Every nation today needs to devise a robust artificial intelligence (AI) strategy. It is not about competing with AI giants like the US and China head-on, but about finding a specific and competitive foothold in this fast-evolving digital landscape where data is the new oil. AI, like Prometheus's gift of fire, is acting as the spine for a broad spectrum of ground-breaking technologies - from data analytics to robotics and the Internet of Things (IoT). Its influence is sweeping across vital sectors such as healthcare, education, energy, manufacturing, and transportation. We are just at the rupture of the AI revolution, with its full impact yet to materialize. It's like watching a thrilling mystery unfold - exciting, unpredictable, and full of opportunities. The recent global frenzy over generative AI models – the new rockstars in the tech world - underscores AI’s disruptive prowess and its potential to rewrite the art of the possible. Nations now stand at a strategic crossroads; a window of opportunity is open for them to make judicious choices about their positions in the AI race.
It's a high-stakes game, and the prizes for playing it well are monumental: enhanced GDP, increased productivity, job creation, improved quality of life, and citizen welfare. This endeavor is akin to a carefully orchestrated symphony - with each instrument, each note, representing key enablers and value creators of national AI strategies. A well-coordinated, strategic sequence could lead to exceptional results; a misaligned action, however, could undermine the overall strategic trajectory. Therefore, the call for action is urgent and should echo in every corner of national policy-making chambers.
Currently, the private sector has led the way in AI. The AI Index compiled by Stanford University reports that, in 2022, industry players released 32 of the 38 machine learning models that can be considered significant, while only 3 were released by academia
If the private sector has been the primary beneficiary of developments so far, a national AI strategy will pay dividends to the general public beyond protecting them from the risks highlighted above. On a practical level, governments can leverage AI to target resources and improve service delivery. If governments fall too far behind the private sector, citizens will grow more frustrated with the delivery of public services, and private actors will be exclusively setting the standards. While trends of the latter are starting to emerge globally, this imbalance risks prioritizing private interests without careful attention to the public good. More broadly, governments should drive the development of AI standards, norms, and priorities – nationally and globally – not relegate those decisions to the private sector. Importantly, they should do so proactively to keep pace with private sector-driven AI innovation.
Countries approach AI from different starting points. They have different priorities for economic growth, social progress, educational achievement, and so on. They bring unique technological, engineering, and other strengths as well as limitations and weaknesses. They also take different approaches to balancing the interests of the government, private sector, and individual citizens. Understanding its starting point and approach to these trade-offs forms the basis for shaping a country’s strategy. In supporting national governments in their AI strategies, BCG has developed the “ASPIRE” framework which further defines and codifies six foundational elements: (1) Ambition, (2) Skills, (3) Policy & Regulation, (4) Investment, (5) Research & Innovation, and (6) Ecosystem.
Ambition is the seed of strategy. It imagines what is possible, determines overall objectives, and directs the allocation of resources. In our review of approximately 50 existing national AI strategies, we identified three central archetypes:
Most countries fit into one of these archetypes, although strategic details and progress along their chosen AI paths vary substantially.
One such variation lies in the economic sectors each country will select as priority beneficiaries of AI’s transformative power. This prioritization does not rule out AI adoption across all sectors; rather, it entails a strategic allocation of resources towards high-potential sectors – often 5 to 7. Three criteria can guide this decision and ensure the concentration of efforts is optimized:
By employing this approach, countries ensure their AI strategy contributes to sectors of national importance and where AI could be meaningfully utilized to generate impact.
A strategy is only as effective as the people possessing the proper skills to execute it. A national AI strategy should outline an approach to building the skill base through education, reskilling, and training. But developing and keeping talent with the necessary AI skills is a global challenge. Countries must deal with:
Regulating AI has come into focus as deployed AI systems have put users, businesses, and government at risk. Both businesses and governments have a role to play.
Overall, regulating AI – whether by simply setting core ethics principles or through proactively introducing protective mechanisms – is necessary to ensure sustainable development of the AI innovation ecosystem, maximization of value from AI solutions, and protection of citizens from harm, undesired use of AI, and discrimination. Both private companies and government have roles to play in developing principles and ethics around AI. UNESCO developed recommendations on the AI ethics focused on human rights and inclusiveness, and was adopted by all 193 Member States. Regulating a fast-changing field like AI is an ongoing process. Leading countries have typically started their journey with soft legislation focused on principles to guide AI players and enable rapid growth of the data and AI economy. Then as understanding and applications become more sophisticated, mature jurisdictions like the US, EU, and China have moved toward more restrictive models coupled with pro-innovation initiatives like dedicated sandboxes (low-risk high support environments setup by government entities to fuel cross-sector innovation.).
Recent disruptions, like the suddenly accelerated adoption of GenAI systems, have triggered different reactions worldwide. While certain countries, like Italy, have chosen a temporary ban as a precautionary measure, others, like Portugal, have swiftly seized the opportunity to integrate this technology into their government services. In times of fast-paced innovation, governments often find themselves in a reactive stance towards private sector advancements. A strong national AI strategy can equip policymakers and legislators with directions, principles, and guidance on key trade-offs that can promote efficient and harmonized decision-making in the face of rapid technological advancements.
