人工智慧和機器學習實施平台的成長機會

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個工作天內

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簡介目錄

人工智慧的進步和上市策略使人工智慧平台供應商成為技術採用的關鍵參與者

在世界各地，企業正在重振地緣政治動盪的市場，重點是釋放資料的潛力並利用人工智慧 (AI) 來支持業務成果。大約 87% 的公司認為人工智慧和機器學習 (ML) 對於實現增加收益、提高業務效率和改善客戶體驗等業務目標非常重要。此外，各行各業的新興大趨勢正在將人工智慧技術推向數位轉型的前沿，引發商業模式創新、提升業務效率、顛覆價值創造和策略差異化，我們正在為推動創新樹立新標竿。

隨著人工智慧/機器學習實施平台的出現，公司可以快速啟動他們的人工智慧採用之旅。這些實施平台支援建置、部署和監控 ML 模型開發和操作流程。它還促進了從資料攝取到業務洞察可視化的端到端機器學習生命週期開發過程。

本報告涵蓋了人工智慧和機器學習實施平台行業的主要新興趨勢，提供了對該行業平台能力的一些見解，並討論了影響人工智慧市場的驅動和抑制因素。此外，該研究還為平台供應商提供了與開發企業客戶可以利用的特定產業業務模型相關的成長機會的見解。

人工智慧——全球企業的優先技術
基於人工智慧的模型和框架幫助企業做出更有效率的決策
企業在人工智慧之旅上不斷取得進展
生長促進因子
成長阻礙因素
商業平台的增加使公司不再需要建立自己的平台
AI/ML實施平台的定義與細分
AI 和 ML 實施平台是開啟 AI 採用之旅的關鍵推動者

成長環境—AI/ML實施平台

AI/ML 實施平台產業的主要趨勢
AI/ML 平台正在擴展其功能以提供端到端生命週期模型部署
更重視以角色為基礎的互動，使企業採用民主化
GenAI 功能的整合正在增強模型開發流程
平台供應商正與IT服務公司合作加速GTM
透過與公共雲端服務供應商的策略合作夥伴關係，擴大對人工智慧工具和基礎設施服務的訪問

公司採取行動 (C2A)

Altair RapidMiner
Dataiku
Alteryx
Databricks
DataRobot

成長機會宇宙

成長機會 1 - 產業產品
圖表清單
免責聲明

簡介目錄

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