From Pilots to Scale: How Hybrid Architectures and Governance Models Shape the Success of AI Adoption in Business

The article examines current aspects of practical implementation of artificial intelligence in business processes of modern organizations. The main focus is on analyzing the effectiveness of various technological architectures and organizational management models for AI projects.
Based on a study of over 40 practical cases of AI implementation in Russian and international companies, the authors identify key success factors for projects. Particular attention is paid to comparing three main AI deployment models: cloud, on-premises, and hybrid. It is proven that hybrid architecture provides an optimal balance between scalability, security, and cost-effectiveness.
The paper also analyzes three main models of AI initiative management: centralized, decentralized, and hybrid hub-and-spoke. It is shown that the latter model is the most effective for scaling AI solutions in large organizations.
The practical significance of the research lies in developing an evolutionary trajectory for AI implementation — from a centralized model at initial stages to a hybrid model as the organization matures. The authors emphasize the important role of a multidisciplinary AI Center of Excellence as a strategic body managing the digital transformation process.
The research findings can be used by company executives and digital transformation specialists when planning and implementing AI implementation projects.

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