2021 年全球人工智能市场趋势

从业务优化到研发推广，企业正在利用人工智能 (AI) 来推动数字化转型并支持业务成果。

在本报告中，我们将针对全球企业进行人工智能引入状况调查。受访者选自金融服务、医疗保健、零售、政府、技术和制造业等多个行业的高级 IT 决策者。调查的主要主题是人工智能采用的当前状态、人工智能采用的关键组织目标、对特定人工智能相关技术的需求以及主要的人工智能采用模型。

目录

调查目的及调查方法

• 调查目的和方法
• 受访者的个人资料

AI引入趋势

• 重点
• 许多组织已开始采用 AI，但仍处于早期部署阶段。
• 公司将人工智能视为实现更高效率的一种手段，也是推动数据中心化和创新的催化剂。
• 引入人工智能，利用多种技术支持用例
• 公有云是人工智能部署的主要模式
• 数据隐私、安全和治理是人工智能实施的关键问题
• 北美组织引领人工智能解决方案的部署
• 旅游、酒店和医疗保健引领整个行业采用人工智能
• IT 运营已成为利用 AI 的主要业务流程

未来下落

• 公司寻求第三方服务提供商的数据迁移和集成支持以创造新机会
• IT 服务提供商能够很好地利用增长机会获利 - 提供集成能力并专注于利用行业知识增强的新技术
• 除了产品/服务质量，技术供应商和服务提供商需要关注数据安全
• 展品清单
• 免责声明

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