Generating Cyber Intelligence (CYBINT) scenarios & solutions to address uncertainty for decision-advantage: Using Intelligence Engineering & Strategic Options Analysis -- A Macro Cyber Scenario Case Study using Intelligence Engineering & Strategic Options Analysis Methods -- Examining the Landscape of Unauthorised Cyber Access (with reference to POSTnote #684) -- Intelligence Engineering-led set-up of generic Strategic Options Analysis Problem to Solution Spaces: Cyber example demonstration -- More than Semantics? Communication of (Un)certainty via ‘Estimative/Probabilistic Language’ -- Estimative/Probabilistic Language - Part II: Expanding the Range of Scenario Options -- Scoping ‘Digital Twins’ in intelligence & strategic foresight projects -- Generative-AI Pilot for Problem Spaces: Can ChatGPT help develop Scenarios? -- An Outline for an Interrogative/Prompt Library to help improve output quality from Generative-AI Datasets -- Prompt-engineering testing ChatGPT4 & Bard for assessing Generative-AI efficacy to support decision-making -- Can Generative-AI (ChatGPT and Bard) Be Used as Red Team Avatars in Developing Foresight Scenarios? -- Realising Foresight Intelligence (FORINT) - Advancing an Intelligence-derived Foresight Framework -- The Role of the Scenario and its Reassessment -- Advancing a New Methodological Process -- Process implications – Current software enhancements, including increasing levels of AI.

This book brings together a diverse range of findings on current and emerging business concerns when the authors were developing a series of 12 working Analytic Research Consortium (ARC) White Papers. It presents several, differently configured scenarios, drawing on cyber as an example; the use and further optimization of estimative/probabilistic language; communicating analytical insights and other findings concerning ‘(un)certainty’ to decision-maker end-users; and mitigating risk. It also evaluates in detail today’s rapidly evolving Gen-AI systems and technologies, e.g. those underlying OpenAI’s ChatGPT and Google’s Bard/Gemini. This includes their respective value concerning scenario development and other business-relevant methods, tools and techniques, e.g. ‘Red Teaming’. The topics discussed are assessed using the multi-methodologies of, firstly, ‘Intelligence Engineering’ (IE) and, secondly, ‘Strategic Options Analysis’ (SOA). The latter half of the book introduces an alternative scenario planning process, including use of new computer-software and AI tools. In addition to Gen-AI, we identify that the emerging discipline of Causal AI may work better for foresight and scenario activities. The book is a valuable read for a diverse readership from the public and private sectors, spanning government, the military, law enforcement, education, industry, commerce, retail, and enterprises of all sizes. Also, students at business schools and high-level decision-makers, including politicians, military commanders, and C-Suite leaders in various fields, will benefit from it.