供应链中的人工智慧：车队管理解决方案

本报告探讨了人工智慧在供应链中的前景，包括领先的基于人工智慧的车队管理解决方案的概况、开发和应用人工智慧解决方案的最佳实践，以及针对最终用户和解决方案提供商的建议。

实际好处：

• 优化您的 AI 企业和基础设施/资产投资，以最大限度地提高效率和盈利能力。
• 了解人工智慧应用的市场现况与未来前景
• 利用市场上领先的用例和解决方案实现搜寻数位化

重要问题的答案：

• 人工智慧在车队和运输管理软体中的创收机会有哪些？
• 阻碍车队管理中 AI 解决方案的开发和实施的主要课题是什么？
• 车队应如何制定 AI 采用策略，以充分利用 AI？

研究亮点：

• 领先的人工智慧为基础的车队管理解决方案简介
• 从解决方案提供者和最终用户的角度识别市场空白
• 为最终用户和解决方案提供者提供有关开发和应用 AI 解决方案的最佳实践的建议

目录

主要发现

市场状况

各大公司的努力

市场空白

获利潜力

建议和最佳实践

Actionable Benefits:

• Optimize Artificial Intelligence (AI)-based investments in enterprises and infrastructure/assets to maximize efficiency and profitability.
• Understand the state of the market and future outlook on AI applications.
• Take a closer look at prominent use cases and solutions in the market.

Critical Questions Answered:

• What is the revenue potential of AI-enabled revenue in fleet and transport management software?
• What are some of the key challenges hindering the development and implementation of AI solutions in fleet management?
• How should fleets build their AI implementation strategy to reap maximum benefits?

Research Highlights:

• Profiles of key AI-based fleet management solutions.
• An in-depth review of market gaps from solution provider and end-user perspectives.
• Recommendations to end users and solution providers on best practices related to AI solutions development and application.

Who Should Read This?

• Fleet management solutions business development, sales, product development, and marketing leaders.
• Fleet managers, safety managers, and fleet operations executives.
• Telco, networking, semiconductor, and module vendors.

TABLE OF CONTENTS

Key Findings

State of the Market

What are Key Players Doing

Market Gaps

Revenue Potential

Recommendations Best Practices