Scenario analysis in the AI era: Redefining human involvement

We investigate two aspects of scenario analysis: 1) how to include humans-in-the-loop when generating a set of plausible future scenarios using generative AI, and 2) how to decide on prudent responses to a set of plausible future scenarios. Our investigation draws upon the literature and practice-based experiments to consolidate two key outputs. First, we provide a scenario analysis guidance tool that will enhance the usefulness of scenarios when using generative AI assistance. Our tool provides guidance on three aspects: AI prompting, testing for relevance, and tuning to fit the purpose. Second, we create a scenario response spectrum framework that provides a structured approach to guide executives in determining the type of response to implement for each scenario. Our five-category response spectrum includes priority action, timely action, safeguard, monitor, and ignore. The scenario response spectrum framework contributes new insights by being based on an impact assessment in conjunction with an understanding of organizational risk tolerance. Collectively, our work aids strategic planning and decision-making in uncertain environments. We also present conjectures on the evolving role of scenario analysis in a world where scenarios are instantly available and virtually costless to create via generative AI systems and we contemplate perpetual scenario analysis via agentic AI systems.

Authors

Institutions

Publication Details

Journal
Organizational Dynamics
Published
2025-11-20
DOI
https://doi.org/10.1016/j.orgdyn.2025.101197
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Scenario analysis in the AI era: Redefining human involvement

Patrick Sharry, George A. Shinkle, Chirag Gujarati
Organizational Dynamics
Ethics and Social Impacts of AI
article

Scenario analysis in the AI era: Redefining human involvement

Patrick Sharry, George A. Shinkle, Chirag Gujarati
article en

Abstract

We investigate two aspects of scenario analysis: 1) how to include humans-in-the-loop when generating a set of plausible future scenarios using generative AI, and 2) how to decide on prudent responses to a set of plausible future scenarios. Our investigation draws upon the literature and practice-based experiments to consolidate two key outputs. First, we provide a scenario analysis guidance tool that will enhance the usefulness of scenarios when using generative AI assistance. Our tool provides guidance on three aspects: AI prompting, testing for relevance, and tuning to fit the purpose. Second, we create a scenario response spectrum framework that provides a structured approach to guide executives in determining the type of response to implement for each scenario. Our five-category response spectrum includes priority action, timely action, safeguard, monitor, and ignore. The scenario response spectrum framework contributes new insights by being based on an impact assessment in conjunction with an understanding of organizational risk tolerance. Collectively, our work aids strategic planning and decision-making in uncertain environments. We also present conjectures on the evolving role of scenario analysis in a world where scenarios are instantly available and virtually costless to create via generative AI systems and we contemplate perpetual scenario analysis via agentic AI systems.

Organizational DynamicsVol. 55(1)
UNSW Sydney (AU)
Openalex Percentile: Top 64%
Ethics and Social Impacts of AI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.