A nation’s willingness to invest in AI needs to match its ambition.
It is important to note that investment support extends well beyond the monetary. It starts with attracting businesses and funders through fiscal, financial, and regulatory incentives, local market information access, and ecosystem promotion. Countries can also increase the ease of starting businesses, and establish investment protections to create a pro-investment climate. They can offer business advisory and legal support. Finally, they should facilitate connections among stakeholders, building a pro-partnership environment, and developing clear paths for investors and efficient approaches to match-making.
Governments can also deploy their R&D budget and agenda in support of AI by targeting areas that play to the nation’s strengths or are critical to addressing its most pressing challenges. A nation’s ambition archetype – national enabler, specialist, or industry leader – will largely shape the scope and priorities of its AI R&D agenda. It will also guide the respective roles of government, academia, and private players, and how their contributions are orchestrated. There is no one-size-fits-all for national priority-setting. Leading countries follow diverse approaches. Some, like Switzerland, are already leaders in general R&D, so include AI organically in auxiliary national strategies. Others, like Singapore, have a dedicated AI strategy with a strong R&D focus. Finally, countries like the US make AI R&D a specific priority domain with its own extensive strategy, focusing on moonshot initiatives and requiring heavy investments.
Generally, countries should focus on supporting basic research, public-private partnership, and collaboration with global AI organizations.
Typically the public sector can kick-start R&D by creating demand for AI innovation and providing financing. Academia is responsible for research, knowledge transfer, talent development, and international stakeholder attraction. The private sector develops its own research, fosters collaborations, funds R&D, and captures value. The orchestration of these stakeholders takes different forms across leading countries. Some favor a self-orchestrating ecosystem, others delegate organization to area-specific champions. All leading countries, however, seek ways to proactively develop their ecosystems throughout the AI R&D cycle.
International Ecosystems: Global Cooperation Efforts
Despite countries competing to become global AI leaders, cooperation between one another has never been more critical to address the global challenges raised by AI and better capitalize on its opportunities. As such, AI cooperation has become a key enabler for countries around the world.
Local Ecosystems: Fulfilling Infrastructure Needs
Beyond international cooperation, the presence of a local ecosystem adjacent to AI is crucial. Many of the most effective AI applications are not stand-alone but rather depend on an interconnected ecosystem infrastructure. Self-driving cars, for example, have built-in sensors and processing units, cameras, and wireless connectivity built by separate companies that must work seamlessly together. These ecosystems vary in complexity, depending on a nation’s ambitions, but will all involve startup development, industrial adoption, infrastructure, data access, and government support. As with research and innovation, collaboration is the cement that holds ecosystems together.
In addition to cross-cutting ecosystem infrastructure providing security and interoperability, the following three overarching layers of infrastructure are particularly important in driving leading countries’ AI success:
A strategy is only as good as its execution. How then can countries put a national AI strategy into action? Our recommendation is to start with four concrete steps before engaging with the specific dimensions of the ASPIRE framework.
First and foremost, governments need to establish a clear and dedicated ownership structure that possesses the authority and capacity to lead the national AI strategy. This entity could be a central coordinating body, a specialized department, or an empowered agency for instance. Its mandate includes mobilizing the entire government machinery and ensuring the necessary technical expertise to support the strategy's development.
Secondly, the designated entity should foster collaboration and engagement with a wide range of local stakeholder groups: technology, communications, labor, education, financial, and economic development, as well as key national sectors, who will be involved in the drafting of the strategy to ensure alignment at the national level.
This wider group of stakeholders is key to the third step. For the strategy to reflect a country’s broader societal aspirations, it must be inclusive. To achieve this and ensure special interests do not have an undue influence, consultations must be made a priority, involving academia, businesses, civil society organizations, and experts from law, sociology, and other adjacent fields. Consultations should also go beyond national borders, capturing inputs from international experts, leading countries, and prospective partners, and aligning the strategy with global trends and standards.
Lastly, as the strategy reaches maturity, awareness will become a priority both at the local level, ensuring all parties understand not only the aspirations of their country but importantly how they will benefit from these efforts and what role they will play. Such awareness should also be raised at the international level to promote the country’s agenda, accelerate participation in global AI cooperation efforts, and establish the country as “open for business” when it comes to data & AI. Furthermore, given that AI is a rapidly evolving technology, it’s paramount for governments to possess the agility to periodically revisit and refine their national AI strategies. As advancements occur and more insights are garnered, updating the strategy becomes pivotal to stay relevant to the latest global trends, build upon earlier accomplishments, and refine the nation’s unique value propositions and strengths in this space.
These steps constitute an integral part of the strategy activation journey and will be critical to making AI aspirations a reality. As emphasized across this piece, the public sector can play a catalytic role by providing the necessary ingredients for success. While national governments can create conducive innovation environments, it’s the proactive collaboration with the private sector and the broader stakeholder map that will drive AI to flourish responsibly in the 2020s and beyond.
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