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1725020

全球人工智慧IT服務成長機會

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個工作天內

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簡介目錄

IT服務供應商在加速人工智慧應用方面發揮關鍵作用

全球人工智慧IT服務成長機會研究對全球人工智慧IT服務的現狀和未來前景進行了全面的分析。該研究借鑒了最近對商業決策者進行的一項調查的結果，確定了影響全球行業的關鍵促進因素和限制因素。

在策略方面，我們正在探索服務供應商如何透過增強諮詢和顧問服務、利用基礎模型提供特定於人工智慧的服務以及開發端到端人工智慧功能來實現差異化。該研究強調了透過開發特定產業的解決方案和採用解決道德、環境和社會問題的負責任的人工智慧實踐來確保永續成長的重要性。

分析重點介紹了塑造人工智慧 IT 服務市場的關鍵參與企業及其提供客戶價值的策略。最後，它確定了可行的成長機會，包括產業專用的人工智慧解決方案、整合服務以及諮詢和策略諮詢服務，為服務供應商提供了利用一些不斷變化的市場需求的藍圖。

人工智慧對IT服務業三大策略挑戰的影響

內部挑戰

為什麼？

  • 將人工智慧融入企業是一個複雜且多方面的過程，涉及多項內部挑戰，包括資料品質和可用性、成本、技能差距、舊有系統整合和道德問題。
  • 企業一直在尋找能夠幫助他們應對採用和擴展人工智慧的技術和組織挑戰的人工智慧供應商和服務供應商。

弗羅斯特的觀點

  • 人工智慧服務供應商將專注於開發端到端人工智慧功能，並在企業人工智慧採用中展現從實施合作夥伴到策略顧問的不斷發展的角色。
  • 他們可能會繼續與新興企業和科技巨頭建立策略夥伴關係，以增強他們的人工智慧能力。
  • 此外，持續投資研發以探索新技術並開發創新工具、平台和服務將簡化人工智慧整合的採用。

顛覆性技術

為什麼？ ：

  • 使用基礎模型，而不是建立專門用於特定任務的模型，允許公司從預先訓練的模型開始並使其適應不同的用例，從而使人工智慧開發民主化。
  • 企業在利用大規模語言模型 (LLM) 的同時，也在探索規模較小、客製化的訓練模型，為各種規模的企業提供經濟高效、適應性強的人工智慧解決方案。

弗羅斯特的觀點

  • 服務供應商將繼續與主要基礎模型供應商建立策略夥伴關係。
  • 服務供應商可能會增加使用小型語言模型 (SLM) 和特定產業數據和專業知識來創建獨特的高價值解決方案。
  • 服務供應商也可能建立創新實驗室/A-lab，讓客戶試驗 LLM 和專有模型，促進更深入的研究。

競爭日益激烈

為什麼？ ：

  • 服務供應商將與多個 AI 生態系統參與者競爭，超大規模資料中心業者、全球系統整合(GSI)、專注於 AI 的新興企業、顧問公司，甚至希望抵消硬體銷售收益下降的傳統OEM。

弗羅斯特的觀點

  • 服務供應商要想在人工智慧發展中保持領先地位，就必須投資於人才發展，以確保擁有能夠提供先進人工智慧解決方案的熟練勞動力。
  • 對人工智慧道德實踐（包括隱私、安全、信任和安全）的關注仍將十分重要。優先考慮道德考慮的提供者可能更有能力建立客戶信任並克服採用障礙。

成長動力

人工智慧能夠從全球不斷成長的企業和客戶數據中提取價值，這將推動其應用

數據的快速成長是推動人工智慧服務普及的關鍵因素。物聯網設備的激增和數位足跡的不斷擴大導致數據量呈指數級成長，全球企業迫切需要人工智慧工具。這些工具可以處理和分析數據、發現模式和相關性，並得出有意義的見解，從而可以在時間緊迫的情況下發現新的競爭優勢。

成本節約和效率提升是推動人工智慧應用的強大經濟驅動力

越來越多的企業意識到人工智慧自動化的潛力，它可以顯著降低營運成本，同時提高預測和決策的準確性。人工智慧系統的一致營運能力使其成為尋求最佳化營運和資源配置的企業有吸引力的投資。

成熟技術推動市場成長

運算能力和 GPU 功能的不斷提升，使得 AI 系統更加強大、有效率。隨著 AI/ML 演算法和 LLM 的進步，AI 解決方案現在可以提供更可預測的結果，並實現自動化和更高的效率。此外，預先訓練的模型和工具的可用性最大限度地減少了技術障礙並使人工智慧解決方案能夠快速採用。雲端處理基礎設施的增強使得各種規模的組織能夠更輕鬆地存取和擴展這些功能。

成長抑制因素

實現人工智慧和機器學習演算法所需的乾淨數據有限

AI 和 ML 演算法的成功取決於可用的企業資料的品質。在全球人工智慧 IT 服務日益成長的機會中，乾淨、標準化的數據對於技術創造價值和實現業務成果至關重要。對於大多數採用人工智慧的企業來說，取得乾淨、可用的資料集是一項挑戰。

明確的投資收益(ROI)

公司不願採用人工智慧解決方案，因為他們無法估計投資報酬率。因此，供應商需要幫助企業預測部署AI解決方案的投資報酬率。

缺乏領導承諾

人工智慧服務需要在人力、技術和基礎設施方面進行大量投資。如果沒有強力的領導承諾，人工智慧舉措的預算分配將仍然有限，而沒有統一策略的人工智慧投資將導致效率低下和零碎的人工智慧採用。

法律規範和道德規範缺乏明確性

監管和道德問題，包括限制存取預先匿名資料的隱私考慮、智慧財產權問題、缺乏演算法透明度、演算法偏見以及工作安全擔憂，阻礙了人工智慧市場的成長。

目錄

全球人工智慧IT服務成長機會

  • 戰略問題
  • 為何成長變得越來越困難？
  • The Strategic Imperative 8（TM）
  • 人工智慧對IT服務業三大策略挑戰的影響
  • 成長要素
  • 企業採用人工智慧正進入實施階段
  • IT服務供應商在AI價值鏈中扮演關鍵角色

成長機會分析

  • 成長動力
  • 成長抑制因素
  • AI IT服務趨勢
  • 加強諮詢和顧問服務：全球服務供應商的關鍵成長機會
  • AI IT服務趨勢
  • 在基礎模型之上建構專業化的AI服務
  • AI IT服務趨勢
  • 開發端到端人工智慧能力：全球服務供應商的策略要務
  • AI IT服務趨勢
  • 開發產業專用的解決方案以加速人工智慧的採用
  • AI IT服務趨勢
  • 利用道德人工智慧強化你的價值主張

採取行動的公司

  • 公司在行動：聯想
  • 正在行動的公司：日立
  • 公司在行動：印孚瑟斯
  • 正在行動的公司：NTT Data

成長機會領域

  • 成長機會1：諮詢和顧問服務
  • 成長機會2：產業/功能用途
  • 成長機會3：整合服務

後續步驟Next steps

  • 成長機會的益處和影響
  • 後續步驟Next steps
  • 圖片列表
  • 免責聲明
簡介目錄
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