人工智慧和机器学习实施平台的成长机会

Artificial Intelligence and Machine Learning Implementation Platform Growth Opportunities

出版日期: 2023年11月23日 | 出版商:

Frost & Sullivan | 英文 47 Pages | 商品交期: 最快1-2个工作天内

价格

简介目录

人工智慧的进步和上市策略使人工智慧平台供应商成为技术采用的关键参与者

在世界各地，企业正在重振地缘政治动盪的市场，重点是释放资料的潜力并利用人工智慧 (AI) 来支持业务成果。大约 87% 的公司认为人工智慧和机器学习 (ML) 对于实现增加收益、提高业务效率和改善客户体验等业务目标非常重要。此外，各行各业的新兴大趋势正在将人工智慧技术推向数位转型的前沿，引发商业模式创新、提升业务效率、颠覆价值创造和策略差异化，我们正在为推动创新树立新标竿。

随着人工智慧/机器学习实施平台的出现，公司可以快速启动他们的人工智慧采用之旅。这些实施平台支援建置、部署和监控 ML 模型开发和操作流程。它还促进了从资料摄取到业务洞察可视化的端到端机器学习生命週期开发过程。

本报告涵盖了人工智慧和机器学习实施平台行业的主要新兴趋势，提供了对该行业平台能力的一些见解，并讨论了影响人工智慧市场的驱动和抑制因素。此外，该研究还为平台供应商提供了与开发企业客户可以利用的特定产业业务模型相关的成长机会的见解。

人工智慧——全球企业的优先技术
基于人工智慧的模型和框架帮助企业做出更有效率的决策
企业在人工智慧之旅上不断取得进展
生长促进因子
成长阻碍因素
商业平台的增加使公司不再需要建立自己的平台
AI/ML实施平台的定义与细分
AI 和 ML 实施平台是开启 AI 采用之旅的关键推动者

成长环境—AI/ML实施平台

AI/ML 实施平台产业的主要趋势
AI/ML 平台正在扩展其功能以提供端到端生命週期模型部署
更重视以角色为基础的互动，使企业采用民主化
GenAI 功能的整合正在增强模型开发流程
平台供应商正与IT服务公司合作加速GTM
透过与公共云端服务供应商的策略合作伙伴关係，扩大对人工智慧工具和基础设施服务的访问

公司采取行动 (C2A)

Altair RapidMiner
Dataiku
Alteryx
Databricks
DataRobot

成长机会宇宙

成长机会 1 - 产业产品
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简介目录

Product Code: PF65-69

Advancements in AI and Go-to-Market Strategies Position AI Platform Vendors as Key Players in the Technology s Adoption

Globally, businesses are reestablishing themselves in geopolitically unstable markets, with an emphasis on unlocking data's potential and leveraging artificial intelligence (AI) to support business outcomes. About 87% of enterprises believe AI and machine learning (ML) are important in achieving business goals to grow revenue, increase operational efficiencies, and improve the customer experience. Also, megatrends emerging across industries are pushing AI technologies to the forefront of digital transformation, sparking innovation in business models, turbocharging operational efficiencies, disrupting value creation, and setting new benchmarks to drive strategic differentiation.

The emergence of AI and ML implementation platforms enables enterprises to jumpstart their AI adoption journey. These implementation platforms provide support in building, deploying, and monitoring ML model development and operationalization processes. They also facilitate end-to-end ML life cycle development processes-from data ingestion to the visualization of business insights.

This report highlights key emerging trends in the AI and ML implementation platform industry, offers insights into a few industry platform capabilities, and discusses drivers and restraints that impact the AI market. Additionally, the research offers insights for platform vendors into a growth opportunity related to developing industry-specific business models that enterprise customers can leverage.

Strategic Imperatives

Why is it Increasingly Difficult to Grow?
The Strategic Imperative 8™
The Impact of the Top 3 Strategic Imperatives on Artificial Intelligence (AI) and Machine Learning (ML) Implementation Platforms
Growth Opportunities Fuel the Growth Pipeline Engine™

Background-AI and ML Implementation Platforms

AI-A Technology Priority for Global Enterprises
AI-based Models and Frameworks Drive Efficiency in Enterprise Decision-making
Enterprises Are Advancing on Their AI Adoption Journeys
Growth Drivers
Growth Restraints
Increased Commercial Platforms Enable Enterprises to Shift from the Need to Build In-house Platforms
AI and ML Implementation Platform-Definition and Segmentation
AI and ML Implementation Platforms Are Primary Enablers in Kickstarting the AI Adoption Journey

Growth Environment-AI and ML Implementation Platforms

Key Trends in the AI and ML Implementation Platform Industry
AI/ML Platforms are Expanding Capabilities to Provide End-to-end Life Cycle Model Deployment
Increased Focus on Role-based Interaction Is Democratizing Enterprise Adoption
Integrating GenAI Capabilities Is Enhancing the Model Development Process
Platform Vendors Are Partnering with IT Services Companies to Accelerate GTM
Strategic Partnerships with Public Cloud Service Providers to Extend Access to AI Tools and Infrastructure Services