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市场调查报告书
商品编码
1725020

全球人工智慧IT服务成长机会

Global Artificial Intelligence Information Technology Services Growth Opportunities
出版日期: | 出版商: Frost & Sullivan | 英文 27 Pages | 商品交期: 最快1-2个工作天内

价格
简介目录

IT服务供应商在加速人工智慧应用方面发挥关键作用

全球人工智慧IT服务成长机会研究对全球人工智慧IT服务的现状和未来前景进行了全面的分析。该研究借鉴了最近对商业决策者进行的一项调查的结果，确定了影响全球行业的关键驱动因素和限制因素。

在策略方面，我们正在探索服务供应商如何透过增强咨询和顾问服务、利用基础模型提供特定于人工智慧的服务以及开发端到端人工智慧功能来实现差异化。该研究强调了透过开发特定产业的解决方案和采用解决道德、环境和社会问题的负责任的人工智慧实践来确保永续成长的重要性。

分析重点介绍了塑造人工智慧 IT 服务市场的关键参与企业及其提供客户价值的策略。最后，它确定了可行的成长机会，包括产业专用的人工智慧解决方案、整合服务以及咨询和策略咨询服务，为服务供应商提供了利用一些不断变化的市场需求的蓝图。

人工智慧对IT服务业三大策略挑战的影响

内部挑战

为什么？

  • 将人工智慧融入企业是一个复杂且多方面的过程，涉及多项内部挑战，包括资料品质和可用性、成本、技能差距、旧有系统整合和道德问题。
  • 企业一直在寻找能够帮助他们应对采用和扩展人工智慧的技术和组织挑战的人工智慧供应商和服务供应商。

弗罗斯特的观点

  • 人工智慧服务供应商将专注于开发端到端人工智慧功能，并在企业人工智慧采用中展现从实施合作伙伴到策略顾问的不断发展的角色。
  • 他们可能会继续与新兴企业和科技巨头建立策略伙伴关係，以增强他们的人工智慧能力。
  • 此外，持续投资研发以探索新技术并开发创新工具、平台和服务将简化人工智慧整合的采用。

颠覆性技术

为什么？ ：

  • 使用基础模型，而不是建立专门用于特定任务的模型，允许公司从预先训练的模型开始并使其适应不同的用例，从而使人工智慧开发民主化。
  • 企业在利用大规模语言模型 (LLM) 的同时，也在探索规模较小、客製化的训练模型，为各种规模的企业提供经济高效、适应性强的人工智慧解决方案。

弗罗斯特的观点

  • 服务供应商将继续与主要基础模型供应商建立策略伙伴关係。
  • 服务供应商可能会增加使用小型语言模型 (SLM) 和特定产业数据和专业知识来创建独特的高价值解决方案。
  • 服务供应商也可能建立创新实验室/A-lab，让客户试验 LLM 和专有模型，促进更深入的研究。

竞争日益激烈

为什么？ ：

  • 服务供应商将与多个 AI 生态系统参与者竞争，超大规模资料中心业者、全球系统整合(GSI)、专注于 AI 的新兴企业、顾问公司，甚至希望抵消硬体销售收益下降的传统OEM。

弗罗斯特的观点

  • 服务供应商要想在人工智慧发展中保持领先地位，就必须投资于人才发展，以确保拥有能够提供先进人工智慧解决方案的熟练劳动力。
  • 对人工智慧道德实践（包括隐私、安全、信任和安全）的关注仍将十分重要。优先考虑道德考虑的提供者可能更有能力建立客户信任并克服采用障碍。

成长动力

人工智慧能够从全球不断增长的企业和客户数据中提取价值，这将推动其应用

数据的快速成长是推动人工智慧服务普及的关键因素。物联网设备的激增和数位足迹的不断扩大导致数据量呈指数级增长，全球企业迫切需要人工智慧工具。这些工具可以处理和分析数据、发现模式和相关性，并得出有意义的见解，从而可以在时间紧迫的情况下发现新的竞争优势。

成本节约和效率提升是推动人工智慧应用的强大经济驱动力

越来越多的企业意识到人工智慧自动化的潜力，它可以显着降低营运成本，同时提高预测和决策的准确性。人工智慧系统的一致营运能力使其成为寻求优化营运和资源配置的企业有吸引力的投资。

成熟技术推动市场成长

运算能力和 GPU 功能的不断提升，使得 AI 系统更加强大、有效率。随着 AI/ML 演算法和 LLM 的进步，AI 解决方案现在可以提供更可预测的结果，并实现自动化和更高的效率。此外，预先训练的模型和工具的可用性最大限度地减少了技术障碍并使人工智慧解决方案能够快速采用。云端处理基础设施的增强使得各种规模的组织能够更轻鬆地存取和扩展这些功能。

