2021 年全球人工智能市場趨勢

從業務優化到研發推廣，企業正在利用人工智能 (AI) 來推動數字化轉型並支持業務成果。

在本報告中，我們將針對全球企業進行人工智能引入狀況調查。受訪者選自金融服務、醫療保健、零售、政府、技術和製造業等多個行業的高級 IT 決策者。調查的主要主題是人工智能採用的當前狀態、人工智能採用的關鍵組織目標、對特定人工智能相關技術的需求以及主要的人工智能採用模型。

目錄

調查目的及調查方法

• 調查目的和方法
• 受訪者的個人資料

AI引入趨勢

• 重點
• 許多組織已開始採用 AI，但仍處於早期部署階段。
• 公司將人工智能視為實現更高效率的一種手段，也是推動數據中心化和創新的催化劑。
• 引入人工智能，利用多種技術支持用例
• 公有雲是人工智能部署的主要模式
• 數據隱私、安全和治理是人工智能實施的關鍵問題
• 北美組織引領人工智能解決方案的部署
• 旅遊、酒店和醫療保健引領整個行業採用人工智能
• IT 運營已成為利用 AI 的主要業務流程

未來下落

• 公司尋求第三方服務提供商的數據遷移和集成支持以創造新機會
• IT 服務提供商能夠很好地利用增長機會獲利 - 提供集成能力並專注於利用行業知識增強的新技術
• 除了產品/服務質量，技術供應商和服務提供商需要關注數據安全
• 展品清單
• 免責聲明

Highlights from the 2021 Frost & Sullivan Global AI Survey

From optimizing operations to driving R&D, enterprises are leveraging artificial intelligence (AI) to drive digital transformation and support business outcomes. However, where are global organizations in this journey and what are their adoption drivers and restraints?

In this study, Frost & Sullivan presents the key findings of a survey conducted among global enterprises on their state of adoption of AI. Respondents were drawn from senior IT decision makers across multiple verticals such as financial services, healthcare, retail, government, technology, and manufacturing. The major themes explored in the survey include the current state of AI deployment, key organizational goals of AI implementation, the demand for specific AI-related technologies, and the main AI deployment models.

The study surveys technology vendors and service providers to obtain a view on AI priorities and help end users understand the benefits and the challenges of AI (as cited by global peers). In addition, the study gives readers an understanding of the prominent AI-related technologies that enterprises are adopting. It also offers insight into the main challenges enterprises face in their AI adoption journey.

Table of Contents

Research Objectives and Methodology

• Research Objectives and Methodology
• Respondent Profile

State of AI Adoption

• Key Takeaways
• While Many Organizations have Initiated AI Adoption, it is Still in the Early Stage of Deployment
• Enterprise Customers View AI as a Means to Achieve Greater Efficiency and as a Catalyst to Boost Data Centricity and Innovation
• AI Deployments Leverage Multiple Technologies to Support Use-cases
• Public Cloud is the Dominant Model of AI Deployment.
• Data Privacy, Security, and Governance is a Key Challenge for AI Implementation
• North American Organizations Lead the Deployment of AI Solutions
• Travel and Hospitality and Healthcare Lead AI Deployment Across Verticals
• IT Operations is Emerging as a Key Business Process that Leverages AI

The Way Forward

• Enterprises Seek Data Migration and Integration Support to Create New Opportunities for Third-party Service Providers
• IT Service Providers are Well Positioned to Monetize Growth Opportunities-Given their Integration Capabilities and Focus on Emerging Technologies Augmented with Industry Knowledge
• Besides Product/Service Quality, Technology Vendors and Service Providers will Need to Demonstrate Strong Focus on Data Security
• List of Exhibits
• Legal Disclaimer