By Catherine Jewell, Information and Digital Outreach Division, WIPO
Now in its 15th edition, the Global Innovation Index (GII) 2022 tracks global innovation trends and ranks the innovation performance of 132 economies amid the ongoing COVID-19 pandemic, geo-political tensions and supply chain and energy disruptions. The GII provides benchmarking data on innovation performance and serves as a useful guide for the development of innovation policies.
GII 2022 also explores the future of innovation driven-growth at a time when the socio-economic impact of innovation is at an historic low, despite a surge in R&D investment. The co-authors of the report, Senior Economists Klaas de Vries, from The Conference Board, and Sacha Wunsch-Vincent, from WIPO, share the key findings.
What were the most striking developments in the GII 2022 rankings?
GII 2022, which maps the world’s most innovative economies, reveals a number of interesting moves, with some new powerhouses emerging. Switzerland topped the rankings for the 12th consecutive year, followed by the United States, Sweden, the United Kingdom and the Netherlands. China (rank 11) is knocking on the door of the top ten, with consistently strong performance from India (rank 40) and Türkiye (rank 37), which entered the top 40 for the first time.
The middle-income economies with the fastest innovation-performance growth to date include
Viet Nam (48), the Islamic Republic of Iran (53) and the Philippines (59).
We also see several developing economies performing above expectation on innovation relative to their level of economic development. These include newcomers Indonesia (75), Uzbekistan (82) and Pakistan (87). Eight so-called “innovation over performers” are from Sub-Saharan Africa, with Kenya (88), Rwanda (105) and Mozambique (123) in the lead. In Latin America and the Caribbean, innovation over performers include Brazil (54), Peru (65) and Jamaica (76) 
.
What major trends does the GII 2022 reveal?
GII 2022 shows that research and development (R&D) and other investments, which drive innovation, continued to surge in 2022, despite the COVID-19 pandemic. The world’s most innovative companies increased investments in R&D by 10 percent to over USD 900 billion invested in 2021, higher than pre-pandemic levels. Venture capital (VC) deals also surged by 46 percent in 2021, with Latin America, the Caribbean and Africa experiencing the strongest VC growth. However, the VC outlook for 2022 is more somber, with a significant deceleration expected, raising significant concerns for more fragile economies.
In fact, the socio-economic impact of innovation is at an all-time low, with productivity growth stagnating.
What is the relationship between innovation and productivity?
Traditionally, innovation has been the key to improving levels of productivity. GII 2022, however, points to a pronounced slump in economic productivity since the 1970s. Put simply, productivity is about how efficiently we produce things. Improvements in productivity directly boost economic output relative to the population, improving living standards, for example, by lifting people out of poverty and eradicating arduous tasks.
Major economic downturns aside, productivity and economic output grew year-on-year worldwide throughout the 19th and 20th centuries (see Figure 1).
While it took 50 years for productivity to double after 1870, it has since doubled roughly every
25 years. As a result, in 2021, an hour worked in high-income economies produced, on average,
24 times more goods and services compared to 1870. The rise in living standards since the 19th century and the First Industrial Revolution can be traced to technological breakthroughs, new waves of invention and innovation, and the effective diffusion of new technologies across economies.
Figure 1: Real GDP per capita levels at the frontier, 1300–2021
Unfortunately, since the 1970s, there has been a sustained slowdown in productivity. The slowdown intensified during the global financial crisis of 2008/2009 and has since worsened. In 2021, global labor productivity fell sharply to zero, and is forecast to stagnate in 2022, largely because of higher energy costs.
Figure 2: Labor productivity growth, 1871–2021
For middle-income economies, the trend is not so clear-cut. China’s productivity growth gathered speed from the 1980s, but has slowed already over the last decade. Most other emerging economies, however, were never part of the productivity spurt, in particular Africa, Latin America, and most economies in the Middle East and Asia. Notable exceptions are India, Indonesia and Türkiye. Indeed, the problem for most developing economies is that they have never enjoyed increasing productivity growth.
How pessimistic or optimistic are you about innovation in future productivity-driven growth?
Technology pessimists argue that the supply of innovation has fallen, slowing improvements in living standards. They argue that innovations are more difficult to come by and that those that are emerging will not have the same transformative impact on productivity as past “great” inventions like the combustion engine, electricity, plumbing, airplanes and barcodes. In other words, despite massive innovation investments, it is becoming more costly to find and develop transformative innovations and we are living in a period of stagnation.
However, technology optimists, whose arguments we favor, note that it takes time for the impact of innovations to unfold given the many challenges associated with the diffusion of innovation at every level.