成长抑制因素

实现人工智慧和机器学习演算法所需的干净数据有限

AI 和 ML 演算法的成功取决于可用的企业资料的品质。在全球人工智慧 IT 服务日益增长的机会中，干净、标准化的数据对于技术创造价值和实现业务成果至关重要。对于大多数采用人工智慧的企业来说，取得干净、可用的资料集是一项挑战。

明确的投资收益(ROI)

公司不愿采用人工智慧解决方案，因为他们无法估计投资报酬率。因此，供应商需要帮助企业预测部署AI解决方案的投资报酬率。

缺乏领导承诺

人工智慧服务需要在人力、技术和基础设施方面进行大量投资。如果没有强有力的领导承诺，人工智慧倡议的预算分配将仍然有限，而没有统一策略的人工智慧投资将导致效率低下和零碎的人工智慧采用。

法律规范和道德规范缺乏明确性

监管和道德问题，包括限制存取预先匿名资料的隐私考虑、智慧财产权问题、缺乏演算法透明度、演算法偏见以及工作安全担忧，阻碍了人工智慧市场的成长。

目录

全球人工智慧IT服务成长机会

  • 战略问题
  • 为何成长变得越来越困难？
  • The Strategic Imperative 8（TM）
  • 人工智慧对IT服务业三大策略挑战的影响
  • 成长要素
  • 企业采用人工智慧正进入实施阶段
  • IT服务供应商在AI价值链中扮演关键角色

成长机会分析

  • 成长动力
  • 成长抑制因素
  • AI IT服务趋势
  • 加强咨询和顾问服务：全球服务供应商的关键成长机会
  • AI IT服务趋势
  • 在基础模型之上建构专业化的AI服务
  • AI IT服务趋势
  • 开发端到端人工智慧能力：全球服务供应商的策略要务
  • AI IT服务趋势
  • 开发产业专用的解决方案以加速人工智慧的采用
  • AI IT服务趋势
  • 利用道德人工智慧强化你的价值主张

采取行动的公司

  • 公司在行动：联想
  • 正在行动的公司：日立
  • 公司在行动：印孚瑟斯
  • 正在行动的公司：NTT Data

成长机会领域

  • 成长机会1：咨询和顾问服务
  • 成长机会2：产业/功能用途
  • 成长机会3：整合服务

后续步骤Next steps

  • 成长机会的益处和影响
  • 后续步骤Next steps
  • 图片列表
  • 免责声明
简介目录
Product Code: PFR1-69

IT Service Providers are Playing an Important Role in Accelerating AI Deployments

The Global Artificial Intelligence Information Technology Services Growth Opportunities study provides a comprehensive analysis of the current landscape and the future prospects of AI IT services worldwide. It draws on insights from a recent enterprise decision-maker survey and identifies key drivers and restraints shaping the industry globally.

Strategically, the study explores how service providers can differentiate themselves by strengthening advisory and consulting services, leveraging foundational models to create specialized AI offerings, and developing end-to-end AI capabilities. The study underscores the importance of developing industry-specific solutions and adopting responsible AI practices to address ethical, environmental, and social considerations, ensuring sustainable growth.

The analysis highlights key participants shaping the AI IT services market and their strategies to deliver client value. Finally, the study identifies actionable growth opportunities, such as industry-specific AI solutions, integration services, and consulting and strategic advisory services, providing a roadmap for service providers to capitalize on some of the evolving market demands.

The Impact of the Top 3 Strategic Imperatives on the AI Information Technology Services Industry

Internal Challenges

Why:

  • Integrating AI into an enterprise is a complex and multifaceted process that involves several internal challenges, such as data quality and availability, cost, skills gap, legacy system integration, and ethical concerns.
  • Enterprises are constantly looking for AI vendors and service providers that can address both technical and organizational challenges in AI adoption and scaling.

Frost Perspective:

  • AI service providers will focus on developing end-to-end AI capabilities to demonstrate their evolving role from implementation partners to strategic advisors in the enterprise AI journey.
  • They will continue to establish strategic partnerships with start-ups and technology giants to enhance their AI capabilities.
  • Furthermore, continuous investment in R&D to explore new technologies and develop innovative tools, platforms, and services will simplify the adoption of integrating AI.

Disruptive Technologies

Why:

  • Instead of building specialized models for specific tasks, foundational models allow organizations to start with a pre-trained model and adapt it to various applications, democratizing AI development.
  • While companies are leveraging large language models (LLMs), they are also exploring smaller, custom-trained models that offer cost-effective, adaptable AI solutions for businesses of all sizes.

