Latin America could become a global supplier of talent in artificial intelligence at a lower cost if the right policies around education and investment from developed countries are in place to enable the creation of skilled professionals.
This is the view of Marco Stefanini, the founder and chief executive of Stefanini IT Solutions, one of Brazil's largest IT outsourcing firms with a global reach, and Fabio Caversan, research and development director in AI at the company's offices in the United States.
Stefanini and Caversan authored an entire chapter of a report published by business school Insead, Global Talent in the Age of Artificial Intelligence. The chapter looks at the current state of affairs when it comes to AI talent readiness in Latin America, as well as opportunities and challenges.
"There is a truly golden opportunity in Latin America to become a global delivery center for AI applications and projects", the report argues. "Doing so will help draw investments from leading countries looking for talent."
Large organizations and developed countries should invest in the AI field in Latin America, according to the report, preferably by joining or creating an AI center in the region, which would create talent pools that could be accessed at a lower cost:
"This could be an opportunity to attract investment from the leading AI countries in Latin America since there is a war for talent in the area and talent is getting more expensive in the world's leading AI countries", it adds.
The report argues that a few nations are well-placed in terms of aspects like governance and infrastructure in the AI field. Market adoption and investments are still low in terms of volume, it adds. The fact that much of the region's workforce could be replaced by AI systems is another upside, according to the report.
"Although these [areas] can be viewed as challenges, together, they also present a historic opportunity to transform Latin America into a large AI talent pool", the assessment's authors argue.
The assessment ranks Mexico as the best performer in terms of AI readiness in the region, followed by Uruguay, Chile, Brazil and Colombia. Cuba has the lowest score in Latin America.
The report notes that Mexico was the first country in Latin America to publicly announce a national AI strategy in 2018, with case studies using the technology to achieve social goals, such as increasing financial inclusion, combating corruption, improving public health, and reducing crime.
Uruguay, the second best-prepared country on the Insead ranking, has launched its public consultation on AI in April 2019 and spent the whole year working on the plan, which is just about ready. The report also mentions Chile's plan to address the infrastructure, priority areas and ethics, standards and regulations around AI.
On Brazil, the report notes that AI is part of the country's digital transformation plans, which will touch on the areas of infrastructure, research and development, privacy and security of digital data, education, international digital relations, digital economy, and digital citizenship and government. The report mentions that the Brazilian government "recognizes a need for a specific strategy addressing AI", as well as the public consultation on the subject, which is currently underway.
While the assessment states that Latin America is "not entirely out of the AI game" and that the region has good examples of AI initiatives among the top-ranked AI-ready countries, it mentions there is work to be done: "There are still a lot of challenges to positioning the region as a relevant global player," it says.
According to the report, challenges for the region include lack of specialized AI talent - as major technology firms are tapping into Latin talent pools if they have the rights skills - as well as poor gathering of data needed to use in AI systems, as well as overall lack of funding and insufficient or incorrect understanding of AI technology in the marketplace.
Stefanini and Caversan advocate for a joint AI strategy for Latin America, given the countries' similarities in terms of approach and difficulties faced. They also argue that people must be educated and trained in the AI field - in maths, computer science and AI tools in the short-term and neuroscience, machine learning and soft skills in the long-term.
"Opportunities and risks are alike, though at opposite ends of the spectrum: We can drastically either increase or decrease the growing gap that exists today between the population with access to resources and those without it", the report says.
"Technology can be a blessing, a curse, and - more often than not - both."