What are the challenges associated with diffusion of technology?
You may think the main challenges relate to investing money into R&D, filing patents and driving different forms of inventions. But the eternal challenge is the uptake of technology; how to get firms and households in as many countries as possible to use these inventions. And today, that process is too arduous and slow. The adoption of green technologies to mitigate the catastrophic effects of climate change is a case in point. The technology exists, but its use, and therefore its impact, lag starkly.
Research and development (R&D) and other investments, which drive innovation, continued to surge in 2021 despite the COVID-19 pandemic.
What then is the outlook for an innovation-driven productivity revival?
Evidence is building of the emergence of two innovation waves, each with the potential for large, measured – and possibly unmeasured – productivity and welfare impacts.
The first is the ICT wave, which started in the 1970s and is forecast to regain strength over the coming years. This is best conceptualized as the “Digital Age wave” made up of two consecutive surges. The first led to the installation of sophisticated communication networks and equipment, such as the Internet and mobile devices. The second relates to the diffusion of general-purpose digital technologies, such as supercomputing, cloud computing, the Internet of Things (IoT), artificial intelligence (AI) and automation.
The impact of this Digital Age wave unfolds in two ways. First, in terms of a powerful effect on scientific advances and R&D in fields like bio-informatics, pharmaceuticals, green tech and others, leading many to observe a convergence of ICT, bio- and nanotechnology, and cognitive science research. Second, in terms of its profound effect on non-ICT sectors, in particular through the application of AI-driven automation, large-scale digitalization, 3D-printing and advanced robotics. The large-scale adoption of these technologies would hike productivity in every manufacturing sector and agriculture, as well as those large service sectors – education, health, construction, hospitality and transport - which are currently trailing in productivity.
There is also the real possibility of a “Deep Science” wave building around breakthrough inventions and innovations in the life sciences, health, agri-food, energy, clean tech and transport. This wave will drive scientific progress in an array of technical fields (beyond ICT), which have matured over the last decades and which are erupting.
Evidence is building of the emergence of two innovation waves, each with the potential for large, measured – and possibly unmeasured – productivity and welfare impacts.
Both the Digital Age and the Deep Science waves have been building for some time. Breakthroughs in biotechnologies, biochemistry, nanotechnologies, new materials and other advances in basic science over recent decades are paving the way for downstream innovations and signal a strong comeback for the hard sciences.
Taken together, these dynamics have driven radical progress in diverse fields, including the life sciences, health, agri-food, energy, clean tech and transport innovation .
On balance, if adoption is high – and that is the crux of the matter – innovation-driven productivity growth propelled by the Digital Age and Deep Science waves could be high.
What are some of the innovation policy priorities that you identify?
First, the funding of research relevant to future innovation waves remains a key role for government.
Second, in all future innovation waves, policymakers need to influence the translation and adoption of research through the application of both supply and demand-side policies that set innovation targets and focus on specific areas. Such decisions can no longer be left to the market alone.
Third, the rising inequality among firms and regions that lead, and those that lag, between high-paid and low-paid workers, and across countries, is a major drag on technology diffusion, adoption and productivity. Tackling these inequalities will be key to realizing the benefits of any upcoming innovation wave.
Fourth, a skills gap stands in the way of new innovation waves materializing and creating impact. This is most evident in the fields of advanced ICT, programming, AI and data science and is valid even in the most advanced high-income economies. Similar skills gaps will also emerge in the fields driving the Deep Science wave.
The funding of research relevant to future innovation waves remains a key role for government.
Fifth, access to, management and valorization of data are cornerstones of all future innovation waves. New data infrastructure and management systems are essential.
Sixth, over the coming years, topics such as humanoid robots, AI, bio- or genetic engineering, new health solutions, and novel food types, will challenge social acceptance and will require public debate to explore the risks, social values and the pros and cons of these ground-breaking innovations. Developing a common understanding of the social benefits of these advances will be central to facilitating their uptake and adoption.
Finally, the current international environment poses real challenges to the diffusion of technology through trade, investment and other international knowledge flows. This is particularly problematic for emerging and developing countries, which are in dire need of integrated global value chains and innovation networks in order to catch up. Keeping alive the possibility of quick productivity wins will be crucial. Developing economies will also need specific approaches to absorb existing technologies – particularly in health and agriculture. Fostering incremental, grassroots innovations and making traditional innovation policy measures more relevant to less formal innovation are important factors in this context. Local governments and firms need to actively steer the development of innovations that respond to local needs – rather than relying on technology diffusion alone.
