Corporate AI Johari Window
In an era defined by Agentic AI, ubiquitous telemetry, and autonomous data pipelines, traditional frameworks for Enterprise Risk Management (ERM) and corporate governance are rapidly collapsing. Business-critical information is no longer confined to isolated enterprise silos; it is continuously cross-referenced, mined, and synthesized by both internal algorithms and external autonomous agents. This whitepaper introduces The Corporate AI Johari Window™, elevating the classical 1955 interpersonal model into a triadic, strategic C-level framework designed for executive boards, CISOs, and enterprise architects. By mapping the dynamic tensions across three analytical axes: X-Axis: Corporate X Internal Awareness (Processes, vulnerabilities, and strategic intent) Y-Axis: Competitors & Market Awareness (Industry intelligence, supplier data, and unwritten norms) Z-Axis: AI & Synthetic Awareness (Frontier models, web crawlers, and algorithmic pattern recognition) The model articulates 12 distinct strategic rooms structured across three operational database layers: Layer 1: The Internal Ecosystem ($Competitors = NULL$): Balancing autonomous optimization against algorithmic drift and context stripping. Layer 2: The Transparent Marketplace ($Competitors = TRUE$): Addressing asymmetric exposure, commoditization, and the modern "Emperor’s New Clothes" paradox where external agents detect corporate failures before executive leadership does (Room 6). Layer 3: The Proprietary & Protected Space ($Competitors = FALSE$): Defending proprietary alpha, navigating algorithmic short-selling driven by synthetic mosaics (Room 10), and maintaining the non-digital corporate sanctum against systemic macro shocks (Room 12). Furthermore, the paper details critical governance imperatives, including Temporal Entropy (the natural drift of data toward public exposure), Zero-Day vulnerability exploitation lifecycles, and the Triad of Governance: Model $\rightarrow$ Architecture $\rightarrow$ Trust. The Corporate AI Johari Window™ serves as the architectural blueprint required to transform black-box exposure into controlled enterprise resilience.
Authors
- Lars Bacher
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-11-01
- DOI
- https://doi.org/10.5281/zenodo.23867379
- Primary Topic
- Information Technology Governance and Strategy
- Type
- preprint