Publications & Documents

The provision of key health technologies and products such as vaccines and antibiotics is insufficient in purely competitive and volume-based markets, requiring new revenue streams for sustainability. Recent developments in health innovation suggest that innovative collaborative mechanisms can be effective in addressing this issue. In the domains of vaccines and antibiotics, these approaches should incorporate shared research investment, long-term access planning, the provision of manufacturing infrastructure, supply chains, and financial returns. Collaborative approaches such as subscription models could be piloted at the regional level, while other models could be developed to delink innovation, manufacturing, and access from sales volume and revenue. Finally, blended finance instruments from the development field could encourage greater collaboration among established and emerging stakeholders in health innovation. These stakeholders should work together to create, test, access, and implement more collaborative approaches to health innovation to share upfront investments, mitigate risks of failure, and accelerate market access.

The transition to climate neutrality requires cost reductions in existing clean technologies to enable rapid deployment on a large scale, as well as the development of emerging technologies such as green hydrogen. This policy paper argues that science, technology, innovation, and industrial (STI&I) policies focusing on developing and deploying low-carbon technologies are crucial to achieving carbon neutrality. It notes however that the current level of innovation is insufficient to meet the net-zero challenge due to a policy emphasis on deployment rather than research and development (R&D) support. The paper explores the rationale for more ambitious STI&I policies targeted at R&D for climate neutrality and provides policy recommendations for an effective innovation policy for net-zero, including its interaction with the broader climate policy package.

Artificial intelligence (AI) is transforming economies and promising new opportunities for productivity, growth, and resilience. Countries are responding with national AI strategies to capitalise on these transformations. However, no country today has data on, or a targeted plan for, national AI compute capacity. This policy blind-spot may jeopardise domestic economic goals. This report provides the first blueprint for policy makers to help assess and plan for the national AI compute capacity needed to enable productivity gains and capture AI’s full economic potential. It provides guidance for policy makers on how to develop a national AI compute plan along three dimensions: capacity (availability and use), effectiveness (people, policy, innovation, access), and resilience (security, sovereignty, sustainability). The report also defines AI compute, takes stock of indicators, datasets, and proxies for measuring national AI compute capacity, and identifies obstacles to measuring and benchmarking national AI compute capacity across countries.

This paper uses information collected and provided by GlassAI to analyse the characteristics and activities of companies and universities in Canada, Germany, the United Kingdom and the United States that mention keywords related to Artificial Intelligence (AI) on their websites. The analysis finds that those companies tend to be young and small, mainly operate in the information and communication sector, have AI at the core of their business, and aim to provide customer solutions. It is noteworthy that the types of AI-related activities reported by them vary across sectors. Additionally, although universities are concentrated in and around large cities, this is not necessarily reflected in the intensity of AI-related activities. Taken together, this novel and timely evidence informs the debate on the most recent stages of digital transformation of the economy.

Illicit trade in counterfeit goods causes economic damage by reducing sales and profits as well as innovation incentives in legitimate industries. This study looks at damages caused by illicit trade in counterfeits to small and medium-sized enterprises. The robust evidence on the magnitude, scope and trends of this risk informs policy makers about the need to include anti-counterfeiting elements in policy packages designed to support SMEs.

This report presents a case study of applying the OECD anticipatory innovation governance framework to develop and manage anticipatory innovation ecosystems as vehicles for knowledge generation, innovation governance and co-ordinated action to achieve policy goals. Part I establishes the case for anticipatory innovation ecosystems and sets out how they can be governed through a multi-level approach. In Part II, opportunities and challenges for applying this approach in the Latvian context are identified, and recommendations are made for developing anticipatory innovation ecosystems in Latvia.

This work employs a novel approach to identify and characterise firms adopting Artificial Intelligence (AI), using different sources of large microdata. Focusing on the United Kingdom, the analysis combines data on Intellectual Property Rights, website information, online job postings, and firm-level financials for the first time. It shows that a significant share of AI adopters is active in Information and Communication Technologies and professional services, and is located in the South of the United Kingdom, particularly around London. Adopters tend to be highly productive and larger than other firms, while young adopters tend to hire AI workers more intensively. Human capital appears to play an important role, not only for AI adoption but also for firms’ productivity returns. Significant differences in the characteristics of AI adopters emerge when distinguishing between firms carrying out AI innovation, those with an AI core business, and those searching for AI talent.

Digital technologies underpin the creation, generation, collection, transfer and use of data, and digital technological development and deployment shape data governance policy debates. This report analyses how technological development can raise different issues for data governance through the example of connected and automated vehicles, which collect large volumes of data that are likely to be personal. Through the example of these vehicles, this report explores data governance in an evolving technological landscape, and offers recommendations to ensure policies remain resilient to technological change over time.