知识经济转型，2025-2035年

充分利用人力资本、数位基础设施和人工智慧（HiDiAi），塑造未来知识经济

全球知识经济正处于转型关键阶段。未来十年的成长将取决于人力资本、数位基础设施和人工智慧（AI）的结合。这三大要素构成了Frost & Sullivan的HiDiAi框架。从人工智慧驱动的生产力转型到人口结构变化和对数位独立的追求，各国经济正在改变知识的创造、规模和货币化方式。

在此转型过程中，各国政府正大力发展STEM（科学、技术、工程和数学）人才，企业正积极采用智慧製造和现代专业服务，金融体係也透过数位互联互通变得更加包容。到2035年，那些认识到高数位化和人工智慧（HiDiAi）各组成部分互联互通的国家将加速创新，创造更多价值，并建构更强大的经济体。

我们最新的建议检验于2035年将重塑知识经济的关键力量、技术驱动因素和政策工具。这些建议探讨了企业培训专案如何弥补人才缺口，知识型供应链和智慧技术如何改变产业竞争格局，以及人机协作在管治和商业领域的发展趋势。此外，建议还引入了“知识密集度评分”，该评分基于高知高智商（HiDiAi）要素对各行业进行评估，旨在帮助政策制定者和企业识别未来的领导者和落后者。

随着经济体日益知识主导和相互关联，国家宏观经济的成功将需要从传统的产业策略转向整合人力、数位和人工智慧的系统。那些及早采​​取行动的国家、企业和投资者将成为下一代全球成长模式的核心。

主要主题：

• 1.密集型产业的新增长机会
• 2. HiDiAi智慧创新框架
• 3. 各行业知识密集度得分
• 4. 促进STEM教育、本地数位独立和人工智慧应用的关键政策槓桿
• 5. 未来的关键经营模式将涵盖平台开发、智慧技术和人机协作。

分析范围

• 知识经济是一种经济体系，其价值创造是透过人类智慧（Hi）、数位智慧（Di）和人工智慧（Ai）的结合来实现的。这三大支柱协同运作，在产业和社会各界广泛创造、传播和利用知识。
• 该研究检验了2024年至2035年间各产业和子部门的知识密集度将如何演变。它指出了应该在哪些领域进行投资，应该实施哪些政策，以及未来应该培养哪些技能。

本次调查的目的

• 它对 12 个主要行业和 60 多个子行业的知识密集度进行了基准评估。
• 规划推动未来竞争力的政策、投资和技能。
• 确定国家和区域优先发展领域，以促进未来知识主导经济成长。

知识类型

• 无形
• 线上课程、专利、演算法、软体、资料集、数位内容
• 有形
• 电脑、行动装置、智慧感测器、书籍、伺服器

三大策略要务对知识经济的影响

颠覆性技术

原因

人工智慧、自动化、云端基础设施和区块链领域的突破正在改变知识的创造、交换和商业化方式。企业采用人工智慧的比例将从2019年的20%上升到2023年的50%以上，将加速生产力提升，并重塑服务、研发、法律、医疗和教育等领域的价值链。运算能力、资料可用性和开放原始码创新的整合，使得先进工具能够大规模应用。

弗罗斯特的观点

企业需要建构人工智慧、云端运算和资料工程的内部能力，开发能够使其服务和产品脱颖而出的独特应用，而不仅仅是简单地采用工具。例如，西门子正在将人工智慧嵌入其工业软体中，用于预测性维护；塔塔咨询服务公司（TCS）则推出了一套人工智慧云端套件，以加速企业专属知识解决方案的开发。经合组织（OECD）的数据显示，投资研发和数位化技能提升的企业，在五年内生产力成长可提高30%至50%。

地缘政治动盪

原因

全球管治碎片化、保护主义抬头以及资料在地化法律正在阻碍全球思想、人才和数位服务的流动。超过70个国家已经颁布或正在起草跨境资料法规，而移民限制和数位主权问题也限制人才流动。这些变化正在重新定义知识的创造、储存和获取方式及地点。