Frost Perspective:

  • Service providers will continue to establish strategic partnerships with leading foundational model vendors.
  • They will promote the use of small language models (SLMs) with industry-specific data and expertise to create unique, high-value solutions.
  • Service providers will also establish innovation labs/A labs to allow clients to experiment with LLMs and proprietary models to foster deeper research.

Competitive Intensity

Why:

  • Service providers compete with several AI ecosystem participants, including hyperscalers, global system integrators (GSIs), specialized AI start-ups, consulting firms, and even traditional OEMs, which look to offset declining revenues from hardware sales.

Frost Perspective:

  • Investing in talent development to ensure a skilled workforce capable of delivering advanced AI solutions will be crucial for service providers to stay at the forefront of AI developments.
  • Focusing on ethical AI practices, including privacy, security, trust, and safety, will remain important. Providers that prioritize ethical considerations will be better positioned to build trust among clients and overcome adoption barriers.

Growth Drivers

AI's Ability to Unlock Value from the Growing Global Volumes of Enterprise and Customer Data Drives its Uptake

Data proliferation has become a significant catalyst for AI service adoption. Data's exponential growth, driven by increased IoT device adoption and expanding digital footprints, has generated an urgent need for AI tools in enterprises globally. These tools process, analyze, find patterns and correlations, and derive meaningful insights, uncovering new competitive advantages in a limited time.

Cost Reduction and Efficiency Improvements Represent Compelling Economic Drivers for AI Adoption

A growing number of enterprises recognize AI automation's potential to significantly reduce operational costs while improving accuracy in predictions and decision-making. AI systems' ability to operate consistently has made them attractive investments for businesses seeking to optimize their operations and resource allocation.

Maturing Technologies Drive Market Growth

Continuous improvements in computing power and GPU capabilities have made AI systems more powerful and efficient. Owing to advancements in AI/ML algorithms and LLMs, AI solutions now offer more predictable outcomes, enabling automation and higher efficiencies. In addition, the availability of pre-trained models and tools minimizes technological barriers and supports faster AI solution adoption. Enhanced cloud computing infrastructure has made these capabilities more accessible and scalable for organizations of all sizes.

Growth Restraints

Limited Availability of Clean Data to Implement AI and ML Algorithms

AI and ML algorithms' success depends on the quality of available enterprise data. Clean and standardized data is pivotal to **Title:** Global Artificial Intelligence Information Technology Services Growth Opportunities technologies' ability to deliver value and business outcomes. Accessing clean and usable datasets is challenging for most enterprises adopting AI.

Clear Return on Investment (ROI)

Enterprises are reluctant to adopt AI solutions as they cannot estimate the ROI, mainly because the high initial investment increases costs before the expected return date. Thus, vendors must help enterprises foresee the ROI in implementing AI solutions.

Lack of Leadership Commitment

AI services require significant investments in talent, technology, and infrastructure. Without strong leadership commitment, budget allocation for AI initiatives will remain limited, and investing in AI without a unified strategy will lead to inefficiencies and fragmented AI adoption.

Lack of Clarity Concerning Regulatory Frameworks and Ethical Practices

Regulatory and ethical issues, such as privacy considerations that restrict access to data before anonymization, intellectual property issues, a lack of algorithm transparency, algorithm biases, and job security concerns, will hinder the AI market's growth.

Table of Contents

Global Artificial Intelligence Information Technology Services Growth Opportunities PFR1-

  • Strategic Imperatives
  • Why is it Increasingly Difficult to Grow?
  • The Strategic Imperative 8™
  • The Impact of the Top 3 Strategic Imperatives on the AI Information Technology Services Industry
  • Growth Generator
  • Enterprise AI Deployments are Moving to the Implementation Phase
  • IT Service Providers Play a Pivotal Role in the AI Value Chain

Growth Opportunity Analysis

  • Growth Drivers
  • Growth Restraints
  • AI IT Service Trends
  • Strengthening Advisory and Consulting Services: A Key Growth Opportunity for Service Providers Globally
  • AI IT Service Trends
  • Building Specialized AI Services on Foundational Models
  • AI IT Service Trends
  • Developing End-to-End AI Capabilities: A Strategic Imperative for Global Service Providers
  • AI IT Service Trends
  • Developing Industry-specific Solutions for Accelerated AI Adoption
  • AI IT Service Trends
  • Strengthening Value Propositions with Ethical AI

Companies to Action

  • Company to Action: Lenovo
  • Company to Action: Hitachi
  • Company to Action: Infosys
  • Company to Action: NTT Data

Growth Opportunity Universe

  • Growth Opportunity 1: Consulting and Advisory Services
  • Growth Opportunity 2: Industry Vertical/Function-specific Applications
  • Growth Opportunity 3: Integration Services

Next Steps

  • Benefits and Impacts of Growth Opportunities
  • Next Steps
  • List of Exhibits
  • Legal Disclaimer