Knowledge Economy Transformations, 2025-2035

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.