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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

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

Security, Audit and Leadership Series

Why do governance failures continue to occur even when organizations have extensive controls, reporting systems, audit functions, and formal oversight structures?"Trigger-Based Governance" (TBG) argues that the problem often lies not in the absence of information, but in the transition from information to judgment. Signals may be visible, reported, and discussed without creating a legitimate basis for changing how an issue is governed.The book develops TBG as a decision architecture for making that transition explicit. It focuses on three connected questions: when ordinary monitoring is no longer sufficient, where limited governance attention can have the greatest effect, and what kind of problem is actually present. These questions are addressed through the concepts of triggers, leverage, and classification.Rather than prescribing universal thresholds or automatic escalation rules, TBG provides a framework through which organizations can define their own conditions for shifting governance posture. The book examines how this logic can operate through audit committees, internal audit, management, boards, and other oversight functions; why institutional structure alone is insufficient; and how independence, trust, organizational culture, and the legitimacy of challenge affect whether signals become actionable.It also considers how AI, analytics, expanding disclosure expectations, and global governance convergence are changing the environment in which oversight judgment is exercised.Written for directors, audit committee members, internal audit leaders, senior executives, and governance, risk, and assurance professionals, the book offers a practical way to understand not simply what organizations should monitor, but when monitoring itself should give way to deliberate governance judgment.

When Oversight Must Shift from Monitoring to Judgment

Trigger-Based Governance

Why the Companies That Win Rent the Technology and Keep What They Learn

Renting Intelligence

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

Artificial Intelligence and the Transformation of Organizations

Algorithmic Management

The honest guide to product management in the age of AI.Product management is one of the most sought-after roles in technology - and one of the most misunderstood. The blog posts make it sound like being a mini-CEO. The job descriptions promise creative ownership and outsized impact. Neither tells you what it actually feels like to do the work on a Tuesday at 2pm when the sprint is behind, the stakeholder is upset, and the data is contradicting itself.Product Manager? is the candid guide the field has been missing. Modeled on the MIT Press classic Architect? A Candid Guide to the Profession, it skips the sales pitch and goes straight to what the job is, who thrives in it, and whether you would.AI changed the job. This book explains how.The production work that used to define a PM's day - writing specs, synthesizing research, building competitive analyses - is now done in minutes. What that compression reveals is that skills were never the real job. Judgment, systems thinking, conflict navigation, and narrative gravity were always what separated the PMs who made consequential decisions from the ones who produced a lot of artifacts. AI removed the scaffolding. Now those traits are the whole job.Each chapter covers one dimension of what PMs actually do: how they think, how they navigate peers and power, how they use tools without being used by them, and what the career looks like across startup, scale-up, and large company contexts. Every chapter ends with a realistic exercise designed to surface a real answer - not whether you can pass a case interview, but whether you actually like this kind of work.Who this book is for: People seriously considering a PM career. Current PMs recalibrating for the AI era. Anyone who wants the real answer, not the marketing version.

The Traits That Survive AI and Whether You'd Like the Work

Product Manager?

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

Arthur Ford Publishing

The human's guide to Artificial Intelligence

Don't Panic AI is mostly harmless

Companies are buying, selling, and managing AI as if it were software. But AI does not behave like software—and that mismatch is quietly fracturing growth models, org structures, metrics, dashboards, and investment decisions across the global enterprise. While organizations can track what they are spending on AI models and infrastructure, few have the commercial, organizational, and operational architecture to answer the era's hardest questions: How do we accurately price and capture the value of intelligent outcomes? How do we redesign our workforce and talent models beyond naive headcount cuts? How do we prove, measure, and scale real return across an enterprise built for human-operated software, not intelligent systems? In Quantware, technology pricing strategist Esra Kucukciftci reveals that these enterprise roadblocks are not temporary growing pains. They are the evidence of a fundamental economic paradigm shift from software to quantware: a new system of value creation that is dynamic, distributed, and continually evolving. This paradigm shift fundamentally rewrites the commercial and operational models. Where software sells tools, static features, and user access, quantware commercializes verifiable outcomes. It redefines what customers pay for, how providers prove performance, how contracts assign risk and revenue, and how enterprises evaluate true return on intelligent systems (ROIS). Kucukciftci outlines the blueprint for redesigning the enterprise around this post-software reality. She details the transition from Software-as-a-Service (SaaS) to Resolution-as-a-Service (RaaS), along with new approaches to AI outcome economics and dynamic contracts. Crucially, she introduces a new organizational design—The Dynamic Firm— built to align human talent with machine delivery alongside the PROVE framework to govern intelligent value creation at scale. Drawing on her experience advising global enterprise technology companies, private equity portfolios, and high-growth ventures, Kucukciftci addresses both sides of the post-software economy: the technology providers building AI offerings, and the enterprise leaders tasked with buying, implementing, and governing them. For leaders who know AI will reshape their business but lack the commercial, organizational, and operational models for what comes next, Quantware provides the language, architecture, and practical playbook to compete and win in the post-software era.

The Post-Software and Post-Product Era in Business

Quantware

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

Hart Studies in European Criminal Law

This book offers a comprehensive legal analysis of the urgent challenges posed by deepfakes, focusing on the restrictive measures proposed or introduced to address their related harms. Readers will gain a clear understanding of the harms associated with deepfakes - especially in areas like non-consensual sexualised content and political disinformation - and how criminal and digital regulatory systems are attempting to respond. From a criminal law perspective, the book offers a dual-level critique. On the one hand, criminal law is invoked for its expressive and symbolic function, particularly in response to the discriminatory and gender-based harms often associated with deepfakes, as well as the broader need to prevent systemic risks to democratic society when it comes to electoral manipulation and freedom of thought. Here, criminal law would play a vital role in affirming societal condemnation of such conduct and in acknowledging the serious impact on victims. On the other hand, its use is increasingly entangled with emerging frameworks of digital regulation, taking on a more instrumental role in defining illegal content and reinforcing standards shaped primarily by private platforms and regulatory bodies. This dual function raises fundamental questions about the legitimacy and efficacy of using criminal law-the most coercive form of state power-for purposes that extend beyond its traditional scope. Additionally, the book explores regulatory measures aimed at controlling deepfakes, considered both as AI-generated content and as harmful online material. Discussions around content moderation, transparency duties-such as labelling and watermarking-and safety by design measures are gaining attention globally, with the European Union's Digital Services Act and AI Act leading the way. The book's primary goal is to bridge the two worlds of criminal law and digital regulation through a careful and critical analysis, making it a valuable resource for a broad audience.

Harmful AI-generated Content between Criminal Law and Digital Regulation

Addressing Deepfakes

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

AI Prompt Playbook for Internal Auditors

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