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Magwenjere: Governing the AI Machine

Governing the AI Machine

The G.A.M.E. Framework for Enterprise Risk and Board Accountability

AI Firing Freeze: Why fully-staffed organizations thrive in an AI-driven economy challenges one of the biggest assumptions in modern business; that artificial intelligence capabilities should automatically lead to workforce reduction.

As organizations race to implement AI chatbots, AI agents and agentic AI solutions, many are planning layoffs and hiring freezes in pursuit of short-term cost savings. But what if that strategy is fundamentally flawed?

Drawing on proven patterns of technological transformation, innovation, market expansion and real-world operational risks, AI Firing Freeze argues that the organizations most likely to thrive in an AI-driven economy will not be those that aggressively reduce headcount, but those that retain, repurpose and upskill their teams to work alongside AI for exponential results.

AI Firing Freeze shows you how to combine the strengths of AI with the human insight, critical thinking, experience, curation and governance your organization needs for success.

This book gives you clear guidance for maximizing the value - and minimizing the risk - of your AI solutions. It shows you how to leverage high-powered hybrid human and AI teams to run your operations; how to identify the AI initiatives that deliver the greatest ROI; how to inventory, monitor and manage all of your AI initiatives; how to secure your investments with AI governance; and how to ensure that every AI solution has the right level of supervision and human intervention to protect your organization.

Inside, readers will discover:Why human vision, creativity, judgement, quality control and expertise are critical differentiators in an AI-driven economy
The hidden operational, financial, reputational and liability exposures of overreliance on AI with insufficient human involvement
What is causing the "AI boomerang effect" and how to avoid that trap
A step-by-step process for building your AI-empowered organization
Role-specific guidance on leveraging your current teams 
Tools for realistic resource planning with hybrid human and AI teams
How to establish an AI governance framework that helps your organization scale safely and sustainably.





AI Firing Freeze inspires your organization to see beyond the initial allure of using AI capabilities for quick overhead reductions. It shows you how to combine AI and human strengths to superpower your teams, unlock innovation, expand your markets, increase resilience and create sustainable long-term growth.

Before you downsize for the promise of AI, you need to read this book.

Why fully-staffed organizations thrive in an AI-driven economy

AI Firing Freeze

Kirkus Reviewed Amazon #1 International Bestseller
"...clear thinking about AI and large language models...Get it!" 
- Kirkus Reviews

From former Apple, Intuit, and eBay executive Dan Leiva comes a leadership playbook for scaling human potential in an AI-driven world.

Artificial intelligence is transforming how work gets done. But as organizations accelerate automation, many leaders are discovering an unintended consequence: trust erodes, judgment disappears, and accountability becomes unclear.

In AMPLIFIED: The Operator's Playbook for Scaling Human Potential in an AI World, veteran technology executive Dan Leiva delivers a practical leadership framework for navigating the hybrid future of work-where humans and intelligent machines operate side by side. Drawing on decades of experience leading large-scale operations inside some of the world's most influential technology companies, Leiva moves the conversation beyond tool adoption and hype to focus on what truly matters: intentional system design for organizations that must operate with both speed and wisdom.

As AI tools rapidly increase efficiency and decision velocity, organizations face a deeper challenge. Automation can quietly erode human responsibility, blur decision authority, and weaken the judgment that resilient organizations depend on. AMPLIFIED confronts this reality head-on and provides leaders with a disciplined approach for ensuring that technology strengthens-not replaces-the human capabilities that make organizations adaptable and trustworthy.

This book is not about how to use AI faster.

It is about how to design organizations that scale judgment, trust, and responsibility alongside technology.
Through clear models, operational examples, and leadership insights, Leiva introduces a framework for governing hybrid human-AI systems that preserves human agency while unlocking the benefits of intelligent automation. Rather than treating AI as a standalone tool, AMPLIFIED shows leaders how to embed it within systems of accountability, learning, and ethical decision-making.

Inside AMPLIFIED, leaders will learn how to:

¿ Recognize when efficiency becomes a hidden organizational risk
¿ Design decision boundaries that preserve human accountability
¿ Replace symbolic "human-in-the-loop" models with real authority and agency
¿ Measure trust, learning velocity, and ethical health-not just output and productivity
¿ Lead organizations without becoming the decision bottleneck
¿ Build operational systems that adapt under pressure instead of snapping
¿ Align automation with culture, governance, and long-term strategic resilience
¿ Protect the human core of leadership in an increasingly algorithmic world

Leiva argues that the real competitive advantage of the AI era will not belong to organizations that automate the fastest-but to those that design the most resilient human-machine systems. The leaders who succeed will be those who understand how to amplify human potential rather than quietly replace it.

Part leadership philosophy, part operating manual, AMPLIFIED is a clear-eyed guide for executives, founders, operators, and technology leaders responsible for steering organizations through the next wave of transformation. It offers practical insight for anyone tasked with building teams, systems, and cultures that can thrive in an AI-driven world.