Frost & Sullivan的观点

企业需要将其数位化营运区域化，并分散其创新中心，以确保跨境资料弹性。 SAP 和Oracle正在扩展其区域云端中心，以遵守欧盟、印度和中东的资料在地化法律。企业应建立跨司法管辖区的研发策略和具弹性的端到端安全指导基础设施，以因应地缘政治动盪造成的单点故障。

压缩客户价值链

原因

科技正在简化知识服务的获取途径，减少中间环节，并实现与客户的直接互动。全球企业正越来越多地透过数位化自助服务和人工智慧辅助平台提供咨询、研发、法律和IT服务。智慧合约、专家网路和模组化数位化交付正在缩短B2B知识服务（例如法律咨询、人力资源、培训）的交易时间。

弗罗斯特的观点

按需、个人化、自助式知识解决方案的兴起正在加速咨询、教育、研发、法律服务和软体开发等行业的转型。传统企业正面临来自敏捷型企业的衝击，这些企业能够即时获得专业知识、自动化工具和分散式问题解决模型。这种转变凸显了理解知识服务在全球经济中如何被分解和重新分配的迫切性。

成长驱动因素

• 生成式人工智慧和知识工作自动化：据预测，到 2030 年，生成式人工智慧将自动化高达 30% 的知识工作者任务，从而改变跨行业和地理的研究、法律、教育和设计等服务的提供方式。
• 企业需要不断提升技能：全球超过 80% 的 CEO 将技能转型列为首要任务，企业正在大力投资终身学习和建立内部能力，以在快速发展的知识产业中保持竞争力。
• 全球劳动力虚拟化和远距知识工作：到 2035 年，超过 10 亿工人可能从事混合或完全远端的知识工作，这将扩大全球人才的获取途径，同时也给数位基础设施、平台和劳动力再培训系统带来更大的压力。
• 数位公共基础设施和资料生态系统：各国政府正在投资建立开放的数位基础设施（例如印度的 DPI、欧盟的 Gaia-X），以建立透明且可互通的平台，从而促进创新、数位创业和公平获取知识服务。
• 无形资本在价值创造中的崛起：软体、专利、数据和品牌价值等无形资产现在占全球企业价值的 55% 以上，竞争优势从有形资产转向知识主导能力。

成长限制因素

• 获得高级技能和高等教育的机会不均等：全球只有 28% 的劳动力拥有高等教育或正规数位技能，经合组织国家和开发中国家之间存在巨大差距，限制了新兴经济体知识型劳动力的准备程度。
• 全球数位落差体现在基础设施和连接性方面：仍有 26 亿人缺乏网路接入，限制了他们获得数位教育、服务和经济活动的机会，尤其是在撒哈拉以南非洲、南亚和世界各地的农村地区。
• 人工智慧管治与伦理挑战：缺乏清晰统一的人工智慧管治，导致知识产业领域对人工智慧的应用存在许多不确定性。截至2024年，超过50%的国家尚未制定全面的国家人工智慧策略。
• 中低收入国家研发投入不足：高所得经济体将超过 2.5% 的 GDP 用于研发，而低收入国家平均研发投入不足 0.5%，这限制了它们产生和吸收知识型创新的能力。
• 智慧财产权体系碎片化且不一致：全球智慧财产权执法依然薄弱且分散。假冒商品占全球贸易的2.5%，阻碍了创新、智慧财产权商业化和跨国知识投资。

