The Compliance Fluency Gap
This whitepaper critically examines the systemic failures of AI-first GRC and presents a superior model: a human-led, visually-defined approach that builds deep "compliance fluency" and positions AI in its proper role as an analytical co-pilot, not an unreliable author.
Abstract
The rush to adopt Artificial Intelligence in Governance, Risk, and Compliance (GRC) is creating a dangerous paradox. While promising efficiency, an over-reliance on AI for generating compliance documentation and managing GRC programs is leading to generic, ineffective security postures and fostering a superficial "checkbox compliance" culture. This whitepaper critically examines the systemic failures of AI-first GRC, citing evidence of widespread project underperformance, the erosion of essential institutional knowledge, and the fundamental unsuitability of Large Language Models (LLMs) for creating net-new, factually grounded compliance content.
We then present a superior model: a human-led, visually-defined approach that uses a tree graph structure to build deep "compliance fluency." This model, exemplified by the Valdyr platform, structures organizations as roots that branch through policies, standards, controls, evidence and processes, with controls linking directly to frameworks like SOC 2 or CMMC, providing the hierarchical context necessary for genuine risk management and operational resilience, and positions AI in its proper role as an analytical co-pilot, not an unreliable author.
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This abstract provides just a glimpse into the comprehensive analysis and solutions presented in our complete whitepaper. To explore the full research, methodology, and detailed recommendations for building genuine compliance resilience, access the complete document below.