Buch, Englisch, 272 Seiten
AI for the Intelligence Analyst
Buch, Englisch, 272 Seiten
ISBN: 978-1-394-34504-5
Verlag: Wiley
Integrating AI into intelligence analysis and OSINT workflows for working analysts
Deep Insight: AI for the Intelligence Analyst examines how artificial intelligence reshapes intelligence gathering and open source intelligence methodology. Written by Rae Baker, a Specialist Master at Deloitte and Senior OSINT Analyst within the Dynamic Adversary Intelligence team, this book focuses on core principles and methodology rather than specific tools that quickly become outdated. Baker frames AI as an accelerator for analyst workflows, helping practitioners streamline repetitive tasks and dedicate more time to substantive analysis.
Rather than cataloging individual AI tools, Deep Insight blends intelligence and OSINT concepts with real-world stories, thought experiments, and immersive scenarios designed to help analysts apply AI to their specific operational roadblocks. Each chapter connects AI capabilities directly to intelligence processes, showing how automation and machine learning techniques fit within established analytical frameworks and tradecraft. The structure builds progressively from foundational AI concepts to applied intelligence use cases.
Readers will also find: - Methodology-focused guidance on integrating AI into existing OSINT collection and analysis processes without tool dependency
- Real-world scenarios and thought experiments illustrating how AI addresses common bottlenecks in intelligence workflows
- Frameworks for evaluating when AI augmentation adds value versus when human analytical judgment remains critical
- Practical approaches to automating repetitive intelligence tasks so analysts can focus on higher-order analytical work
- Strategies for applying AI responsibly within intelligence operations, including bias awareness and ethical considerations for analysts
Deep Insight serves intelligence and OSINT professionals at beginner to intermediate levels who want to integrate AI into their analytical processes. Security researchers, government contractors, and analysts working in related fields will find a methodology-driven approach that connects AI capabilities directly to the tradecraft and workflows they use daily.
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Weitere Infos & Material
Contents
Day 1 with AI: First Steps
Meet the Analysts
AI Overview
OSINT Overview
Chapter 1: Setting Sail
Integrating AI and Intelligence
Mission
Understanding AI’s Role in Intelligence
Introduction to Workflow Development
Chapter 2: Mapping the Depths
Exploring Foundational AI Technologies
Mission
Matching AI Capabilities to Analyst Problems
Matching Tools to Real Users
Think Like the Adversary
Chapter 3: Casting the Nets
Automating Data Collection for Research and Analysis
Mission
The Data Problem
What Analysts Need to Know About Data
Data Types and Sources
What Does Automating Collection Actually Mean?
Designing an AI Collection Workflow
Chapter 4: Diving Beneath the Surface
Using Machine Learning for Pattern Detection
Mission
Organizing the Noise
What Is Machine Learning?
How Machine Learning Works
Types of Machine Learning
Why Machine Learning Matters to Analysts
Chapter 5: Interpreting the Sea
Using Natural Language Processing (NLP) to Decode and interpret Global Data
Decoding the Message
What Is Natural Language Processing?
Why Natural Language Processing Matters to Analysts
NLP Toolbox
Chapter 6: Steering the Ship
Writing Effective Prompts for Accurate Results
Mission
What Is a Prompt?
Why Prompts Matter in Intelligence Work
How AI Interprets Prompts
What Makes a Prompt Work
Advanced Prompting Techniques
Chapter 7: Adjusting the Sails
Predictive Analysis to Anticipate Future Threats
Mission
What Is Predictive Analysis?
How AI Enhances Predictive Analysis
Key Steps in Predictive Analysis for Intelligence Work
Using Predictive Analysis to Assess Risk and Forecast Threats
Case Studies in Predictive Analysis
Chapter 8: Staying the Course
Maintaining Ethical Standards in AI
Mission
Critical Thinking in AI Times
Ethical Issues in AI for Intelligence Work
The Human Cost of AI
Chapter 9: Anchoring Down
From Analyst to Developer
Mission
The Vibe Coding Problem
Why Python?
Building Your First Tool: Domain Analyzer
Poof, You Are Now a Developer (Not a Vibe Coder)
Chapter 10: Captain’s Log
Case Studies in AI-Enhanced OSINT
Mission
The Gunslinger’s Hallway: Same Skills, Different Worlds
Chapter 11: Scanning the Horizon
Preparing for the Future of AI and OSINT
Mission
Agentic AI
Multimodal AI
Large World Models
Quantum Computing and Security
Attribution and Contamination
Chapter 12: Plotting the Next Course
Beyond the Basics
Mission Wrap-Up
What You Actually Built
Next Steps
Wrap-Up
About the Author
Acknowledgments
