Unlock the opportunity: present and future of Artificial Intelligence in Latam
Rafael Igual
Business Design | Innovation Strategy | Venture Building |?Ecosystem Development | Corporate Transformation | Exponential Technologies |?Startup | Scaleup | Venture Capital
In the past decade Artificial Intelligence (AI) has shifted from the peripheries of policy attention to the centre of investment and political focus. Global AI private investment was $91.9 billion in 2022, which represented a 26.7% decrease since 2021. The total number of AI-related funding events as well as the number of newly funded AI companies likewise decreased. Still, during the last decade as a whole, AI investment has significantly increased. In 2022 the amount of private investment in AI was 18 times greater than it was in 2013.
Although government policy is growing, the region’s private sector has been leading the way in terms of AI development. Each of the largest sectors of the region has developed its own AI Startup darling, producing regional success stories of their own and attracting the attention of international investors and venture capitalists. But are the countries in Latam moving fast enough and putting in place the right policies to maximise the benefits of AI while minimising any negative impacts it might potentially have?.
This article examines the current state of AI in Latam and provides a high-level outlook for the next decade. It examines AI investment, industry trends in the region, the policy environment and challenges, and a series of policy takeaways based on international good practice for policymakers looking to develop their AI ecosystems and capabilities.
Introduction: the AI opportunity
AI strategies published by Latam countries all emphasise as their top priorities cultivating local talent, strengthening the technological infrastructure and ensuring that AI is deployed in a responsible manner. Argentina, Brazil, Chile, Colombia and Uruguay are the only countries in the region to have released standalone national AI strategies. The first countries to publish their strategies were Argentina, Colombia and Uruguay, followed by Brazil and Chile in 2021.
The covid-19 pandemic has caused an unprecedented upsurge in private tech investment across the region, with venture-capital investments increasing more than threefold in the past year alone. Since 2019 over US$20bn of venture capital (VC) funding has gone into tech startups in the region (US $4.1bn in 2020 and US $15.3bn in 2021).
Since 2010 global investment in AI has increased from a mere US$0.8bn to US$78bn in 2021—an increase of over 9,000%. However, the promise of AI is currently being experienced unevenly across the globe. For decades awareness of AI has been concentrated in countries and regions such as the US, the UK, China and Europe. The same applies to private investment—in 2020 private AI investment in the US reached US $23.6bn, followed by China (US $9.9bn) and the UK (US $1.9bn).
Balancing the promise and pitfalls of AI
The impact of AI technology is forecast to be considerable. Analysis Group, an economic consultancy, argues that AI could add up to US $2.95trn to the global economy within the next decade. McKinsey Global Institute estimates that AI will deliver US $13trn by 2030. While estimates by PwC, push this up to US $15.7trn.
But with the promise of AI come potential challenges. Risks associated with AI include the possibility of biased and unexplainable outcomes, ethically challenging applications, privacy concerns and misuse of AI. These problems can have painful implications at the individual level, such as discriminatory algorithms excluding minority groups. Another concern is AI’s potential impact on the labour market.
The proliferation of AI and automation is frequently linked to unemployment, with one study by PwC claiming that up to 30% of jobs could be automated by the mid- 2030s.
What is the present and future of AI in Latam?
To truly benefit from the promise of AI, there is work to be done throughout the Latam region, from cultivating the talent to support a thriving AI ecosystem to developing robust regulatory frameworks to promote responsible AI use and development.
Latam is characterised by diverse AI ecosystems in terms of capabilities, with countries exhibiting strengths in vastly different areas. Brazil, for example, has made a name for itself as the capital of tech startups, which account for over 5.6% of its GDP. Here, S?o Paulo in particular stands out. Home to over 2,700 tech startups and the largest tech hub in the region, the city’s GDP alone is larger than the combined economies of Argentina, Chile, Paraguay, Uruguay and Bolivia.
