CAPS: Cognitive Accounting and Productivity Standard A Voluntary Disclosure Framework for Measuring AI-Driven Productivity Beyond GAAP

CAPS (Cognitive Accounting and Productivity Standard) is a proposed disclosure and measurement framework designed to capture forms of economic value creation that traditional financial reporting does not observe. As artificial intelligence becomes embedded in operational workflows, a growing share of productivity, cost displacement, and capability development occurs outside the scope of GAAP-based financial statements. CAPS addresses this gap by introducing a structured, three-tiered metric system—input, output, and momentum metrics—paired with a Reporting Quality Modifier (RQM) to contextualize reliability and comparability. The framework focuses on four categories of underreported value: displaced value (costs eliminated by AI), trapped value (latent productivity not yet monetized), lost value (erosion in non-adopting firms), and momentum value (rate of capability accumulation). Rather than attempting balance sheet recognition, CAPS operates as a parallel disclosure layer, enabling analysts, operators, and investors to better assess operational reality and forward-looking capacity. CAPS is not an audited standard or replacement for GAAP or IFRS. It is a working draft intended for voluntary adoption, critique, and iterative refinement. Its primary objective is comparability over precision—providing a consistent lens through which AI-driven productivity can be evaluated across firms, even in the absence of audit-grade verification. The framework is designed to evolve through real-world application and feedback, with future versions expected to expand metric rigor, industry-specific adaptations, and integration into valuation methodologies.