目录

调查范围

• 分析范围
• 分割

策略要务

• 为什么经济成长变得越来越困难？
• The Strategic Imperative 8（TM）
• 三大策略要务对知识经济的影响

成长机会分析

• 成长驱动因素
• 成长限制因素

知识经济框架

• 知识投资推动历史性的经济成长
• 弥合知识鸿沟：主要已开发国家和新兴国家问题的比较分析
• HiDiAi 知识经济框架

人类智能

• 高等教育技能分布：当前趋势与未来展望
• 企业技能提升生态系驱动劳动转型
• 扭转人才流失：人才留存策略

数位智能

• 支持知识经济的数位基础设施
• 新兴市场数位化连结的社会经济效益
• 6G发展计画 - 国家概览

人工智慧

• 对人工智慧赋能型劳动力的需求
• 人工智慧人才招聘与人工智慧技能采纳差距
• 人工智慧投资现状
• 人工智慧作为知识经济的驱动力

政策指南和最佳实践

• 知识经济政策指南与实际模型
• 处于高科技、数位与人工智慧（HiDiAi）转型成长模式的十字路口

主要行业的知识密集度

• 知识密集度－产业间比较图
• 知识密集度－子部门比较图
• 知识密集－汽车製造业
• 知识密集度－机械产业
• 知识密集度—化学製造业
• 知识密集度－半导体製造业
• 知识密集度－食品饮料製造业
• 知识密集度 - 金融业
• 密集型密集－物流领域
• 知识密集度－资讯与通讯科技（ICT）
• 知识密集度—建设业
• 知识密集度 – 零售业
• 密集型产业－采矿业
• 密集型农业
• 密集型密集－製药製造业

成长机会领域

• 成长机会 1：智慧製造与嵌入式智能
• 成长机会2：知识主导供应链
• 成长机会 3：专业服务的平台化
• 成长机会 4：数据商业化与智慧财产权市场
• 成长机会 5：人工智慧增强教育和医疗保健领域的知识传递

附录

• 价值提案－为什么高第爱如此重要

未来发展

• 成长机会带来的益处和影响
• 下一步
• 附件清单
• 免责声明

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.

Table of Contents

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

Human Intelligence

• Tertiary Skill Distribution-Current Trends and Future Potential
• Corporate Reskilling Ecosystem Driving Workforce Transformation
• Reversing Brain Drain-Strategies for Talent Retention

Digital Intelligence

• Digital Foundations for Knowledge Economies
• Socio-Economic Benefits of Digital Connectivity in Emerging Markets
• 6G Development Efforts-Country Snapshots

Artificial Intelligence

• AI-Ready Labor Demand
• AI Hiring and AI Skill Penetration Divide
• AI Investment Landscape
• AI as a Driver of the Knowledge Economy

Policy Playbook and Best Practices

• Knowledge Economy Policy Playbook and Real-World Models
• Intersections of HiDiAi-Transformational Growth Models

Knowledge Intensity in Key Industries

• Knowledge Intensity-Inter-Sector Comparison Mapping
• Knowledge Intensity-Sub-sectoral Comparison Mapping
• Knowledge Intensity-Automotive Manufacturing Sector
• Knowledge Intensity-Machinery Sector
• Knowledge Intensity-Chemical Manufacturing Sector
• Knowledge Intensity - Semiconductor Manufacturing Sector
• Knowledge Intensity-Food & Beverage Manufacturing Sector
• Knowledge Intensity-Finance Sector
• Knowledge Intensity-Logistics Sector
• Knowledge Intensity-Information and Communication Technologies ICT Sector
• Knowledge Intensity-Construction Sector
• Knowledge Intensity-Retail Sector
• Knowledge Intensity-Mining Sector
• Knowledge Intensity-Agriculture Sector
• Knowledge Intensity-Pharmaceutical Manufacturing Sector

Growth Opportunity Universe

• Growth Opportunity 1: Smart Manufacturing & Embedded Intelligence
• Growth Opportunity 2: Knowledge-Driven Supply Chains
• Growth Opportunity 3: Platformization of Professional Services
• Growth Opportunity 4: Data Commercialization & Knowledge IP Markets
• Growth Opportunity 5: AI-Augmented Knowledge Delivery in Education & Health

Appendix

• Value Proposition-Why HiDiAi Matters

Next Steps

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