The examples above demand robust investment in science and technology, to thrive as platforms of biomedical knowledge production and true clinical impact. In this section, I describe what I see as challenges and opportunities for stakeholders from emerging economies to join these efforts, to prepare institutions and society to benefit from AE in biomedical research and health innovation.

Challenges

Despite the predicted global impact, AE R&D has historically been concentrated in entrepreneurship in North America and Europe. Projects have been conducted by groups of scientists in developed countries with consolidated science and technology policies and mature national systems of innovation. Figure 3 (supported by data extracted from Dimensions.ai) [46] demonstrates the rapidly growing number of annual publications from the United States, Canada, and Germany. Researchers in China and India have improved their presence in the field significantly, reinforcing the need to examine AE trends beyond North America and Europe.

Fig. 3

Yearly publications on autonomous experimentation systems, selected countries, 2014–2022

Below I select six challenges faced by stakeholders from emerging economies seeking to enter the field of AE.

Persistent issues in education for science and technology

Performance in AE research is closely linked to a country’s ability to cultivate a national workforce with strong qualifications in the STEM fields. It has implications in how competitive R&D centers are in attracting individuals with exceptional backgrounds in mathematics, programming, and the natural sciences, including professionals from abroad [47]. STEM education is fundamental for training scientists in automation, digitalization, and automatization of biomedical research.

Emerging economies face unique and persistent challenges in Science education, which might lead the research in those countries into a prolonged gap in AE expert knowledge. According to the New York Academy of Sciences’ 2015 report “The Global STEM paradox”, 90% of skilled workers from Caribbean countries leave home to pursue opportunities overseas. Likewise, the World Bank shows that “African countries lose 20,000 skilled professionals to the developed world each year and, as of 2011, one in every nine Africans with a graduate degree lives outside the continent.” [48]. This is not only an issue in places with low levels of economic activity and growth. Even large markets as Brazil struggle as a relevant economy with persistently poor levels of STEM education [49].

However, from the 1990s, we can see a clear trend of emerging economies who have succeeded at fostering STEM fields as a driver of a qualified workforce – being top-ranked in STEM education even when compared with high-income societies. According to the Center of Excellence in Education (CEE) Index of Excellence in STEM Education, China has led the rankings for the last 30 years, with Russia ranked in second place. Students in Taiwan are positioned in fourth place, followed by Singapore, South Korea, Vietnam, Romania, Hong Kong, and Iran [50].

While it is not possible to trace a linear relationship between STEM education and AE initiatives, the index provides some indication of which countries are most likely to advance AI for scientific research enhancement and clinical applications. It can thus inform institutional preparedness and policymaking, towards future AE-assisted innovations in the biomedical sector.

Non-resilient science and technology policies

Governments worldwide experience fiscal problems, political tensions, crises, and other inevitable shocks in governance of national policies. These realities affect the resilience of S&T policies, with financial impacts, among others. Extensively studied, resilience is a critical aspect of a well-successful system of S&T policies and initiatives, and is associated with progress and breakthroughs in basic research, innovation and catching-up of knowledge-intensive sectors as the biotechnology and biopharmaceutical industries [51,52,53,54]. For example, in comparing S&T policy between the United States and China, scholars note the value of resilience for US basic science research over the long term [55, 56].

As Fig. 4 shows, between 2002 and 2020, investment in R&D as a percentage of GDP grew significantly in countries like China and Thailand, but stagnated in countries such as Russia, Brazil, Mexico, and South Africa; S&T innovation did not see substantial growth in these countries during this period (See Fig. 4).

Fig. 4

R&D Expenditure (% of GDP), Selected countries and World, 2002–2020. Source: elaborated by the author with data from World Bank, OECD, Statista and National Governments

In some emerging economies, despite political and economic crises, S&T policies have resulted in curious paradoxes. For example, the fact that Brazil and India have increased STEM graduates from 4 million to 5 million annually in the second half of the 2000s, while countries such as the United States, United Kingdom, and Japan continued to produce 1 million graduates each year [48].

