From Battlefield to Boardroom: Strategic Red Teaming as an Epistemic Governance Instrument in the Age of AI

Jul 16, 2026

Strategic planning for AI adoption often treats approval as sufficient evidence that an initiative is sound. This technical report formalizes strategic red teaming as a board-level assumption stress-testing model for AI governance. It tests the propositions that must be true for a material AI strategy to be defensible, using a bounded six-component process covering mission alignment, assumption mapping, dependency stress testing, economic fragility, regulatory exposure simulation, and accountability-boundary testing.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages7

Reading Time18 min

Introduction

Positioning and claim boundary

The governance problem

Red teaming modalities

AI as an exposure multiplier

arXiv :2607 .0 19 13v 1 [ cs .CY] 2 Jul 2026 From Battlefield to Boardroom: Strategic Red Teaming as an Epistemic Governance Instrument in the Age of AI Jeroen Janssen Apparens [office@apparens. nl](office@apparens. nl) arXiv technical report edition, July 2026 Abstract Strategic planning for AI adoption commonly treats approval as sufficient evidence that a proposed initiative is sound. This technical report formalizes strategic red teaming as aboard-level assumption stress-testing model for AI governance. The model is designed to test the propositions that must be true for a material AI strategy to be defensible, rather than to test model outputs, security controls, or compliance artefacts alone. The report preserves the original title of the working paper but reframes the contribution as a bounded governance design artefact: a six-component process for mission-alignment testing, assumption mapping, dependency stress testing, economic-fragility testing, regulatory-exposure simulation, and accountability-boundary testing. The argument is that AI integration changes the evidentiary burden of strategic approval along five exposure dimensions: operational leverage, transparency reduction, dependency concentration, regulatory liability, and accountability-boundary shift. Under these conditions, conventional risk registers and management-owned assurance processes are insufficient because they document known risks within an accepted plan rather than adversarially testing the assumptions that make the plan appear acceptable. The proposed design specifies inputs, outputs, evidence grades, independence requirements, reporting lines, and board decision records. It does not claim legal sufficiency, empirical validation, regulatory endorsement, or universal necessity. It claims a testable institutional design for producing board-quality evidence about the strength of strategic assumptions in AI-embedded organizations. Keywords: strategic red teaming; AI governance; assumption testing; board governance; epistemic accountability; risk governance; EU AI Act. 1. Introduction AI adoption strategies often move from executive advocacy to board approval without an adversarial test of the assumptions on which the strategy depends. Standard risk governance usually asks whether identified risks have controls. It rarely asks whether the strategic propositions that justified the initiative were ever true enough to rely on. This report treats that gap as an epistemic governance problem. The central question is: under what conditions does AI integration transform strategic red teaming from a useful governance instrument into a board-level assumption stress-testing requirement? The paper does not assert that every AI deployment requires a full strategic red-team engagement. It defines the conditions under which the evidentiary burden becomes material: consequential AI use, significant capital commitment, dependency on external AI providers, high-risk regulatory exposure, opacity in decision pathways, or an accountability structure that cannot be reconstructed after harm occurs. The report contributes a design artefact: a formal model for strategic red teaming as independent, evidence-graded assumption stress testing. The object of test is not a model, application, policy, or control framework. The object is the cognitive architecture of a strategic decision: the propositions that must hold for the strategy to be defensible. 2. Positioning and claim boundary This is a technical report on institutional design. It is not an empirical study, legal opinion, or regulator-endorsed framework. Its claims are bounded as follows. • Design claim. Strategic red teaming can be specified as a repeatable governance process with defined inputs, independence rules, evidence grades, outputs, and reporting lines. • Necessity claim. A full engagement is warranted only when AI integration creates material uncertainty, opacity, dependency c

FAQs

What does the report mean by strategic red teaming as “epistemic governance” for AI?

It frames the governance gap as an epistemic problem: approval should be supported by adversarial stress-testing of the underlying strategic propositions, not only by checking identified risks or controls within an accepted plan.

When does the report argue a full strategic red-team engagement becomes material?

When AI integration creates material uncertainty or opacity, increases dependency concentration on external providers, elevates high-risk regulatory exposure, or introduces accountability ambiguity that cannot be reconstructed after harm.

What is the six-component process specified by the model?

The process covers mission-alignment testing, assumption mapping, dependency stress testing, economic-fragility testing, regulatory-exposure simulation, and accountability-boundary testing, producing evidence-graded board-quality documentation.

Jul 16, 2026

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