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Developing a national AI strategy: insights from global approaches

  • Writer: Digital Team
    Digital Team
  • Jan 10, 2024
  • 5 min read
AI strategy

Developing a national AI strategy: insights from global approaches


As artificial intelligence (AI) becomes a transformative force in governments and societies, nations around the world are racing to develop national AI strategies. These strategies aim to harness AI for economic growth, improved public services, and global competitiveness while mitigating associated risks such as ethical misuse, economic disruption, and social inequality. This report provides a comparative review of national AI strategies, drawing from global examples and international frameworks to inform effective policy development.


1. International frameworks guiding AI strategy


Several global institutions have developed guidelines and models to support countries in crafting their AI strategies:


  • World Economic Forum (WEF): Recommends a "minimum viable" national strategy structured around five dimensions: data protection and ethics, research collaboration, workforce readiness, investment in strategic sectors, and international cooperation. It promotes SWOT analysis as a starting point and stresses the importance of clearly defined objectives.


  • OECD: Advocates for trustworthy AI through five stewardship principles—human-centred design, transparency, robustness, accountability, and inclusivity. Its AI Policy Observatory tracks policies from over 60 countries, supporting international alignment.


  • European Union: The EU strategy emphasises legal regulation, ethical AI development, and a coordinated investment plan. Tools include the AI Act, Coordinated Plan on AI, and emphasis on building trust through a strong governance framework.


2. National AI strategies: country comparisons


United Kingdom: The UK’s strategy is structured around three pillars: long-term investment, broad benefit distribution, and effective governance. The UK supports regional AI hubs, international talent attraction, and ethical use standards through institutions like the Alan Turing Institute.


United States: The US strategy, shaped by the National Artificial Intelligence Initiative Act, centres on leadership in innovation, trustworthy AI, education, and strategic infrastructure. It includes substantial sector-specific strategies across healthcare, defence, and education, coordinated by federal entities like NIST and OSTP.


China: China's AI strategy, led by the State Council, is framed by goals to become the global AI leader by 2030. Its approach combines centralised planning with open-source collaboration, focusing on surveillance, automation, and national infrastructure.


European Union members:


  • France: Prioritises ethical AI, public-private R&D, and societal benefit. A hallmark is its investment in supercomputing infrastructure for AI research.

  • Germany: Emphasises AI in manufacturing and research transfer, supported by frameworks to ensure safe, human-centric AI.

  • Netherlands: Focuses on responsible AI via public-private partnerships, particularly in water management and infrastructure.

  • Sweden: Leads in green technology AI applications, blending innovation with sustainability and strong international standards.

  • Denmark: Targets citizen-centred services using AI, supported by a robust ethics framework and data policies.

  • Spain: Develops AI through digital infrastructure and support for tourism and public administration transformation.

  • Italy: Focuses on AI for cultural heritage and human-centric innovation through regional research hubs.


Asia-Pacific and North America:


  • Singapore: Prioritises rapid deployment in high-value sectors and collaborative AI projects under a human-centred, Smart Nation framework.

  • Australia: Supports industry-led innovation and national challenges such as agriculture through ethical, inclusive AI.

  • Canada: Stresses research excellence and health applications, facilitated by national AI institutes like CIFAR, Amii, Mila, and Vector.


3. Shared themes in national strategies


Across national strategies, several recurring themes emerge:

  • Research and development: All countries see R&D as the engine for AI progress.

  • Talent and skills: Investment in education, upskilling, and attracting global talent is a priority.

  • Ethical and responsible AI: Countries are converging on principles of transparency, fairness, and human rights.

  • Economic competitiveness: AI is seen as a catalyst for innovation, productivity, and sectoral transformation.

  • Public service and societal value: Governments are deploying AI in health, justice, education, and environment.

  • Industry collaboration: Public-private partnerships and startup ecosystems are widely encouraged.

  • International cooperation: Nations recognise the global nature of AI and seek to engage in multilateral governance and research alliances.

AI framework

4. Managing national AI risks


Despite varying priorities, nations share concerns about AI risks:


  • Ethical issues: Bias, discrimination, data misuse, and lack of transparency are major worries.

  • Job displacement: Automation could lead to economic disruption, requiring upskilling policies.

  • Security: Nations fear misuse in cyberattacks or autonomous weapon systems.

  • Accountability: Clear legal and regulatory frameworks are needed to manage responsibility and liability.

  • Geopolitical competition: AI is now a dimension of national power and technological sovereignty.