Considerable effort has been devoted to analyzing investment in applied research and technology transfer within emerging economies [57]. Table 1 illustrates the increasing significance and involvement of funders from China and South Korea, identified as key emerging contributors to the resources allocated for AE R&D, as mentioned by scientists in indexed publications (mainly the National Natural Science Foundation of China and the Ministry of Science and Technology of the People’s Republic of China). However, scientific publications in AE systems are still concentated and focused on its growth in United States and European countries. Agencies of the National Science Foundation and National Institutes of Health in the United States, European Commission (EC), European Research Council (ERC) and the German Research Foundation are also frequently associated with AE publications (Table 1).

Table 1 Ranking of 20 funders (number of mentions in indexed publications), 2008–2023

As discussed by many scholars, STEM capabilities play a critical role in emerging areas of the so-called “Convergence Sciences” as one could list computer-aided drug design systems [58], computational chemistry [59], AI-informed computational biophysics [60], and others.

This might be an straightforward claim in global technology hubs in the north, with much investment coming from both committed governments and/or private stakeholders [61]. The resilience of S&T policies in high-income countries may be partly attributed to complementary R&D expenditure between the public and private sectors, which supports innovation when economies and governments face crises [62]. However, and as we all know, this is not the reality in the Global South societies. Due to impeditive costs, high failure rates, and resistance to disruptive technologies, AI-enhanced initiatives can require sustained government investment until risks are sufficiently reduced to elicit private sector collaboration and investment.

In fact, investors are now more eager and willing to invest in AI related technologies in emerging economies [63] but much research is needed to know in what sense those investments are building permanent research infrastructures adequate to future integration of stakeholders from emerging economies in the global knowledge and technology networks in AE. Stakeholders from emerging countries should rethink the role of public and private investment in research and how they are actually leading AI initiatives to produce new science and technologies [64]. In addition, universities and research institutes can play a fundamental role in coordinating initiatives and promoting AE institutional preparedness and programs.

Competitiveness in attracting global talents

Improving the competitiveness of institutions for attracting international talents is crucial for basic research and technological innovation. In more than a decade studying how scientists conduct their work in public and private laboratories in biochemistry, genomics, biopharmaceutical manufacturing and development, molecular systems engineering, and bionanomaterials discovery, it is easy to recognize the value of internationalization and cultural diversity for science. Successful graduate programs and steady flows of talented and hard-working immigrants are fundamental to support the work of professors and senior scientists, and build research programs, where immigrants regularly become indispensable leaders [65].

Robust internationalization initiatives for graduate programs are one means to better position emerging economies institutions to access global STEM expertise and to be part of AE knowledge and innovation networks. However, internationalization is also dependent on investments done in Education for science and technology. Overcoming persistent issues about educational gaps and brain drain are still relevant, and some emerging countries do it better than others.

While language barriers and lack of resources are regularly used to explain the inability of scientists from emerging economies to access critical STEM research capabilities [66], countries such as South Korea, India, and Singapore have demonstrated that these factors offer only a partial explanation. Institutions from these countries have effectively integrated themselves into global academic networks partially through successful policies for internationalization of graduate and research programs, well-funded by universities, governments and companies [67]. For example, Nanyang Technical University, the Chinese University of Hong Kong, and the Korea Advanced Institute of Science and Technology (KAIST) in Seoul are cases of institutions who have overcome the one-way road of talent departure [68]. This can be viewed as a significant outcome of past investments in R&D capabilities within some emerging economies. Scholars dedicated to the examination of R&D dynamics in late industrialized economies show that, especially for the cases of China and South Korea, investments have led to more productive systems for fostering university-industry links, particularly as their funding mechanisms become more diversified, formalized and stable over time [69].

Quality of collaborations in clinical studies

International collaboration in biomedical research is fraught with challenges for emerging economies, often characterized by delayed collaboration in clinical trials. A seemingly simple question has the potential to shed light on the role of global south in large scientific and technological partnerships. This question pertains to areas in which scientists and stakeholders from the low and middle-income countries are specifically sought out for clinical trial collaboration, and why they considered critical to its success [70].