The Operator's Playbook for Scaling Human Potential in an AI World

AMPLIFIED

Risk, Governance and Society

From Data Analytics to Global Risk Governance

Evolution of Anomaly Detection

AI and quantum computing are two disruptive forces about to push financial services and the banking industry over the edge, demanding an unprecedented transformation. They are not fleeting trends but fundamental disruptors that will reshape the core of banking and finance. Authored by a senior Swiss banking technology executive, this practical guide helps board members and senior leaders turn disruption into a disciplined strategic agenda. It offers a rare insider perspective and a roadmap for navigating these seismic shifts. Bridging the gap between technological innovation and practical application, this book equips leaders with the tools to address the challenges and opportunities posed by AI and quantum computing. It features a thorough review of the latest business opportunities and threats associated with these technologies, alongside foresight-based strategic decision frameworks to guide prioritisation. Real-world case studies and an online companion with 125 AI use cases tailored for banks provide actionable insights. It also introduces an original AI Adoption Maturity Model and a Hybrid Enterprise Reference Architecture to ensure safe integration of internal systems with external frontier models. Finally, it provides two detailed multi-year roadmaps, offering a clear path to harness AI's potential and to prepare for a post-quantum future through crypto agility.Rather than offering abstract predictions or generic solutions, this book presents financial-services leaders with the frameworks, choices, and implementation path they need to act with confidence at a moment when waiting is no longer an option.

Evolutions at the Bleeding Edge

How AI and Quantum Computing Will Make or Break the Bank

Juridicum – Schriftenreihe zum Wirtschafts-, Unternehmens- und Bankrecht / Series on Business, Corporate and Banking Law

This book examines the transformative impact of artificial intelligence on corporation management, with a particular focus on decision-making at the board level. As AI technologies increasingly permeate corporate structures, traditional legal frameworks face profound challenges in addressing issues of accountability, responsibility, and governance.
Adopting a comparative legal perspective, the study analyses the role of artificial intelligence within corporate boards under Turkish and German law. It explores the possibility of AI acting as a board member, its use as a strategic asset, and the legal implications of delegating managerial functions to AI systems. Particular attention is given to the evolving duties of directors, including the potential obligation to integrate AI into corporate management and the development of governance frameworks for its responsible use.
The book further examines key concerns such as fiduciary duties, liability, compliance, and the need for organisational restructuring in light of AI-driven decision-making. By bridging corporate law and emerging technologies, it contributes to contemporary debates at the intersection of law and innovation.
This work will be of interest to scholars, practitioners, and policymakers in corporate law, commercial law, and technology law, and provides practical guidance for board members in navigating the challenges of AI-driven corporate governance.

A Comparative Legal Analysis

Artificial Intelligence and Corporation Management

Turn enterprise AI into a source of strategic insight, not just productivity gains.The AI Gap by leading AI expert and keynote speaker Richard Foster-Fletcher shows business and technology leaders how to unlock greater value from enterprise AI by changing the structures, processes and culture surrounding it. Organizations invest in AI expecting new intelligence and transformative insights. Yet AI is often introduced through procurement, security, legal and compliance systems designed for standard software, restricting its potential before it can deliver on that promise. This book explains why this gap persists and what organizations must change to close it. You'll learn how to: - Identify organizational barriers limiting the value of AI - Move beyond productivity-focused AI implementation - Create conditions where AI can generate deeper insights - Enable employees to explore, experiment and challenge established thinking &gt;The AI Gap equips leaders to rethink AI implementation, create space for experimentation and turn artificial intelligence into a powerful driver of organizational insight and long-term business value. Themes include: enterprise AI, AI implementation, AI strategy, business transformation, organizational culture, AI innovation

How Business Decisions Expand What AI Can Do

The AI Gap

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 behavior Featuring 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

Professional Practice in Governance and Public Organizations

This book examines how governance structures shape incentives, behavior, and long-term investment, arguing that the quality of governance is the primary determinant of prosperity and liberty. It explains how political power operates, why inclusive democracies tend to outperform autocracies, and how institutional frameworks can leverage technology to automate enforcement.&nbsp;Drawing on institutional economics, mechanism design, game theory, and systems engineering, the book reframes constitutional design as an engineering problem rather than an ideological debate. Instead of prescribing specific policy decisions, it proposes a framework for constructing rules and constitutional provisions that reliably produce better collective decisions.&nbsp;Moving from theory to practice, the book offers a rigorous blueprint for scholars, policymakers, reformers, and technologists seeking to improve governance. It provides concrete tools for institutional reform, including an AI-based adjudication system and a “smart constitution” deployable on a blockchain to govern political transitions and establish legitimate interim governments. It also proposes a zero-trust constitutional framework that assumes adversarial behavior by public officials.&nbsp;

From Theories to Codes

Better Governance

We started this book with a simple question: How
risky is too risky?
Risky or Too Risky
159
After five chapters and fifty conversations, the answer is clear:
The only risk that's too risky is the risk of relevance.

Everything else? That's just business.

And as our accidental risk managers, trust-but-verify practitioners, human-centered leaders, and intelligently aggressive innovators have shown us:
When you approach risk with wisdom, courage, and humanity, even the riskiest ventures can become your greatest opportunities. The future doesn't belong to the risk-averse or the
reckless.

