FORMING AN AI-METHODOLOGY FOR BUSINESS MODEL MANAGEMENT IN THE DIGITAL ECONOMY

Abstract

The article introduces the development of a new AI-driven methodology for managing business models in the IT sector. The author’s approach, termed Adaptive Neuro-Driven Project Management (AND-PM), is founded on the integration of artificial intelligence into every core stage of the business model life cycle. Unlike conventional frameworks, in which AI functions as an auxiliary module or an additional analytical component, the AI-oriented methodology positions artificial intelligence as the central element of the management architecture, creating an intelligent layer that permeates all business processes. This conceptual shift enables higher predictive accuracy, improved resource allocation, reduced operational risks, and enhanced overall performance of the business model. A detailed budget for implementing the AI-based management methodology in the IT sector has also been developed. The research and subsequent creation of the AI-oriented AND-PM methodology resulted in a comprehensive conceptual and practical business model for IT project management that synthesizes classical Agile principles with advanced capabilities of artificial intelligence. The proposed framework reconceptualizes project management not as a sequence of isolated tasks but as a continuous, self-learning process in which analysis, forecasting, and adaptation occur in real time. A fundamental component of the methodology is the SmartSprint AI platform, which operates as the intellectual core of the management system. The use of modules such as Task Analyzer, Sprint Planner, Task Matcher, AI Forecast, Risk Radar, and Knowledge Extractor enables automation and optimization across all stages of the business model life cycle in the IT domain – from project initiation to retrospective evaluation. This level of integration significantly reduces manual workload, limits the impact of human subjectivity, and strengthens transparency and predictability in decision-making. A notable outcome of the AND-PM methodology is the transformation of team roles within the project environment. The introduction of new positions –including AI Governance Owner, AI Analyst, Prompt Engineer, and AI-Powered Team Lead – enhances accountability for data quality, ensures proper oversight of model accuracy, and establishes a new paradigm of collaboration between team members and intelligent systems. This role structure reflects current trends in the IT industry, where artificial intelligence is evolving from a supportive tool into a strategic partner in the decision-making process.