Key takeaways:

• • • Strategic collaboration is becoming a defining strength for the region — Latin American organizations are realizing that progress in AI accelerates when they combine forces by linking industry expertise, academic talent, and public‑sector support.

    • AI initiatives rooted in real local challenges are gaining global relevance — By developing solutions grounded in the region’s own structural needs, whether in infrastructure, finance, agriculture, education, or mobility, many LatAm firms are producing technologies that are both highly impactful and naturally scalable.

    • Demonstrating clear outcomes is becoming fundamental — Organizations that show concrete operational improvements, measurable efficiencies, or stronger customer outcomes are strengthening their position with investors and partners.

In recent years, Latin America has experienced significant growth in investments related to AI, accounting for . This is strikingly low given that the region makes up around 6.6% of global GDP, highlighting the region’s opportunities to scale AI initiatives even further. Although there are notable differences among countries, Mexico and Brazil — the two largest LatAm economies — stand out for their volume of AI projects and funding, followed by other nations such as Chile, Colombia, and Argentina.

By recognizing the region’s strengths — which include cost-effective operations, access to data, clean energy, and public support — the region’s businesses can better position themselves and design strategies to draw in international investors that may be increasingly seeking promising locations for AI development.

Lessons from LatAm’s AI success stories

Latin America has produced remarkable AI success stories that can serve as models to build confidence among investors. These cases — involving companies that attracted substantial investment and achieved growth — demonstrate valuable best practices that range from technological innovation to working with governments and corporations. Some of these best practices include:

Building strategic alliances

The journey of innovation rarely unfolds in isolation. At times, the presence of large, established companies, whether local industry leaders or multinationals, has served as a catalyst for AI projects. The experience of that specializes in AI-powered agricultural irrigation, proves it. Now, Kilimo is partnering with EdgeConneX, a data center company based in the United States, on a community .

Academia, too, can be woven into this narrative. Collaborations with research centers or universities offer scientific credibility and connect ventures with emerging talent. In Mexico, AI startups often originate within university settings — such as computer vision projects from the National Autonomous University of Mexico (UNAM), for instance — and maintain agreements that sustain ongoing innovation and technical progress even with modest resources. And academic validations, whether in published papers or conference accolades, tend to resonate with foreign investors. Indeed, the emergence of this ecosystem that features early corporate clients and academic mentors frequently lends a distinctive appeal for those seeking investment.

Focusing on local problems with global impact

Within Latin America, certain issues prove especially relevant in situations in which AI solutions intersect with sectors renowned for regional strengths, such as fintech and financial inclusion, agrotech optimizing agriculture, and foodtech drawing on local ingredients. The experience of Chilean food startup NotCo — in which and subsequently exported — suggests how innovations rooted in local context may generate broader attention.

By addressing needs in urban transport, education, mining and related areas, local LatAm companies can provide access to homegrown data and users, which can further refine technology and open pathways for investors into similar emerging markets. When AI solutions respond to genuine pain points rather than mere novelty, momentum often builds more quickly, and the model finds validation among that evaluate investments.

Showing results and AI ROI early on

Questions linger for many executives . Evidence of clear metrics like cost savings, sales growth, or error reduction can prove persuasive, especially when complemented by success stories from local clients.

Recent studies show that companies ; and such figures tend to reassure those considering investment by illustrating tangible improvements. Testimonials or independent validations, such as a university study, can further illuminate achievements.

The act of quantifying impact — whether in efficiency, revenue, or other relevant KPIs — has a way of transforming perceptions from uncertainty toward clarity.

Leveraging government incentives and collaborations

Many Latin American nations have put forth support programs for AI and tech projects, such as non-repayable funds, soft loans, and tax benefits for innovation illustrated in , , , or the .

Public financing, when present, often acts as a stamp of validation for private investors. For example, this trust extended to Brazilian startups receiving Finep support for AI health projects, which in turn can shift perceptions for foreign ventures capitals. Engagement in government pilots, such as smart city initiatives or solutions for ministries, provides valuable exposure. In such contexts, public-private partnerships and incentives seem to act as quiet levers for growth and legitimacy.

Seeking smart and diversified financing

Financial strategies in Latin America have been shaped by the interplay of local and foreign capital. Local funds often bring insights and patience, while foreign funds may offer larger investments and global scaling experience. Ownership dilution sometimes accompanies the arrival of strategic investors, whose networks can prove invaluable, such as . Programs like 500 Startups, Y Combinator, MassChallenge, and international competitions have ushered LatAm AI startups such as Heru, Rappi, Bitso, and Clip into new rounds of capital following increased exposure.

Efficiency in capital management, which can be demonstrated with lean burn rates and milestone achievement with limited resources, signals an ability to execute within the realities of LatAm, which may enhance the appeal for future investments. The cultivation of relationships and responsible stewardship of capital frequently matters as much as the funds themselves, suggesting that the value of mentorship, contacts, and reputation is often intertwined with deepening financial support.

