MANAGING CORPORATE POLICY FOR THE USE OF AI AND BUILDING A MATURITY AND VALUE MANAGEMENT MODEL

Abstract

This article proposes a theoretical and methodological approach to developing a maturity model for managing the use of artificial intelligence in corporations. The model integrates a risk-oriented regulatory context and elements of management engineering: the AI management system, the lifecycle processes of AI systems, and risk management frameworks. Key maturity dimensions (strategy and policy, organizational architecture and human oversight, data and model management, lifecycle processes, risk and compliance management, security and reliability, value measurement, and management reporting) are highlighted, along with a tiered template with verifiable criteria. An assessment methodology is proposed, including a maturity profile, a compliance map, and a thermal risk visualization, as well as evidence lists (policies, registries, test protocols, monitoring and audit reports). The relationship between maturity and value management is demonstrated: transitions between levels are anchored by target metrics for value and cost, decision quality, and response time, allowing compliance requirements to be aligned with the capitalization of the impact of a portfolio of AI initiatives.