Theoretical Foundations of Decision-Making for Implementing Artificial Intelligence Technologies in Software Products

The study examines theoretical foundations for managerial decision-making on the implementation of artificial intelligence technologies in software products under conditions of accelerated prototyping, AI-supported software engineering workflows, and data-driven product development. The objective is to construct a conceptual decision model that links decision theory, organizational readiness, AI governance, and modern software product management practices. Within the research, existing approaches to AI-based decision-making, organizational AI implementation, and AI-driven software engineering are systematized. The conditions for the reliable deployment of AI functionality into production-grade software are analyzed. Special attention is paid to data quality, digital maturity, and responsible AI governance as determinants of adoption decisions. The methodological base combines a targeted review of recent scientific literature, comparative analysis of conceptual frameworks, and synthesis of a multi-level decision model for product leaders. The conclusions outline the stages and criteria for decision-making on AI implementation in software products, and provide practical guidelines for product leaders and software engineering managers seeking to evaluate AI opportunities, structure experimentation, and align AI-enabled prototyping with long-term product strategy and trust.