Unlocking AI Investment

By applying these principles, Latin American companies have achieved a better position to attract AI investments to their projects and help position the region as a viable destination for technology capital. These recent experiences show that when a LatAm company combines innovation, talent, and strategy — while communicating its story well — it can win over global and local investors alike. Each of the best practices noted above is based on real lessons: international alliances (NotCo with US funds), leveraging incentives (Brazilian companies funded by Finep), talent formation (Santander and Microsoft programs), focus on ROI (successful use cases that convince boards), and more.

Latin America has challenges but also unique advantages. Companies that manage to navigate this environment intelligently will increase their chances of securing the financing needed to innovate and grow. By doing so, they will contribute to a virtuous circle in which each new success attracts more investment to the region and opens doors for the next generation of LatAm AI ventures.

You can find more about the challenges and opportunities in the Latin American region here

For corporate law departments, the cost of an AI-related investment might be on a different scale due to the smaller size of the team, but it is no less daunting given the incessant budgetary pressures that many corporate general counsel (GCs) are under daily. The need to implement an AI-focused strategy along with adopting the tech to support and moving the department toward an AI-driven future is becoming an unavoidable reality for many corporate law departments. Knowing that expense is inevitable, however, does not address the question of how to justify it or calculate the return on that investment (ROI).

Framing the ways we think of ROI

One of the classic measures of ROI is as a multiplier. If a business spends a certain dollar amount on something, they can gauge ROI based on how many multiples of that amount return to the business in gain.

However, this doesn’t really apply to AI in the GCs’ office, for obvious reasons. First and foremost, the GCs’ office typically does not generate revenue for the business, so calculating the revenue generated as a result of an investment in legal tech does not work the same way as it would for a sales or marketing team — but that’s not to say there aren’t ways to calculate return of value to the business.

One potential measure of ROI on new AI tech can be found in its impact on outside counsel spend. If better technology enhances the capacity of the in-house legal team such that there is less need to hire outside counsel, that should factor into the ROI for that specific tech investment.

Of course, there are potential complications here. First, outside counsel rates continue to climb, so even if less work is being sent to outside counsel, total spend on outside counsel may still go up. Second, matter volumes for in-house law departments are increasing nearly across the board and are predicted to continue to do so. As a result, increased matter volumes may exceed even the AI-enhanced capacity of the in-house law department.

How to best respond to these complications is also a matter of framing. Reporting outside counsel spend in raw dollars may not be the best measure of the benefits the in-house team has gained from its AI investment. There are a few other metrics GCs should consider tracking and reporting that might better highlight the benefits the in-house team has gained from AI, including:

• • • ratio of in-house legal matters compared to work sent to outside counsel;
    • increase in total legal matter volume compared to increase in volume sent to outside counsel;
    • percentage increase in matters handled in-house;
    • qualitative measures of the complexity of matters being handled in-house; and
    • savings in projected outside counsel spend at current rates compared to actual outside counsel spend.

The latter measure could actually be quite insightful. It requires multiple data points but speaks the kind of direct financial language in which boards of directors are fluent. Essentially, the GC would need to calculate the amount of work that is now being done by the in-house team as a result of their new-found AI-driven capacity, then calculate what it would have cost to have had outside counsel do that work.

This measure would account for both work that has shifted in-house and away from law firms as well as any new work resulting from the overall increase in matter volume that the in-house team is taking on without involving outside counsel.

Finding creative ways to confront reality

None of this is to suggest that these are the only, or even the best, metrics to meet the challenge of calculating ROI. The more important point is that GCs should be looking creatively in how they think about ROI. Further, the business’s CFO can be an invaluable ally in formulating an approach because the finance team is so often tasked with creating the reporting that other executives and the board rely on when guiding the business. The CFO already speaks the language, and GCs should use them as an interpreter and ally to help shape metrics that tell an effective story for the legal department.

It’s also important to remember that part of the ROI of AI technology is the same as any other technology upgrade. How does the business calculate the ROI on an upgrade to company-provided laptops or phones? How did the business justify making the switch from desktop systems to laptops? While the move to AI is, in many ways, of a different character than past tech upgrades, at its root, what we are talking about in moving to AI-enabled tech is a move to the latest and greatest tech, particularly given its impending ubiquity.

And GCs would be well advised that waiting to learn about and invest in AI until they have the ROI calculation figured out is likely not a safe approach. Nearly 8 out of 10 corporate law departments have reported increasing matter volumes, according to our recent data. At the same time, between 60% and 70% report flat to declining budgets and attorney headcount. This confluence of factors will only ramp up the pressure on GCs to figure out how to handle the increasing demand placed on their departments by the broader businesses they serve.

And while AI provides options to help address these volume and capacity challenges, the results of any investment can and should be tracked and reported to show that the business has not just spent money on new technology for its lawyers but has increased its lawyers’ own ability to contribute to the business’s success.

You can find out more about pricing AI-driven legal services here