New industrial policies – Accelerated digitalization and the rise of AI call for new industrial policies. As value in the global economy shifts toward knowledge-intensive activities, decision makers need to support the adoption and development of new technologies, as well as the creation, dissemination and absorption of productive knowledge.

Coordination – National strategies should coordinate across domains, including STI, industry, education, infrastructure and trade. Moreover, AI policies should go beyond incentives such as tax deductions and include regulations, such as on consumer protection, digital platforms and data protection, along with governance and
enforcement to orient the direction of technological change.
Policies should address the three leverage points:

Infrastructure – It is vital to ensure equitable access to enablers such as electricity and the Internet that facilitate AI adoption and reduce inequalities. This can be achieved by fostering a conducive business environment with incentives for private-sector investment. Distributed networks and computing power can also enable AI
development, but it is important to ensure interoperability and harmonization between infrastructures and systems.

Data – Open data and data-sharing enhance data integration, storage, access and collaboration. AI adoption and development rely on good practices in data collection, with interoperability and accessibility across the innovation ecosystem. Privacy, accountability and intellectual property aspects should also be addressed,
to foster innovation while safeguarding human rights.

Skills – Population-wide AI literacy promotes widespread AI adoption and can be achieved by integrating science, technology, engineering and mathematics (STEM) and AI subjects, from early education to continuous learning. Partnerships between academia and the private sector can help build AI talent to meet particular industry needs and drive AI development.