Autonomous AI Systems: Risk and Compliance in Regulated Domains
Keywords:
Autonomous AI Systems, Regulatory Compliance, Explainable AI (XAI), Wissira Press Academic Books, Wissira Press, Books by WissiraSynopsis
The rise of autonomous AI systems marks a pivotal shift in how organizations design intelligence into their operations. No longer limited to decision support or narrow task automation, these systems increasingly act with initiative—perceiving their environment, making judgments, and executing actions with minimal human intervention. In regulated domains such as healthcare, finance, critical infrastructure, and the public sector, this evolution promises unprecedented efficiency and insight. At the same time, it introduces a new class of risks that challenge existing legal, ethical, and governance frameworks. Autonomy, when combined with scale and speed, amplifies both value and vulnerability.
This book is grounded in the understanding that deploying autonomous AI in regulated environments is not merely a technical endeavor. It is a socio-technical transformation that demands careful alignment between innovation and oversight. Traditional approaches to risk management, compliance, and assurance often fall short when applied to systems that learn, adapt, and act dynamically. Autonomous AI systems must therefore be designed with compliance as a foundational principle—not as an afterthought—ensuring traceability, explainability, accountability, and resilience throughout their lifecycle.
Autonomous AI Systems: Risk and Compliance in Regulated Domains aims to bridge the gap between aspiration and responsibility. It offers practitioners and decision-makers a structured perspective on how to assess, mitigate, and govern risks unique to autonomous behavior, while still enabling meaningful innovation. Drawing on interdisciplinary insights from AI engineering, regulatory policy, risk management, and organizational governance, the book provides frameworks, patterns, and practical guidance for building systems that can withstand regulatory scrutiny and public trust alike.
At its core, this work is guided by a clear conviction: autonomy and compliance are not opposing forces. When approached deliberately, they reinforce one another. Systems that are transparent, well-governed, and aligned with regulatory expectations are ultimately more robust, trustworthy, and sustainable. As autonomous AI becomes embedded in the most sensitive and consequential domains of society, the ability to manage its risks responsibly will define not only organizational success, but also the broader legitimacy of AI itself. This book is offered as a compass for those navigating that responsibility.
Chapters
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Chapter 1: Introduction to AI Project Management in Regulated Domains
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Chapter 2: Foundations of Regulatory Compliance
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Chapter 3: Autonomous Agents and AI Architecture
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Chapter 4: AI Project Planning and Governance
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Chapter 5: Data Management in Regulated AI Systems
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Chapter 6: Designing for Compliance by Default
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Chapter 7: Testing, Validation, and Certification
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Chapter 8: Deployment and Monitoring of AI Agents
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Chapter 9: Case Studies in Regulated Industries
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Chapter 10: Outlook and Emerging Trends
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