5. Key steps for developing a national AI strategy


To support effective strategy design, a general roadmap includes:


  1. Assessment: Evaluate current capabilities and sectoral needs.

  2. Vision and goals: Align AI priorities with national development goals.

  3. Stakeholder engagement: Involve government, industry, academia, and civil society.

  4. Policy and regulation: Define standards for data, ethics, and AI use.

  5. Ecosystem support: Fund R&D, data infrastructure, and innovation hubs.

  6. Talent development: Boost education, training, and talent pipelines.

  7. Public sector adoption: Use AI to improve service delivery.

  8. Ethics and trust: Build frameworks for responsible and explainable AI.

  9. International collaboration: Share knowledge, standards, and project outcomes.

  10. Monitoring: Set up KPIs and regular reviews to track progress.


Summary


Developing a national AI strategy is no longer optional—it’s essential. This comparative review highlights the diversity of approaches and the common ground shared among global leaders. While each country must tailor its strategy to national needs and capacities, lessons from the WEF, OECD, and various national experiences offer a strong foundation.


A successful strategy blends innovation with regulation, local relevance with global engagement, and short-term action with long-term vision. Through coordinated and ethical deployment, AI can drive inclusive economic development and public good on a global scale.


References:



AI Institute for Collaborative Assistance and Responsive Interaction for Networked Groups


Australian AI action plan (20 21) -




report_en


artificial-intelligence


Galindo, L., K. Perset and F. Sheeka (2021), "An overview of national AI strategies and

policies", OECD Going Digital Toolkit Notes, No. 14, OECD Publishing, Paris,


The German Federal Government AI strategy - https://www.ki-strategie-


initiatives/http:%2F%2Faipo.oecd.org%2F2021-data-policyInitiatives-27222


The NSF AI Institute for Artificial Intelligence and Fundamental Interactions (IAIFI)



strategies-and-policies-c05140d9-en.htm


OECD going digital toolkit www.oecd.org/going-digital


The Netherlands Digitalisation Strategy 2021 - file:///C:/Users/P%20W/Downloads/210621-

min-ezk-digitaliseringstrategie-en-v03.pdf


The Norwegian National AI strategy - https://www.regjeringen.no/en/dokumenter/nasjonal-

strategi-for-kunstig-intelligens/id2685594/?q=AI&ch=4#id0026


The NIST AI risk management framework - https://www.nist.gov/itl/ai-risk-management-

framework


George James Consulting


Ohio State University - AIEdge - https://aiedge.osu.edu/

high-level-panel-emerging


06/E09M41_National_Artificial_Intelligence_Strategy.pdf


Swedish Government review of AI potential


The Government of Singapore – National AI strategy.


publishes-its-ai-strategy/


strategy/national-ai-strategy-html-version#executive-summary


strategy/national-ai-strategy-html-version


University of Colorado Boulder - https://www.colorado.edu/research/ai-institute/


US government AI strategy https://www.ai.gov/strategy-documents/


US DoD - U.S. DEPARTMENT OF DEFENSE RESPONSIBLE ARTIFICIAL INTELLIGENCE


STRATEGY AND IMPLEMENTATION PATHWAY, June 22, 2022


United States - ARTIFICIAL INTELLIGENCE ACTION PLAN, May 7, 2022


US State Department - ENTERPRISE DATA STRATEGY: EMPOWERING DATA


INFORMED DIPLOMACY, September 27, 2021


US Department of Homeland Security - S&T ARTIFICIAL INTELLIGENCE AND MACHINE


LEARNING STRATEGIC PLAN, August 1, 2021


United States, Department of Health and Human Services - U.S. DEPARTMENT OF


HEALTH AND HUMAN SERVICES: ARTIFICIAL INTELLIGENCE (AI) STRATEGY, January

14, 2021


United States, Federal Drug Administration - ARTIFICIAL INTELLIGENCE/MACHINE


LEARNING-BASED SOFTWARE AS A MEDICAL DEVICE ACTION PLAN, January 2021


United States, Department of Homeland Security - U.S. DEPARTMENT OF HOMELAND


SECURITY ARTIFICIAL INTELLIGENCE STRATEGY, December 3, 2020

George James Consulting

(United States, Department of Transport - ENSURING AMERICAN LEADERSHIP IN


AUTOMATED VEHICLE TECHNOLOGIES 4.0, January 2020

United States, Department of Justice - DATA STRATEGY FOR THE U.S. DEPARTMENT

OF JUSTICE, February 26, 2019


United States - Department of Defense -DEPARTMENT OF DEFENSE ARTIFICIAL

INTELLIGENCE STRATEGY, February 2019


United States, Office of Director of National Intelligence) THE AIM INITIATIVE: A STRATEGY

FOR AUGMENTING INTELLIGENCE USING MACHINES, January 2019


US Department of Transport - PREPARING FOR THE FUTURE OF TRANSPORTATION:

AUTOMATED VEHICLES 3.0, October 2018


US Department of Transport – Automated driving systems 2.0: A VISION FOR SAFETY,

August 12, 2017



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