At the policy level, Colombia has already published a rich set of policy initiatives that support its AI ecosystem. Since 2018 the country has been governed by a pro-technology government and has been investing in new AI policy initiatives, including its AI strategy, the region’s first AI ethics framework and a new international AI council.
These differences in strengths and capabilities present a very different image compared with other regions of the world. The Middle East and North Africa (MENA) region, for example, is characterised by a government-led investment strategy, where deep pockets of sovereign wealth funds stimulate the still nascent tech sector. Similarly, while European countries exhibit differences in capabilities, with France being particularly strong in AI policy and Luxembourg in Infrastructure, the EU has played a harmonising role for the region’s AI policy.
Latin America has been strongly affected by the pandemic. Since the start of the outbreak the region has recorded nearly 1.57m deaths (accounting for 28.2% of global deaths), and its economy contracted by 7% in 2020. However, it has also given rise to an investment boom among Latin American technology companies, driven by increased online activity and investors’ recognition of huge AI opportunities. According to the Latin America Venture Capital Association (LAVCA), in 2020 tech startups received US $4.1bn in venture-capital investment. In 2021 that number almost quadrupled, reaching US $15.3bn.
Figures for AI-specific investment are less readily available. The startups, in particular, drove AI adoption in the region. The reason for this is that startups are more agile in integrating AI into their operations, products and services, while the organisational culture at large enterprise can stymie the implementation of tools like AI.
Moving forward: seizing the opportunity
The region has all it takes to make the AI revolution a success, but whether it will turn this potential into substantial results has yet to be determined. The past years’ investment in developing AI policies in Brazil, Colombia and Chile as well as the catalysing effect of the covid-19 pandemic on Latin America’s tech sector have provided the countries in the region with a unique opportunity to improve their AI capabilities and foster an uptake across their industries.
Other countries, such as Mexico and Argentina, have yet to implement comprehensive AI policies, but the rapid growth of the region’s tech sector could put pressure on their governments and inspire renewed investment in AI capabilities. For Latam, the diversity of its AI ecosystems could prove to be a strength.
Increased collaboration between the countries in AI development and greater exchanges of technology enablers such as semiconductors and talent could help the countries of the region to offset their weaknesses while capitalising on the areas where they stand out.
AI’s impact across industries
Latam is expected to gain 5.4% of GDP, equivalent to US $0.5trn, as a result of AI by 2030. While this is an impressive gain, it still falls behind China is set to gain 26.1% of GDP, and U.S. 14.5% by the same year. Since the covid-19 pandemic and its catalysing effect in the region’s investment in AI, however, this number is expected to rise.
While post-covid data on AI’s contribution to the region’s economy are not readily available, separate analysis shows that in four out of our five priority countries AI is expected to boost GDP by an entire percentage point by 2035.
Research by the IDC, explains that Latin America’s growth in AI adoption will be driven by companies’ broader need to adopt digital transformation, the benefits they can gain from improved computing processing capacities, and greater resilience against unforeseen market changes. In a region where there are structural problems that can be solved by new enterprises, company executives and policymakers are realising that AI is well positioned to help solve these regional problems.
Even though forecasts for AI growth are lower than for the rest of the world, technology is expected to disrupt almost every sector in the region. While data and forecasts outlining the economic impact of AI by sector are limited, by assessing different use cases across the region we have identified four industries that are expected to be of particular relevance to our target countries in the next decade: public services, healthcare, agriculture and banking & finance.
PUBLIC SERVICES
The public-sector use of AI in Latam has the potential to create opportunities for governments to solve some of the systemic challenges and inefficiencies that have been holding back the social and economic potential of Latam.
For example, one of the main justifications for Colombia’s strategy is the potential of AI to increase the productivity and efficiency of public services, which is also one of the key pillars in Argentina’s national AI plan. Similarly, Chile’s national AI policy outlines as a key objective the need to accelerate state modernisation through AI. The Brazilian strategy’s third pillar focuses on how AI can be applied to public services for the benefit of citizens.
