This article examines the evolution of business models in the context of digital transformation. It analyzes structural changes in the logic of business process design and the transition from traditional linear models to adaptive platform-based configurations. The study employs a systemic and comparative approach and focuses on industries such as finance, construction, and information technology. It identifies the specifics of implementing intelligent systems in each sector and explores the impact of digital solutions on operational efficiency, customer experience, and management practices. The necessity of forming a new organizational architecture, where data and algorithms become the core of value creation, is substantiated. The paper presents examples of successful practices and quantitative indicators of digital transformation. Particular attention is given to the differences in the initial digital maturity levels across industries. It is emphasized that the introduction of algorithmic management requires institutional changes and the emergence of new professional roles. The importance of ethical oversight and algorithm interpretability is considered in the context of growing reliance on automated solutions. The findings of the study can be applied to the development of digitalization strategies in both corporate and governmental practice.