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Safer Agentic AI Book Cover
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Safer Agentic AI

Principles and Responsible Practices

How to govern, align, and secure AI systems that act on their own. Written for policymakers, developers, and safety engineers.

Nell Watson
Prof. Ali Hessami
Nell Watson & Prof. Ali Hessami Chair and Process Architect, Safer Agentic AI Community of Practice
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Where to start

One control, worked through

Deployment
An email assistant reads, sorts and drafts replies in one person’s mailbox. It can also call a tool that sends email.
Control

D3.9 Tool-Use Authorization and Egress Control, SFR D3.9a:

“Calls outside the grant, calls with an argument taken from a field of untrusted content that the grant does not delegate (replying to a message delegates its sender's address, not addresses written in its body), and calls made where task scope is ambiguous shall be refused or escalated for human confirmation, and the agent's own credentials shall never be used to exceed the delegating principal's authority (confused deputy prevention).”
Evidence required
“… paired test results showing that the same tool call, by the same principal, succeeds when the current task explicitly delegates it and is refused when the only source requesting it or supplying its arguments is untrusted content …”
Failure it catches
An incoming message asks for the thread to be forwarded to an address written in its body. The model complies and calls the send tool. The grant check runs outside the model, finds a recipient the user never delegated, and refuses the send or asks the user.
Read D3.9 in full See it as a decision record

Status of this work

Book
Safer Agentic AI: Principles and Responsible Practices, by Nell Watson and Ali Hessami. Kogan Page, first edition, 3 January 2026.
Framework authorship
The Safer Agentic AI Community of Practice, chaired by Nell Watson, with Ali Hessami as process architect, using Weighted Factors Analysis (WeFA) expert elicitation. How the catalogue was produced
Governance
Nell Watson, as chair, approves changes to the framework catalogue and decides each release. To report an error, propose a control or object to a requirement, use the contact form.
Independent review
The framework and the tools have not been independently reviewed. No conflict-of-interest register is published.
Standards status
Not a formal standard of IEEE or any other standards body. Contributors’ roles in such bodies are listed in their biographies.
Release
Version 1.3, draft. For reading, the web edition governs where an archived edition differs; an assessment is read against the edition it records.
Licence
Framework text under CC BY 4.0, site code under MIT. Names, logos and book text are excluded. Licensing
Method validation
WeFA has been applied in aerospace, nuclear and medical systems. Its application to agentic AI is new and has not yet been independently validated.
Self-report questionnaire
Scores reflect your own answers. Nothing is checked.
Automated evidence review
An AI model reads the documents you supply and scores them against the framework. The assessor has not been independently validated, and its findings need human review. How it works and how it has been tested.
Demonstrated safety
Neither tool tests a running system. A good score shows reported or documented practice, not that a system is safe.
Endorsements
The quotations below endorse the book. They are not reviews of the framework or the tools.

What reviewers say about the book

What Is Agentic AI?

Agentic AI systems pursue goals, adapt to situations, and make decisions without human input. Unlike AI that recommends, these systems act—breaking down tasks, running experiments, adjusting to feedback. Because they operate autonomously, errors compound before humans can notice or intervene.

Look Inside the Book

From AI fundamentals through governance frameworks you can act on

Table of Contents

From the Foreword

"This timely volume addresses one of our field's most daunting challenges: ensuring the safe and beneficial development of increasingly autonomous AI systems. The authors combine technical expertise and ethical insight in a comprehensive framework... This book is invaluable for AI researchers, developers, policymakers, business leaders and anyone invested in the responsible future of artificial intelligence."
Dame Wendy Hall
Dame Wendy Hall
DBE, FRS, FREng
Regius Professor of Computer Science, University of Southampton

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Book overview audio

AI-generated discussion of the book, made in January 2026 from material earlier than framework v1.2

47:35 Transcript Full Player

Key Focus Areas

Nine dimensions determine whether an agentic AI system remains safe under real-world conditions.

Goal Alignment

Verifying that an AI system pursues the objectives its operators actually intended, not a distorted proxy.

Value Alignment

Embedding ethical values into AI behaviour and verifying they persist across updates and new contexts.

Safe Operations

Maintaining safe behaviour from development through deployment, including under degraded or adversarial conditions.

Epistemic Hygiene

Preventing AI systems from acting on false, stale, or poorly calibrated information.

Transparency

Making AI decision-making auditable so that operators can trace how a conclusion was reached and why.

Goal Termination

Reliable task completion, graceful shutdown, and orderly decommissioning when a system is no longer needed.

Security

Protecting AI systems against adversarial attacks, prompt injection, data poisoning, and other threat vectors.

Contextual Understanding

Verifying that an AI system accurately models its operating environment, including the boundaries and constraints that apply.

Responsible Governance

Clear lines of accountability, compliance structures, and oversight mechanisms throughout the deployment lifecycle.

Built on Structured Expert Analysis

The book expands on a framework developed by our Community of Practice — international experts in AI, ethics, law, and safety engineering — through the Weighted Factors Analysis (WeFA) expert-elicitation process.

7 Inhibitors Factors that push AI systems toward unsafe behaviour
balanced by
9 Drivers Safety and alignment measures that counteract the inhibitors
Read the Recommended Practices

About the Authors

Leaders in AI safety, ethics, and governance

Nell Watson

Nell Watson

Chair, Safer Agentic AI Community of Practice

Engineer, ethicist, and author of Taming the Machine. Chair of IEEE's Agentic AI Expert Focus Group and President of the European Responsible AI Office. Fellow of the British Computer Society and Royal Statistical Society. Listed as an Icon by the Royal Academy of Engineering.

Prof. Ali Hessami

Prof. Ali Hessami

Process Architect, Safer Agentic AI Community of Practice

Director of R&D at Vega Systems and Chair of IEEE P7000 Technology Ethics Standard. Vice Chair and Process Architect of IEEE ECPAIS. Fellow of the IET and Royal Society of Arts; Chartered Engineer. Visiting Professor at City, University of London and Beijing Jiaotong University.

Our Working Group

Experts from AI, ethics, law, social sciences, and safety engineering contributed to developing this framework.

Regular Contributors

  • Ali Hessami
  • Matthew Newman
  • Sara El-Deeb
  • Farhad Fassihi
  • Mert Cuhadaroglu
  • Scott David
  • Hamid Jahankhani
  • Nell Watson
  • Sean Moriarty
  • Isabel Caetano
  • Roland Pihlakas
  • Vassil Tashev
  • Keeley Crockett
  • Safae Essafi
  • Zvikomborero Murahwi
  • Lubna Dajani
  • Salma Abbasi

Occasional Contributors

  • Aisha Gurung
  • Leonie Koessler
  • Pramod Misra
  • Aleksander Jevtic
  • McKenna Fitzgerald
  • Pranav Gade
  • Alina Holcroft
  • Michael O'Grady
  • Rebecca Hawkins
  • Md Atiqur R. Ahad
  • Mrinal Karvir
  • Sai Joseph
  • Chantell Murphy
  • Nikita Tiwari
  • Tim Schreier
  • Katherine Evans
  • Patricia Shaw

Additional Contributors

  • Fadi Arab

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