daily practice through realworld use cases, ethical risk analysis, and attention to the shifting priorities of practitioners, firms, educators, researchers, and regulators.Concise, timely, and practical, this guide is written for a profession in the midst of rapid transformation. It is designed to be accessible for practitioners while serving as a strategic resource for educators and firm leaders shaping the accounting workforce for the next decade. Cory Ng is an Associate Teaching Professor in the Accounting and Information Systems Department, Villanova School of Business, Villanova University, Pennsylvania, USA. Eric E. Cohen is Chief AI Officer at Cohen Computer Consulting, Pennsylvania, USA.

Implications for Practice, Education, and Research

Generative AI and Agentic Systems in Accounting

Independently published

Build Your First $1,000 System Using AI: A Step-by-Step Blueprint to Find a Niche, Get Clients, and Get Paid

AI Side Hustle

Build a resilient, high-performing organization by integrating agentic AI into strategy, operations, and decision-making. Building an Agentic Organization is a strategic guide for senior technology, AI, and business leaders responsible for delivering value from agentic AI while managing its risks. As organizations move toward human and AI collaboration at scale, leaders must balance innovation with governance, adoption, and long-term economic impact.Written by experienced AI executive Geoffrey Schaefer, this book provides a comprehensive framework for designing an agentic organization by examining strategy, governance, and economics. It explores how to define the purpose of agentic AI, align it with business objectives, and create the structures needed to support safe, scalable adoption. Addressing both opportunity and risk, it equips leaders to navigate workforce concerns, reputational exposure, and the evolving role of AI agents in enterprise environments.You'll learn how to: - Define a clear strategy for integrating agentic AI - Establish governance frameworks to manage risk and accountability - Drive workforce adoption and address resistance to AI collaboration - Assess economic value and impact of agentic AI systems - Manage reputational and operational risks from AI agent behaviorFeaturing real-world examples from Leidos, JPMorgan Chase, SY Partners, and OMA, this book provides a practical roadmap for embedding agentic AI into the fabric of your organization while protecting value, trust, and long-term performance.Themes include: agentic AI, AI strategy, AI governance, AI transformation, enterprise AI, risk management

The Strategy, Governance, and Economics of Agentic AI

Building an Agentic Organization

AI Prompt Playbook for Internal Auditors

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