AIintegratsiooni
AIintegratsiooni (AI integration) denotes the process of embedding artificial intelligence capabilities into existing systems, processes, or products to improve efficiency, automate tasks, and enhance decision-making. It spans software, hardware, data platforms, and organizational workflows, and requires alignment of data, models, and governance.
Key components include data readiness and integration (data quality, preparation, pipelines, feature stores), model deployment (inference
Approaches to AI integration include API-based connections, middleware, microservices, event-driven architectures, and the use of MLOps
Benefits often include improved efficiency and accuracy, enhanced decision support, personalization, predictive maintenance, and cost savings.
Standards and frameworks such as MLOps, AIOps, responsible AI, and data governance help organizations manage risk
Effective AI integration requires cross-functional teams, clear governance, data quality, and ongoing monitoring to ensure value,