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市場調查報告書

商品編碼

1892079

知識經濟轉型，2025-2035年

Knowledge Economy Transformations, 2025-2035

出版日期: 2025年10月15日 | 出版商:

Frost & Sullivan | 英文 71 Pages | 商品交期: 最快1-2個工作天內

價格

簡介目錄

充分利用人力資本、數位基礎設施和人工智慧（HiDiAi），塑造未來知識經濟

全球知識經濟正處於轉型關鍵階段。未來十年的成長將取決於人力資本、數位基礎設施和人工智慧（AI）的結合。這三大要素構成了Frost & Sullivan的HiDiAi框架。從人工智慧驅動的生產力轉型到人口結構變化和對數位獨立的追求，各國經濟改變知識的創造、規模和收益化方式。

在此轉型過程中，各國政府正大力發展STEM（科學、技術、工程和數學）人才，企業正積極採用智慧製造和現代專業服務，金融體係也透過數位互聯互通變得更加包容。到2035年，那些認知到高數位化和人工智慧（HiDiAi）各組成部分互聯互通的國家將加速創新，創造更多價值，並建構更強大的經濟體。

最新的建議檢驗於2035年將重塑知識經濟的關鍵力量、技術促進因素和政策工具。這些建議探討了企業培訓專案如何彌補人才缺口，知識型供應鏈和智慧技術如何改變產業競爭格局，以及人機協作在管治和商業領域的發展趨勢。此外，建議還引進了「知識密集度評分」，該評分基於高知高智商（HiDiAi）要素對各行業進行評估，目的是幫助政策制定者和企業識別未來的領導者和落後者。

隨著經濟體日益知識主導和相互關聯，國家宏觀經濟的成功將需要從傳統的產業策略轉向整合人力、數位和人工智慧的系統。那些及早採取行動的國家、企業和投資者將成為下一代全球成長模式的核心。

主要主題：

1.密集型產業的新成長機會
2.HiDiAi智慧創新框架
3.各行業知識密集度得分
4.促進STEM教育、本地數位獨立和人工智慧應用的關鍵政策槓桿
5.未來的關鍵經營模式將涵蓋平台開發、智慧技術和人機協作。

分析範圍

知識經濟是一種經濟體系，其價值創造是透過人類智慧（Hi）、數位智慧（Di）和人工智慧（Ai）的結合來實現的。這三大支柱協同運作，在產業和社會各界廣泛創造、傳播和利用知識。
本研究檢驗了2024年至2035年間各產業和子部門的知識密集度將如何演變。它指出了應該在哪些領域進行投資，應該實施哪些政策，以及未來應該培養哪些技能。

本次調查的目的

它對 12個主要行業和 60 多個子行業的知識密集度進行了基準評估。
規劃推動未來競爭力的政策、投資和技能。
確定國家和區域優先發展領域，以促進未來知識主導經濟成長。

知識類型

無形
線上課程、專利、演算法、軟體、資料集、數位內容
有形
電腦、行動裝置、智慧感測器、書籍、伺服器

三大策略要務對知識經濟的影響

顛覆性技術

原因

人工智慧、自動化、雲端基礎設施和區塊鏈領域的突破改變知識的創造、交換和商業化方式。企業採用人工智慧的比例將從2019年的20%上升到2023年的50%以上，將加速生產力提升，並重塑服務、研發、法律、醫療和教育等領域的價值鏈。運算能力、資料可用性和開放原始碼創新的整合，使得先進工具能夠大規模應用。

Frost的觀點

企業需要建構人工智慧、雲端運算和資料工程的內部能力，開發能夠使其服務和產品脫穎而出的獨特應用，而不僅僅是簡單地採用工具。例如，Siemens將人工智慧嵌入其工業軟體中，用於預測性維護；Tata Consultancy Services則推出了一套人工智慧雲端套件，以加速企業專屬知識解決方案的開發。OECD的資料顯示，投資研發和數位化技能提升的企業，在五年內生產力成長可提高30%至50%。