It belongs to the risk-intelligent-those who see uncertainty not as a threat to be eliminated, but as a canvas for creation.
Your canvas is waiting. Your team is ready. The only question left is: What risk will you take
tomorrow that your competition is too scared to
take today?

Because in the end, that's not just risk management. That's leadership.
And that's how you build the future-brick by brick. We asked, How risky is too risky?
Now we know:
Not taking any risks at all.

That's too risky.

Tales from the Brick by Brick Pod

Risky or Too Risky

AI is everywhere. The value is not.

Organisations buy licences, launch pilots, build applications and train employees. Yet the hardest question often goes unanswered: what has demonstrably improved?

Why Organisations Fail with AI-and Others Don't explains why technology is rarely the real bottleneck. The real difference lies in an organisation's ability to build AI, govern it and realise value. A successful pilot is not yet a robust capability. Governance only matters when someone can actually intervene. And productivity only counts when work, capacity, customer value or earning power genuinely changes.

Michiel Krol connects strategy, technology, organisation design, leadership and governance with practical experience. He shows how seemingly sensible AI initiatives stall when technology advances faster than the organisation around it-and what leaders must organise differently to move from experimentation to sustainable results.

At the heart of the book are three board-level questions: Can we build it? Can we govern it? Can we realise value from it? These questions are developed through the AI Capability Framework, seven interconnected capability groups and ten recognisable capability paradoxes. Together they provide a practical lens for decisions about strategy, investment, people, risk, operating models and performance.

The book also examines the deeper organisational consequences of AI. What happens to professional development when AI takes over the tasks through which juniors traditionally learn? How do organisations preserve meaningful human oversight? When does outsourcing accelerate progress but weaken internal learning capability? How should leaders think about cybersecurity, supplier dependency, digital sovereignty and the EU AI Act? And what evidence should cause an earlier AI decision to be reconsidered?

Written for board members, executives and senior managers who must make decisions about AI without being AI specialists themselves-and for the professionals who advise them-this is not a tool guide, trend book or hype story. It is an accessible but intellectually substantial management book for leaders who want to connect technology, people, processes, governance and value as one coherent system.

The technology is already here. The difference will be made by the organisation that learns best what it needs to become.

How organisations learn to build AI, govern it and realise value

Why Organisations Fail with AI-and Others Don't

Shared Intelligence

Coming of Age

Wiley Finance

The handbook to unleash the power of AI in Finance with guidance to pragmatically managing AI Risk Are you ready to harness the transformative potential of artificial intelligence and machine learning in finance while effectively managing the associated risks? "AI and Risk Management in Finance: A Practitioner's Handbook" by Sri Krishnamurthy, CFA, is your indispensable guide. Tailored for financial professionals, this comprehensive handbook delivers practical insights, case studies, and frameworks to navigate the complex landscape of AI and ML in the financial sector. This pragmatic handbook, developed primarily for professionals involved in designing, developing, and deploying AI models in the financial industry explores cutting-edge technologies, regulatory landscapes, and pragmatic frameworks. From generative AI to robust risk management strategies, this handbook equips you with the tools you need to validate models, ensure compliance, and operationalize AI risk management effectively. Leveraging lessons from QuantUniversity's AI and Machine Learning Risk Management program offered in 18 countries, this book focuses on enabling practitioners apply the state-of-the-art AI and machine learning techniques factoring unique risks specific to the financial services domain. Whether you're a seasoned professional or a newcomer, this book offers invaluable insights for harnessing the power of AI responsibly in the financial industry. Highlights of the Book: <ul> <li>Machine Learning and AI in Financial Services: Dive into the fundamentals of ML and AI, exploring various applications within the financial industry through real-world case studies.</li> <li>Generative AI and LLMs in Finance: Understand the emerging landscape, key players, and advanced concepts like prompt engineering and fine-tuning with practical examples.</li> <li>Risk Management for AI/ML Applications: Learn about current and emerging regulatory landscapes, AI risk management frameworks, and legislative efforts shaping the field.</li> <li>Data Governance Issues: Address critical aspects of data quality, privacy, security, and governance, with actionable frameworks and illustrative case studies.</li> <li>Model and System Governance: Gain insights into validating machine learning models, quantifying model risk, and ensuring robust system governance with MLOps and model monitoring.</li> <li>Key Risk Assessment Facets: Focus on documentation, explainability, fairness, security, and reliability with detailed case studies.</li> <li>Verification and Validation: Distinguish between verification and validation and learn frameworks for effective AI application validation.</li> <li>Algorithmic Auditing: Conduct comprehensive algorithmic audits with detailed processes and real-world examples.</li> <li>Operationalizing AI Risk Management: Discover ten essential strategies for implementing AI risk management practices effectively in your organization.</li> </ul> Prepare for the future of finance with expert advice and actionable strategies. Don't miss out on this comprehensive guide-your roadmap to navigating AI and risk management in the financial sector.

A Practitioner's Guide to Machine Learning, Generative AI, Agentic Systems, and Responsible Deployment

AI and Risk Management in Finance

Governing the AI Machine

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