Some use cases of AI in the public sector include improving service delivery and government operations. For example, according to the IDB, AI models have a 300% greater predictive capacity than traditional econometric models when forecasting regional trade scenarios, while using AI to personalise education models can increase pass rates by 15% and reduce remediation costs by 40%.
AI for anti-corruption in procurement
Utilising AI-based models has the potential to minimise this economic blow, while also reducing the resources needed to do so. In Colombia, for example, the District of Veeduría has deployed a machine learning (ML) model to draw officials’ attention to the contractual processes most exposed to acts of corruption or inefficiencies.
The model leverages ML algorithms that trawl through a large database of district-level public procurement contracts to predict the level of corruption risk and inefficiency.
Making government more responsive
At the provincial level, Argentina’s public sector has deployed robotic process automation (RPA) to automate bureaucratic tasks and improve public efficiency. The Ministry of Finance of the Province of Córdoba has introduced an RPA software called Laura, which connects a potential beneficiary with the National Social Security Administration (Administración Nacional de la Seguridad Social—ANSES) database to verify their pension situation and determine whether a national or provincial benefit applies as well as their retirement amount.
Moreover, since 2017 Buenos Aires has used Prometea, a system that leverages RPA and machine learning to automatically prepare judicial documents, reducing time spent by 99% for some processes. The tool also uses natural-language processing (NLP) in a virtual assistant, or chatbot, which interprets spoken commands by the user and also provides responses that can guide the user throughout the process of preparing a legal document.
HEALTHCARE
AI adoption in healthcare in Latam is increasing, especially for the purpose of screening and the early detection of conditions, potentially relieving healthcare systems that are overwhelmed by patient demand. The AI healthcare market in Latam has been projected to grow in terms of revenue and to expand at a compound annual growth rate (CAGR) of 37.95% during the forecast years 2019-27.
Leveraging AI in healthcare can play a critical role in improving public access to necessary health services, improve resource allocation, and potentially increase the capacity and resilience of the region’s workforce.
Prediction and prevention of blindness
Latin America’s population aged 65 or older is expected to more than double in the next 30 years, from around 8% today to 17.5% by 2050. This share is expected to exceed 30% by the end of the century. As a result the healthcare sector needs to be well equipped to manage health issues that could affect this growing section of the population.
In Mexico,?PROSPERiA ?has invested time and money in developing a model that utilises AI to help medical professionals detect causes of blindness by analysing high-quality digital images of patients’ eyes. By using AI-enabled automated image recognition of retinas, doctors can automate the retinal screening process, detect patients at risk of developing retinopathy and provide treatment that could prevent this.
The use of such automated tools represents an opportunity to reduce public expenditure associated with direct and indirect costs of such illnesses, while also indirectly addressing the shortage of ophthalmologists to treat a growing problem in the region.
AGRICULTURE
All AI policy documents across the priority countries mention the strategic importance of the agricultural sector and highlight the role of AI in increasing efficiencies and resource use.
For example, Brazil’s national AI strategy highlights how AI systems can help analyse farm data in real time, anticipating the consequences of weather conditions, water use, soil health and other variations. This can help farmers to increase the yield and quality of crops and identify what to plant, how and where.
Cost-effective allocation of resources
Given the region’s reliance on the agricultural sector, it is unsurprising that 55% of the region’s 450 agtech startups are using AI to increase efficiency. Resource efficiencies, in particular, are crucial: the agriculture sector, for example, consumes 70% of global water resources per year for irrigation use to ensure sufficient food production.
Aimirim , a Brazilian startup which provides AI solutions for industry, increases the efficiency of sugarcane pulp combustion for energy production using AI to simulate, control and automate the process. Brazil-based Leaf Agriculture is also working to improve resource allocation by aggregating and organising data from around the farm, making them accessible and useful for farmers and agribusinesses.