地緣政治動盪

原因

全球管治碎片化、保護主義抬頭以及資料在地化法律阻礙全球思想、人才和數位服務的流動。超過70個國家已經頒布或起草跨境資料法規，而移民限制和數位主權問題也限制人才流動。這些變化重新定義知識的創造、儲存和獲取方式及地點。

Frost & Sullivan的觀點

企業需要將其數位化營運區域化，並分散其創新中心，以確保跨境資料彈性。 SAP 和Oracle擴展其區域雲端中心，以遵守歐盟、印度和中東的資料在地化法律。企業應建立跨司法管轄區的研發策略和具彈性的端到端安全指導基礎設施，以因應地緣政治動盪造成的單點故障。

壓縮客戶價值鏈

原因

科技簡化知識服務的獲取途徑，減少中間環節，並實現與客戶的直接互動。全球企業正擴大透過數位化自助服務和人工智慧輔助平台提供諮詢、研發、法律和IT服務。智慧合約、專家網路和模組化數位化交付縮短B2B知識服務（例如法律諮詢、人力資源、培訓）的交易時間。

Frost的觀點

按需、個人化、自助式知識解決方案的興起加速諮詢、教育、研發、法律服務和軟體開發等行業的轉型。傳統企業正面臨來自敏捷型企業的衝擊，這些企業能夠即時獲得專業知識、自動化工具和分散式問題解決模型。這種轉變凸顯了理解知識服務在全球經濟中如何被分解和重新分配的迫切性。

成長促進因素

生成式人工智慧和知識工作自動化：據預測，到2030年，生成式人工智慧將自動化高達 30%的知識工作者任務，改變跨行業和地理的研究、法律、教育和設計等服務的提供方式。
企業需要不斷提陞技能：全球超過 80%的CEO 將技能轉型列為首要任務，企業大力投資終身學習和建立內部能力，以在快速發展的知識產業中保持競爭力。
全球勞動力虛擬化和遠距知識工作：到2035年，超過 10億工人可能從事混合或完全遠端的知識工作，這將擴大全球人才的獲取途徑，同時也給數位基礎設施、平台和勞動力再培訓系統帶來更大的壓力。
數位公共基礎設施和資料生態系統：各國政府投資建立開放的數位基礎設施（例如印度的DPI、歐盟的Gaia-X），以建立透明且可互通的平台，促進創新、數位創業和公平獲取知識服務。
無形資本在價值創造中的崛起：軟體、專利、資料和品牌價值等無形資產現在佔全球企業價值的55%以上，競爭優勢從有形資產轉向知識主導能力。

成長限制因素

獲得高級技能和高等教育的機會不均等：全球只有 28%的勞動力擁有高等教育或正規數位技能，經合組織國家和開發中國家之間存在巨大差距，限制了新興經濟體知識型勞動力的準備程度。
全球數位落差體現在基礎設施和連接性方面：仍有 26億人缺乏網路接入，限制了他們獲得數位教育、服務和經濟活動的機會，尤其是在撒哈拉以南非洲、南亞和世界各地的農村地區。
人工智慧管治與倫理挑戰：缺乏清晰統一的人工智慧管治，導致知識產業領域對人工智慧的應用存在許多不確定性。截至2024年，超過50%的國家尚未制定全面的國家人工智慧策略。
中低收入國家研發投入不足：高所得經濟體將超過 2.5%的GDP 用於研發，而低收入國家平均研發投入不足 0.5%，這限制了它們產生和吸收知識型創新的能力。
智慧財產權體系碎片化且不一致：全球智慧財產權執法依然薄弱且分散。假冒商品佔全球貿易的2.5%，阻礙了創新、智慧財產權商業化和跨國知識投資。

知識密集度 - 產業間比較圖
知識密集度 - 子部門比較圖
知識密集度 - 汽車製造業
知識密集度 - 機械產業
知識密集度 - 化學製造業
知識密集度 - 半導體製造業
知識密集度 - 食品飲料製造業
知識密集度 - 金融業
知識密集度 - 物流領域
知識密集度 - 資訊與通訊科技（ICT）
知識密集度 - 建設業
知識密集度 - 零售業
知識密集度 - 採礦業
知識密集度 - 農業
知識密集度 - 製藥製造業

