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시장보고서
상품코드
1351250
AI 소프트웨어Artificial Intelligence (AI) Software |
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※ 본 상품은 영문 자료로 한글과 영문 목차에 불일치하는 내용이 있을 경우 영문을 우선합니다. 정확한 검토를 위해 영문 목차를 참고해주시기 바랍니다.
세계의 AI 소프트웨어 시장을 조사했으며, 시장 영향요인 및 시장 기회 분석, AI 소프트웨어 매출의 추이·예측, 프레임워크·지역 등 각종 부문별 상세 분석 등을 정리하여 전해드립니다.
리포트의 이점 :
- 향후 매출 기회를 가시화하면서 AI 하드웨어 및 소프트웨어 전략을 책정할 수 있습니다.
- 폭넓은 시장 역학을 고려한 투자와 혁신 계획과 '핫' 매출 기회의 식별이 가능합니다.
- 엣지 AI와 클라우드 AI, 오픈소스와 클로즈드 소스, 지역별 발전, 소비 모델 등 AI 소프트웨어의 주요 동향을 파악할 수 있습니다.
주요 질문에 대한 답변 :
- 생성 AI 기업 도입은 자연언어처리(NLP) 소프트웨어 매출을 어느 정도 자극하는가?
- 엣지 AI 소프트웨어 매출 기회는 다른 AI 프레임워크 사이에서 어떻게 다른가?
- AI 소프트웨어 매출 중 오픈소스가 차지하는 비율은 어느 정도인가?
- 향후 최대 시장 기회를 초래하는 AI 소프트웨어 툴은 어떤 것인가?
조사 하이라이트 :
- 각 소프트웨어 툴별 소프트웨어 매출의 상세 내역
- 지역별 소프트웨어 매출의 종합적 내역
- 클라우드 AI에 대한 엣지 AI의 매출 기회의 예측
- AI 소프트웨어의 소비 모델 검토
- 오픈소스와 클로즈드 소스의 매출 예측
목차
- 테이블
- 차트
Actionable Benefits:
- Develop Artificial Intelligence (AI) hardware and software strategies with visibility over future revenue opportunities.
- Plan investment and innovation considering wider market dynamics and identify "hot" revenue opportunities.
- Become cognizant of key trends in AI software, including edge versus cloud AI, open versus closed source, regional developments, and consumption models.
Critical Questions Answered:
- To what extent will generative AI enterprise adoption stimulate Natural Language Processing (NLP) software revenue?
- How will edge AI software revenue opportunities vary across different AI frameworks?
- What share of AI software revenue will result from open-source?
- Which AI software tools offer the biggest market opportunity moving forward?
Research Highlights:
- A detailed breakdown of software revenue by each software tool.
- Comprehensive breakdown of software revenue by region.
- Forecast of edge against cloud AI revenue opportunities.
- Examination of AI software consumption models.
- Forecast of open and closed-source revenue opportunities.
Who Should Read This?
- AI software decision makers looking to refine their technical and commercial strategies.
- AI hardware leaders building product alignment and new capabilities in the software market.
- Market strategists aligning entry, competitor, and growth approaches to key software opportunities.
- Cloud provider innovation leaders looking to build a strong position in the AI software market across different frameworks and regions.
- Enterprise leaders and professional investors assessing the direction of the AI software market.
Table of Contents
Tables
- Table 1: Artificial Intelligence Software Revenue by Framework
- Table 2: Artificial Intelligence Software Revenue by Tool
- Table 3: Artificial Intelligence Software Revenue by Type
- Table 4: Artificial Intelligence Software Revenue by Region
- Table 5: Artificial Intelligence Software Revenue by Deployment Location
- Table 6: Artificial Intelligence MLOps Tool Revenue by Interface Type
- Table 7: Artificial Intelligence Software Revenue by Workload Type
- Table 8: Artificial Intelligence Software Revenue by Tool Type
- Table 9: Artificial Intelligence Software Revenue by Consumption Model
- Table 10: Artificial Intelligence Software Revenue by Source Code
- Table 11: Open-Source Software Revenue by Artificial Intelligence Framework
- Table 12: Closed-Source Software Revenue by Artificial Intelligence Framework
- Table 13: Edge AI Software Revenue by Artificial Intelligence Framework
- Table 14: Cloud AI Software Revenue by Artificial Intelligence Framework
- Table 15: Computer Vision Software Revenue by Region
- Table 16: Computer Vision Software Revenue by Tool
- Table 17: Computer vision Software Revenue by Deployment Location
- Table 18: Computer vision Software Revenue by Consumption Model
- Table 19: Computer vision Software Revenue by Source Code
- Table 20: Natural Language Processing Software Revenue by Region
- Table 21: Natural Language Processing Software Revenue by Tool
- Table 22: Natural Language Processing Software Revenue by Deployment Location
- Table 23: Natural Language Processing Software Revenue by Consumption Model
- Table 24: Natural Language Processing Software Revenue by Source Code
- Table 25: Graph-Based AI Models Software Revenue by Region
- Table 26: Graph-Based AI Models Software Revenue by Tool
- Table 27: Graph-Based AI Models Software Revenue by Deployment Location
- Table 28: Graph-Based AI Models Software Revenue by Consumption Model
- Table 29: Graph-Based AI Models Software Revenue by Source Code
- Table 30: Computer Vision Edge AI Software Revenue by Tool
- Table 31: Computer Vision Cloud AI Software Revenue by Tool
- Table 32: Natural Language Processing Edge AI Software Revenue by Tool
- Table 33: Natural Language Processing Cloud AI Software Revenue by Tool
- Table 34: Graph-Based AI Models Edge AI Software Revenue by Tool
- Table 35: Graph-Based AI Models Cloud AI Software Revenue by Tool
- Table 36: Edge AI Software Revenue by Workload Interface
- Table 37: Cloud AI Software Revenue by Workload Interface
- Table 38: Edge AI Software Revenue by Source Code
- Table 39: Cloud AI Software Revenue by Source Code
- Table 40: Computer Vision Inference Software Revenue
- Table 41: Computer Vision Training Software Revenue
- Table 42: Natural Language Processing Inference Software Revenue
- Table 43: Natural Language Processing Training Software Revenue by Tool
- Table 44: Graph-Based AI Model Inference Software Revenue by Tool
- Table 45: Graph-Based AI Model Training Software Revenue by Tool
- Table 46: Training Software Revenue
- Table 47: Inferencing Software Revenue
Charts
- Chart 1: Artificial Intelligence Software Revenue by Framework
- Chart 2: Artificial Intelligence MLOps Tool Revenue by Type
- Chart 3: Edge AI Software Revenue by Framework
- Chart 4: Artificial Intelligence Software Revenue by Skill Level
- Chart 5: Comparing Regional AI Software Revenue
- Chart 6: Natural Language Processing Software Revenue by Type
- Chart 7: AI Software Revenue by Deployment Location
- Chart 8: Regional AI Software Revenue by Framework
- Chart 9: Cloud and Edge AI Software Revenue by Source Code
- Chart 10: Cloud and Edge AI Software by Workload Interface
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