Critical Success Factors for GenAI Digital Products: From Technology–Market Duality to a Technology–Market–Ethics Triad

Technology in Society. 2026. Vol. 88. Article 103456.

Sorokin I., Tekic Z.

Generative AI (GenAI) digital products challenge established new product development and product success frameworks because performance after launch remains variable: outputs differ across runs and contexts, behavior can shift under drift, and realized value depends on user interaction, oversight, and governance at scale. Focusing on large language model (LLM)-based GenAI digital products, this study identifies and structures critical success factors (CSFs) for sustained market performance across B2C and B2B contexts. Using a two-stage research design based on expert input, we derive and validate 25 CSFs and apply Interpretive Structural Modeling (ISM) and MICMAC analysis to map dependencies and classify CSFs by driving and dependence power. Established CSFs remain important alongside broader technical, operational, and governance capabilities required by GenAI products. Four CSFs occupy foundational positions and show high driving power: product manager’s AI competency, team’s technical expertise, problem understanding, and ethics. Ethics functions as a permission-to-scale condition shaping design, adoption, and commercialization. This pattern supports a Technology–Market–Ethics triad as an interpretive lens for sustained GenAI product success. The B2C and B2B models converge on the same foundational CSFs but diverge in adoption-facing requirements: B2C emphasizes interaction quality and usability, whereas B2B emphasizes explainability, accountability, integration, and compliance readiness.

Keywords: этика, ethics, критические факторы успеха, LLM, critical success factors, ISM, цифровые продукты, digital products, генеративный ИИ, LLM, generative AI, MICMAC, ISM, MICMAC