Similarly, in Argentina,?Kilimo ?is an AI-based solution that seeks to avoid water waste by optimising freshwater use in agriculture. The company, which is the first certified tool in the region that measures the water footprint in irrigation fields, raised US $1.2m in venture capital funding in 2019. In 2020 Kilimo was expected to benefit over 2,200 small and medium-sized farmers in the region, save 179bn litres of water and save US $22m in direct costs for farmers.
Emissions reductions
Another key factor affecting the livelihoods of farmers is the impact of climate change. Although the LATAM region as a whole accounts for only 5% of global emissions, this share is rising. The World Bank forecasts that climate change will lead to an increase in extreme poverty in the region of up to 300% by 2030.
To address this concern, the IDB has partnered with Japan’s SoftBank to launch e-kakashi, an AI-powered tool that has been deployed in Colombia to improve the productivity and sustainability of rice farming, a process that can emit almost 500m tonnes of greenhouse gases (GHGs) worldwide. The tool uses AI to collect large amounts of environment and weather data, which it then processes and analyses to help farmers navigate the cultivation process and create an optimal rice-producing environment that minimises emissions.
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BANKING & FINANCE
The fintech sector in Latam receives a significant share of venture capital investment, capturing nearly 40% of total VC investments. While data on the adoption of and investment in AI in the region’s financial sector is scarce, total fintech funding in the region has increased from US $44m in 2013 to US $2.1bn in 2019—an increase of over 4,000%.
Financial inclusion through AI adoption
According to research by EY, a consultancy, improving financial inclusion can boost GDP by up to 14% in developing economies, suggesting a strategic and economic advantage of increasing access to financial services in the Latam region.
Challenger fintechs and neobanks employed AI to onboard and provide previously unbanked people with quick and easy-to-use digital banking solutions. As a result, between May and September 2020, 40m people in the region opened a bank account.
Leveraging AI makes financial products like loans more available to populations without a formal bank account, payslip or digital financial track record. With AI, disbursing small loans can become more feasible as the process is automated and scalable. Brazilian unicorn Nubank uses AI for credit decisions as well as to make financial intelligence recommendations to its customers.
Nubank ?has made it part of its goal to serve the currently underserved, which it is managing to do by removing fees, improving the ease of interaction with the technological platform, and ensuring more accessible communications. As a result, it has seen the number of its users expand from 3m in 2017 to over 40m in 2021, with 20% of its customers accessing a credit card for the first time since joining the bank.
In Mexico another fintech firm,?Konfío , became the fourth startup in the country to reach unicorn stage, recording a market value of US $1.3bn in 2021. Konfío is the largest online lending platform for small and medium businesses (SMEs) in Mexico and aims to empower underserved SMEs to benefit from the formal economy and access capital, including those without any formal credit history.
Improving the customer experience
With the pandemic shifting more individuals online, financial services have had to adapt to becoming more innovative and accessible. The risk of financial services failing to progress in line with advances in technology can impact customer engagement and retention significantly.
Creating more value at a lower cost also drives?Ualá’s ?investment in AI, allowing the Argentina-based fintech to understand how clients use its services and on this basis refine its features and offerings.
Another example is Colombia-based RappiPay, which uses AI to make sense of its vast collection of data on consumer behaviour. Recently, the neobank was able to use AI-driven language personalisation in its marketing efforts, which resulted in a significant conversion from views to sign-ups to the RappiCard waiting list.
Barriers and enablers for AI uptake
The policy and business environment for AI in Latam provides examples of both success stories and growing pains. This section sets out the policy context and ways to overcome constraints in order to facilitate safe and responsible AI deployment.
Digital infrastructure
The lack of a digital infrastructure remains a significant challenge for the region as far as supporting its AI ecosystem is concerned. As mentioned by our expert interviewees, multinational companies have been trying to move into the region with the aim of developing regional hubs, but the essential infrastructure, namely 4G, 5G and fibre, is still lacking. Chile and Mexico are the only LATAM countries with an existing 5G infrastructure, and Brazil announced the rollout of its 5G infrastructure in November 2021.