成長機會領域

成長機會1：智慧製造與嵌入式智慧
成長機會2：知識主導供應鏈
成長機會3：專業服務的平台化
成長機會4：資料商業化與智慧財產權市場
成長機會5：人工智慧增強教育和醫療保健領域的知識傳遞

附錄

價值提案 - 為什麼高第愛如此重要

未來發展

成長機會帶來的益處和影響
下一步
附件清單
免責聲明

簡介目錄

Product Code: PG4I-90

Leveraging Human Capital, Digital Infrastructure, and AI (HiDiAi) to Shape Future Knowledge Economies

The global knowledge economy is going through a decisive phase of transformation. In the next decade, growth will depend on the combination of human talent, digital infrastructure, and artificial intelligence (AI). These three components form Frost & Sullivan's HiDiAi framework. From productivity changes driven by AI to population shifts and the quest for digital independence, economies are changing how knowledge is created, scaled, and monetized.

During this transition, governments are encouraging the development of STEM talent, companies are adopting smart manufacturing and modern professional services, and financial systems are enhancing inclusion through digital connections. Countries that find ways to overlap the HiDiAi components will speed up innovation, create more value, and build stronger economies by 2035.

Our latest thought leadership examines the major forces, technology drivers, and policy tools that are reshaping the knowledge economy through 2035. We look at how corporate training programs are closing talent gaps, how knowledge-based supply chains and smart technology are changing industrial competition, and how human-AI collaboration is developing in governance and business. We also introduce Knowledge Intensity Scores, which measure industries based on the HiDiAi components, to enable policymakers and businesses to identify future leaders and laggards.

As economies grow more knowledge-driven and interconnected, country macroeconomic success will require a shift from traditional industrial strategies to integrated human, digital, and AI systems. Countries, companies, and investors that take action early will place themselves at the center of the next global growth model.

Key Themes:

1. Emerging Growth Opportunities in Knowledge-Intensive Industries
2. The HiDiAi Framework for Intelligence Innovation
3. Knowledge Intensity Scores Across Sectors
4. Key Policy Levers Towards Encouraging STEM, Sub-National Level Digital Independence, and AI Adoption
5. Major Business Models of the Future Encompass Platform Development, Smart Technology, and Human-AI Collaboration

Scope of Analysis

The Knowledge Economy is an economic system where value creation comes from the combination of Human Intelligence (Hi), Digital Intelligence (Di), and Artificial Intelligence (Ai). These three pillars collaborate to generate, distribute, and use knowledge widely across industries and societies.
The study looks at how the knowledge intensity of sectors and sub-sectors evolve from 2024 to 2035. It identifies what needs to be invested in, what policies should be followed, and what skills should be developed for the future.

Objectives of the Study

Benchmark knowledge intensity across 12 core sectors and 60+ sub-industries.
Map policy, investment, and skills that are driving future competitiveness.
Identify country and regional hotspots for knowledge-driven future economic growth.

Types of Knowledge

Intangible
Online courses, patents, algorithms, software, data sets, digital content
Tangible
Computers, mobile devices, smart sensors, books, servers

The Impact of the Top 3 Strategic Imperatives on Knowledge Economy

Disruptive Technologies

Why

Breakthroughs in AI, automation, cloud infrastructure, and blockchain are transforming how knowledge is created, exchanged, and commercialized. AI adoption in enterprises rose from 20% in 2019 to over 50% in 2023, accelerating productivity gains and redefining value chains in services, R&D, legal, healthcare, and education. The convergence of computing power, data availability, and open-source innovation is making advanced tools accessible at scale.

Frost Perspective

Firms must build internal capabilities in AI, cloud, and data engineering, not just adopt tools, but develop proprietary applications that differentiate services and offerings. For instance, Siemens is embedding AI into industrial software for predictive maintenance, while Tata Consultancy Services has launched its AI-Cloud suite to accelerate enterprise-specific knowledge solutions. According to the OECD, firms that invest in R&D and digital upskilling report 30-50% higher productivity growth over five years.

