Gartner, 이 4가지 아키텍처 축 없이는 2026년까지 AI 프로젝트의 60%가 실패할 것이라 예측
Gartner는 열악한 데이터로 인해 2026년까지 AI 프로젝트의 60%가 중단될 것으로 예측하며, 프로토타입에서 확장 가능한 프로덕션급 AI 시스템으로 전환하려면 신뢰할 수 있는 데이터 파이프라인과 컨텍스트 엔지니어링이 핵심이라고 강조했다.
gartner predicts that organizations will abandon 60% of ai projects by 2026 if they lack ai-ready data, according to an mit technology review insights report in partnership with elastic. the report identifies four enduring architectural pillars necessary for scaling ai: data quality, context engineering, governance, and human expertise. it emphasizes that while models evolve, the foundation must support reliable retrieval and decision-making, highlighting that context engineering—often more critical than prompt engineering—ensures models receive precise, relevant inputs to maintain speed and accuracy. successful architectures require real-time, unified data foundations and vector databases to support advanced techniques like retrieval augmented generation (rag) as companies move toward agentic systems.