Studies have provided a critique of the nature of clinical trial collaboration between stakeholders from high-income countries and collaborators in emerging economies. Countries like India, Brazil, and some Central American nations have become hubs for clinical trials sponsored by multi-national pharmaceutical companies, who hold exclusive rights to new technologies [71, 72]. If emerging economies serve as crucial testing grounds, contributing considerably to advancing health technologies, questions of fair distribution of benefits arise. For example, to what extent do these collaborations strengthen local scientific expertise? Will global south scientists take an active role in shaping the early stages of technology design of AE systems to enhance knowledge infrastructures in R&D and clinical studies capabilities? These are significant questions for contemporary biotechnology research. In addition, in limited resource settings, the question of whether clinical trial collaborations should be given priority (allocation of funding, human resources) over basic research is an important one to consider.

These questions relate to emerging economies’ “technology sovereignty”. Here I adopt the notion of “technology sovereignty” from the recent work of Jakob Edler and colleagues (2020; 2023), who define it as “the ability of a state or a federation of states to provide the technologies it deems critical for its welfare, competitiveness, and ability to act, and to be able to develop these or source them from other economic areas without one-sided structural dependency.” [73, 74]. Technology sovereignty is critical in AE co-development, to ensure that clinical innovation accelerates while national knowledge capabilities are preserved. Since the Covid-19 crisis, states have been under pressure to develop more resilient and sustainable national infrastructures for health technology development [75, 76].

The integration of AE into health innovation is expected to exert significant pressure on both researchers and industry players. Authorities in emerging economies must proactively build scientific and technological capacities within local universities and healthcare systems to address the growing number of drug candidates generated with assistance of AI entering the market. This preparation will inherently require more rapid and extensive clinical trials and participant recruitment [77], while maintaining high standards of accuracy and compliance with protocols and regulations of pharmaceutical agencies [78, 79].

The great challenge for stakeholders in emerging economies is in leveraging local biomedical infrastructures to capitalize on this emerging trend, overcoming their historic role as knowledge dependent-systems and clinical trial hubs. This shift has potential to propel national innovation systems to transcend the traditional North-South divide in biomedical research.

Health systems’ disconnection from R&D activities

Health systems in emerging economies regularly face significant fiscal and political constraints, and many have experienced defunding over the past two decades [80, 81]. This is a challenge not exclusive to global south societes [82]. However, and beyond its institutional mission of offering qualified healthcare services, health systems are important assets for R&D activity and health innovation [83], as well as critical to assist decision-making on relevant national health policies and health technology initiatives and programs [84, 85].

Reliable health systems are key to supporting clinical innovation and access to health technologies. During the Covid-19 pandemic, for example, in countries like China, Brazil, and India, collaborations between scientists, technology developers, and public health systems facilitated development and distribution of locally produced Covid-19 test kits, thanks to ad-hoc coordination between universities, regional science policy instruments, state laboratories, regulators, and health systems [86,87,88]. Thus, health systems could play a critical role in collecting patient data to support research, and in creating new platforms in the early stages of AE development [89].

When incorporated effectively, health policies can inform national strategies of technology development, and serve as catalysts of sectoral S&T collaboration. Case studies from emerging economies offer valuable insights into the role of healthcare systems, including examples such as:

Dialogue between health systems and experts that led national authorities to invest in R&D for dengue technologies in the Philippines [90];

Forging of connections between medical authorities and regional scientific resources to propel a molecular biology-driven cancer research agenda in Brazil, establishing its technical and political feasibility through claims of scientific impact allied with its public health relevance [91];

Management of knowledge about Ebola through local medical and scientific collaborations in Guinea, Mali, Ghana, and Kenya [92];

Negotiations within an international consortium of experts on responsible innovation for Zika Virus [93].

Collaboration between health systems and scientists in China and Brazil to establish platforms for genomic data for use in precision medicine [94].

The essential role of health systems in technology exchange to nationalize Covid-19 vaccines in the Global South [95].

Co-production of knowledge by public health agents, experts, and US and Brazilian patients, on the topic of Long Covid [96].

These case studies illustrate diverse contributions of emerging economy health systems to the advancement of biomedical research and health technologies. At the same time they demonstrate the reactive nature of health systems, which tend to respond to local health issues and crises, rather than proactively developing long-term efforts to align institutional readiness with the evolving R&D landscape to address health challenges [97].