Geopolitical Chaos

Why

Fragmentation in global governance, rising protectionsm, and data localization laws are disrupting the global flow of ideas, talent, and digital services. Over 70 countries have enacted or drafted cross-border data regulations, and talent mobility is tightening due to immigration restrictions and digital sovereignty concerns. These shifts are redefining how and where knowledge can be created, stored, and accessed.

Frost Perspective

Firms must regionalize their digital operations, diversify innovation hubs to secure cross-border data resilience. SAP and Oracle have expanded regional cloud centers to comply with data localization laws in the EU, India, and the Middle East. Companies should establish multi-jurisdictional R&D strategies and resilient end-to-end safe-guild infrastructure to address single-point failure from geopolitical disruption.

Customer Value Chain Compression

Why

Technology is streamlining access to knowledge services, reducing the role of intermediaries, and enabling direct customer engagement. Global enterprises are increasingly delivering consulting, R&D, legal, and IT services through digital self-service or AI-assisted platforms. Transaction times for B2B knowledge services (e.g., legal advice, HR, training) are shrinking due to smart contracts, expert networks, and modular digital delivery.

Frost Perspective

The rise of on-demand, personalized, and self-service knowledge solutions is accelerating change in consulting, education, R&D, legal services, and software development. Traditional firms face disruption from agile players offering instant access to expertise, automation tools, and decentralized problem-solving models. This shift underscores the urgency of mapping how knowledge services are being unbundled and redistributed in the global economy.

Growth Drivers

Generative AI and Automation of Knowledge Work: Generative AI is expected to automate up to 30% of knowledge worker tasks by 2030, transforming how services like research, law, education, and design are delivered across industries and geographies.
Corporate Demand for Continuous Skill Upgradation: Over 80% of CEOs globally cite skills transformation as a top priority, with firms investing heavily in lifelong learning and internal capability-building to stay relevant in fast-evolving knowledge sectors.
Global Talent Virtualization and Remote Knowledge Work: Over 1 billion workers could operate in hybrid or fully remote knowledge jobs by 2035, expanding access to global talent but increasing pressure on digital infrastructure, platforms, and workforce reskilling systems.
Digital Public Infrastructure and Data Ecosystems: Governments are investing in open digital infrastructure (e.g., India's DPI, EU's Gaia-X) to create transparent, interoperable platforms that accelerate innovation, digital entrepreneurship, and equitable access to knowledge services.
Rise of Intangible Capital in Value Creation: Intangible assets such as software, patents, data, brand equity, now account for over 55% of global corporate value, shifting competitive advantage from physical assets to knowledge-driven capabilities.

Growth Restraints

Unequal Access to Advanced Skills and Higher Education: Only 28% of the global workforce has tertiary education or formal digital skills, with large disparities between OECD and developing nations, limiting knowledge workforce readiness in emerging economies.
Global Digital Divide in Infrastructure and Connectivity: 2.6 billion people remain offline, limiting access to digital education, services, and economic participation, especially in Sub-Saharan Africa, South Asia, and rural regions globally.
AI Governance and Ethical Uncertainty: Lack of clear, harmonized AI governance is creating uncertainty in deploying AI across knowledge sectors; over 50% of countries lack comprehensive national AI strategies as of 2024.
Underinvestment in R&D in Low- and Middle-Income Countries: While high-income economies spend over 2.5% of GDP on R&D, the average in low-income countries remains below 0.5%, constraining their ability to generate or absorb knowledge-based innovations.
Fragmented and Inconsistent Intellectual Property Regimes: Global IP enforcement remains weak and fragmented. Counterfeit trade accounts for 2.5% of global trade, discouraging innovation, IP commercialization, and cross-border knowledge investment.

Research Scope

Scope of Analysis
Segmentation

Strategic Imperatives

Why is it Increasingly Difficult to Grow?
The Strategic Imperative 8™
The Impact of the Top 3 Strategic Imperatives on Knowledge Economy

Growth Opportunity Analysis

Growth Drivers
Growth Restraints

Knowledge Economy Framework

Knowledge Investments Powered Historical Economic Take-Offs
Bridging the Knowledge Divide-Comparative Analysis of Key Advanced and Emerging Country Challenges
The HiDiAi Framework of Knowledge Economy