Similarly, as financial and other services move online and employ AI to increase efficiency and reduce costs, digital infrastructure could become a determinant of financial and other types of inclusion. Investing in digital infrastructure and 5G networks thus remains a crucial policy priority for the region’s countries. Furthermore, with the rest of the region facing a gaping digital divide, expanding the availability of bandwidth from cities to rural areas represents a real opportunity for socioeconomic impact.
AI Talent
The availability of AI talent remains an important issue in Latin America, and virtually all the region’s published AI strategies make it a priority. Part of the challenge in finding experienced talent is also the relative newness of AI-driven businesses in the region.
Until then the tight market for talent could constrain firms that are early in their journey to implement AI, because they may find it more difficult to compete with companies that have a more clearly defined AI strategy and already have the bulk of their team in place.
Enterprise AI programmes
In response to the region’s shortage of talent, private companies are stepping up to the plate and developing their own in-house AI onboarding programmes. These programmes are providing the region’s firms with a quick supply of talent, matching the firms’ business needs directly.
It is unlikely that these in-house initiatives will be able to match the talent gap in the region, but they could well form the basis for more orchestrated vocational programmes.
AI-enabled labour market
Investing in educational programmes and upskilling, however, is of paramount importance not only for AI development but also for safeguarding the region’s labour market against automation technologies. While more research is needed to understand the specific impact of automation on the labour market, there is agreement that policies need to be put in place to upskill the region’s workforce and enable labour mobility.
There are a number of policies that could prepare the region’s workforce to participate in an AI-enabled labour market. Life-long learning programmes, for example, can provide a starting point for ensuring that workers can develop market-relevant skills as technology uptake moves forward.
AI Policy playbook
AI has found fertile ground in Latam. A number of regional success stories provide evidence that countries across the continent have the capabilities and talent to grow innovative companies with the potential to scale across the continent and contribute to economic growth. From Healthtech startups forecasting and preventing illnesses that affect millions, to Agtech companies using AI to harvest soil more sustainably —the current growth trajectory suggests that these startup— led innovations are just in their infancy.
To help policymakers in the Latam region consider how to tackle these challenges and what policies they should implement for both the short and the long term. IDB and Economist Impact have produced a policy playbook that analyses policies across six key dimensions.
1. Nurturing local talent
As emphasised throughout this report, human capital is critical to realising a successful and thriving AI ecosystem. There is a need for policymakers in the Latam region to pay greater attention to cultivating a highly skilled domestic workforce capable of both developing and using AI systems from a young age, while minimising the risk of graduates moving to the US, a global leader in AI. At the same time, policymakers should create incentives to attract and retain foreign talent to the region’s AI research community.
2. Fostering local research & development
The Latam region accounted for only 1.3% of global AI journal publications between 2000 and 2020, indicating a dearth in research capabilities. Contributing to this is the global phenomenon of AI researchers and data scientists facing the temptation to move from academia to industry, attracted by lucrative salaries and better resources, such as higher computing power and better data. To counteract this, policymakers can implement strategies that attract researchers from leading countries and institutions to the Latam region, while creating an AI research agenda focused on local and regional AI challenges.
3. Safeguarding transparency and ethical use
Globally, one of the most important conversations about AI focuses on transparency and ethics. Such risks include the perpetuation of real-world biases in algorithmic decision-making, potentially resulting in the discrimination of already disadvantaged groups such as ethnic minorities, women and people on low income. On top of this, governments are grappling with ensuring that different stakeholders are appropriately guided to understand and engage with AI effectively and safely.
4. Creating a robust infrastructure and data environment
As mentioned above, infrastructure and data are two of the key enabling prerequisites of a robust AI ecosystem, along with skills and talent. As AI proliferates across sectors, so will the requirements needed to run such systems. While investment in AI is considerable in the region, this must be matched by accessible and robust data, which are severely lacking in the region at the moment.