Ethics, transparency and democratic values

Effective democratic policies for funding R&D activity are critical in advancing emerging technologies. Confidence in ethics committees, pharmaceutical agencies, and regulatory bodies is essential. Scholars have noted that the absence of well-defined regulations and democratic institutions capable of addressing issues in technology development, animal experimentation, and clinical trials is a primary challenge faced by scientists and developers seeking to collaborate with emerging economies [98].

Respect for regulations has historically been institutionalized as part of the routine of knowledge production in biomedical domains, a concern for researchers from the early stages of technology development. In nascent fields such as molecular systems engineering, regulatory limitations are even capable of redirecting research agendas. In Europe and the United States, clear-cut guidelines and regulatory bodies composed of science and bioethics experts are understood as essential to impartial examination of ethical concerns [99].

AE in clinical innovation introduces a new level of complexity, as knowledge on engineering, computing and mathematics operate in different regimes of norms and regulations, with a traditional distancing from animal subjects, or biological or living things. Additionally, ethical and regulatory considerations of STEM research differ substantially from biomedical research and clinical interventions. For example, how will scientists conducting AI-assisted nanomaterials discovery assure ethics committees composed of health professionals that the potential risks of autonomously-synthetized chemicals have been anticipated and accounted for? This is also a concern in well-established health research organizations.

If ethics and transparency are critical, this debate must advance to the level of public exchange. Lack of transparency in reforming institutions for AI and other digital transformations in health-related research can have unintended results, in some cases damaging societal sympathy towards new technologies. Are democratic regimes in emerging economies prepared to provide an arena for discussion of this technological transition marked by intense convergence of STEM knowledge into healthcare [100, 101]?.

Cases from India [102], China [103], the Philippines [104], and Iran [105] demonstrate how a lack of democratic policies can restrict meaningful research collaboration at critical stages, due to high levels of uncertainty or imprecisely defined tech regulation. Integration of AI into the healthcare sector presents a challenge for both developed and emerging economies, as both regulatory and scientific communities are still establishing consensus and rules in this field. Reform in legal frameworks will be critical for coordination between AE developers and emerging economy stakeholders.

Opportunities

AI present stakeholders in emerging economies with a range of new opportunities [106]. In this section I highlight six of these areas.

Local expertise in digital health technologies

The AE community may lack awareness of experts in emerging economies, and their potential as collaborators. For decades, engineer scientists from emerging economies have developed tools and technologies in the fields of bioinformatics, computation, and automation with high levels of success [107, 108].

I would like to highlight two examples from India and Brazil, regarding laboratory autonomation and AI-assisted systems in healthcare. In India, the 2017 launch of Aptio Automation, the first fully automated track lab, brought automation lab innovation in the country to a new level. This initiative involved years of multidisciplinary research and robust investments from local companies and industry leaders [109], fostering a partnership between science, manufacturing, hardware and software experts [110]. Capabilities held in those projects work as a set of fundamental knowledge which could allow stakeholders to develop AE systems locally [111].

In recent years emerging economy researchers have opened avenues for collaboration, merging competencies towards constructive interface between healthcare and AI-driven knowledge platforms. For example, new capabilities developed in Latin America are fundamental to improving data robustness and to feed generative-AI integration into healthcare innovations. A recent project in Brazil well-successfully interfaced technical skills between automation systems for a mega volume reference clinical laboratory, creating an interconnected system capable of linking nearly one hundred different analyzers and seven clinical specialties [112].

Integration among scientific, engineering, and health research competencies are needed to propel AE towards clinical application. But this translational work should not be taken for granted. In AE’s current stage, developers are actively designing and prototyping efficient, precise, and reproducible systems, while partners from the healthcare sector serve as co-developers [113]. International collaborations producing large amount of clinical data serve as robust input to AE R&D hubs, and they might benefit from exchange with innovators from emerging economies.

Reducing disadvantages through digital collaboration

S&T policies and research institutions from emerging economies face disadvantages compared with high-income countries [