5. Industry engagement
Latam is experiencing rapid growth in its AI ecosystem, with significant investment pouring into the private sector during the pandemic. To advance this progress, policymakers need to stimulate the private sector and the startup ecosystem further, which can, in turn, foster more innovation, drive economic growth and increase job growth in a fast-moving industry. Policymakers can allocate budgets to explicitly support local AI startups, encourage home-grown innovation and collaborate with the private sector to ensure knowledge exchanges.
Create AI challenges by inviting startups to bid for solving particular local challenges through AI products. Non-financial and financial incentives can be useful tools to encourage innovation in the private sector, for example through AI innovation challenges. Such challenges are typically focused on using AI to solve real-world challenges in areas such as transport and public healthcare.
Incubators and accelerators focused specifically on AI Startups. Establish government-led incubators and accelerators to support the AI startup ecosystem. Engage in multi-stakeholder consultations when developing AI policies and related policies.
6. Refining AI policies
Develop, revise and monitor national AI strategies. Some of the region’s governments have designed national AI strategies while some are still in the process of doing so. Governments that have not developed AI policy documents should do so. Governments that have already developed these policies should ensure that they are regularly refined to align with their set timeline, and simultaneously monitor that over time they are aligned with the county’s vision.
Establish AI working groups with policymakers from across the region to align policies. Create AI learning tracks for government officials focusing on the nature, opportunities and risks stemming from AI. Collaborate with leading tech industry actors to develop a suite of short, accessible AI courses to support public-sector employees’ professional development in a digital economy, with a focus on the fundamentals of AI, regional challenges of AI adoption, and the responsible and ethical use cases of AI.
Closing thoughts
Although 2022 was the first year in a decade where private AI investment decreased, AI is still a topic of great interest to policymakers, industry leaders, researchers, and the public. Policymakers are talking about AI more than ever before. Industry leaders that have integrated AI into their businesses are seeing tangible cost and revenue benefits. The number of AI publications and collaborations continues to increase. And the public is forming sharper opinions about AI and which elements they like or dislike.
AI will continue to improve and, as such, become a greater part of all our lives. Given the increased presence of this technology and its potential for massive disruption, we should all begin thinking more critically about how exactly we want AI to be developed and deployed. We should also ask questions about who is deploying it, AI is increasingly defined by the actions of a small set of private sector actors, rather than a broader range of societal actors.
The growing popularity of AI has prompted intergovernmental, national, and regional organizations around the globe to craft strategies around AI governance and public sector investment. These actors are motivated by the realization that the societal and ethical concerns surrounding AI must be addressed to maximize its benefits. The governance of AI technologies has become essential for governments across the world, and particularly in Latam region.
The proportion of private companies adopting AI in 2022 has more than doubled since 2017, though it has plateaued in recent years between 50% and 60%, according to the results of McKinsey’s annual research survey. Organizations that have adopted AI report realizing meaningful cost decreases and revenue increases.
As the region is looking to a post-covid future, the perspectives and seizing of AI opportunity in Latam is amazing. AI public sector and venture capital investments, industry trends in the region, the policy environment and challenges looking to develop AI ecosystems and capabilities.
Argentina, Brazil, Mexico, Colombia, Chile and Uruguay?are pioneers in develop, publish and implement (standalone) National Policy, Plan or Strategy on Artificial Intelligence. Comprising priority initiatives and measures covering five main areas:
The proliferation of national AI strategies, initiatives and measures show us the importance of AI to the region’s socioeconomic transformation.
We still have a long way to run, but we’re building the foundations of the greatest revolution ever seen in LATAM. I invite you to subscribe to my Substack's Newsletter to be informed of use cases, applications, risks, benefits, corporates, startups, venture capital, public policies and investments on Artificial Intelligence, Large Language Models & Data technologies applied to innovation, transformation, growth, sustainability and social impact in LATAM markets.
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