Driving AI Advancement Through Strategy, Data Expertise

Q: How would you describe Brain Food's position within the AI and data consulting ecosystem in Latin America?
A: We specialize in the intersection between business strategy and data technologies, with a decade of experience that has allowed us to anticipate trends in the region and build solid technical capabilities with a practical approach. We are a technical-strategic partner that accompanies the entire cycle, from conceptualization to effective and sustainable implementation.

Q: What differentiates you from other regional or global players?
A: Our main competitive advantage is the combination of a deeply pragmatic approach with a multidisciplinary organizational structure that integrates strategic consultants with experts in Data Science, AI, Machine Learning, Data Engineering and Business Intelligence. Unlike more generalist firms or those focused on a single industry or technology, we work across multiple sectors, allowing us to transfer knowledge. We build solutions in collaboration with client teams, transfer knowledge through direct technical training, and ensure that the value generated remains within the client’s organizations, avoiding unnecessary technology dependencies and enabling true digital transformation.

Q: Which industries have shown the highest adoption of your solutions and how has Brain Food helped them generate transformational change in their operations?
A: We have seen accelerated adoption of our solutions in industries such as retail, mass consumption, financial services, mining, and air transportation. In these sectors, our value has been in developing advanced models for different types of use cases such as demand forecasting, personalized recommendations, and price and inventory optimization. We have also accompanied businesses in the maturation of their data governance strategies, Digital and Data, AI Roadmaps and Strategies, enabling robust operational frameworks that allow scaling use cases of Generative AI and intelligence applied to business.

Q: As part of Artefact, what additional synergies or capabilities have enhanced your value proposition in the Chilean and Latin American market?
A: We have significantly expanded our operational and technological capabilities in the region by incorporating a global network of over 1,700 experts. We also have direct access to methodologies proven in the European Union, Asia, and the United States. The synergy with Artefact allows us to scale multi-regional projects with agility, incorporate specialized multilingual talent, and quickly adapt technological advances to local contexts. We maintain a close and agile structure, with partners and practice leaders directly involved in the projects, ensuring technical depth and contextual focus. This approach allows us to address digital  and data transformation initiatives. For example we just finished a data & AI strategy project in the Financial Services industry for  11 countries simultaneously in almost every continent of the world, with homogeneous standards and coordinated delivery, which would have been unlikely without this alliance.

Q: How do you structure an end-to-end solution from problem detection to full adoption of an AI or advanced analytics-based solution?
A: We approach AI and advanced analytics projects were we mainly face two possible contexts: customers with a vision and desire for the future but not necessarily a clear and concrete  strategic connection of that vision with the new technological and data opportunities and solutions. The second are customers with a specific use case or cases already identified. In the first scenario, our work begins with an in-depth diagnosis of the business and the joint definition of a data or AI strategy, analyzing viable initiatives, building robust business cases, and evaluating the client’s technical feasibility. This process involves roundtables with key stakeholders, prioritization based on expected impact, and a gradual planning aligned with the client's internal capabilities. We interact with companies with great internal capabilities and others that are just starting their journey, and everything in between

In parallel, during development and implementation, we emphasize effective change management, actively integrating users and setting realistic expectations about the scope of the solutions. We accompany the client beyond the technical delivery, performing tests, iterations, and subsequent adjustments in production to ensure full adoption and continuous improvement. Also, key is the evaluation of the quality of the available data and the practical selection of the most appropriate solution, prioritizing the impact on KPIs and critical processes over technological sophistication. Sometimes sophistication is needed, but in other cases a simpler solution may be more appropriate. 

Q: What elements do you consider a priority to ensure data quality and governance from the beginning?
A: In every data project we lead, our priority is to establish a solid framework that ensures the integrity, security, and traceability of the information from the beginning, even if the organization does not yet have a formal governance policy. This involves clearly defining who accesses data, with what permissions, where it is stored, and under what privacy protocols. We always adhere to regulatory frameworks and cybersecurity standards, deploying solutions in our clients' infrastructures to minimize exposure risks. We also work in close coordination with IT and business areas so that each data flow has a clear responsible party, thus reducing vulnerabilities and ensuring the responsible and strategic use of information.

Q: Why should companies focus on having a data strategy in place?
A: Although each company faces different realities in terms of investment, technological maturity or competitiveness, what is certain is that all of them are being pushed — to a greater or lesser extent — to evaluate how to take advantage of the value of their data. The difference today is not in the existence or not of data, but in the speed, diversity, and sophistication with which it can be transformed into actionable decisions. In this context, developing a clear strategy makes it possible to identify gaps, evaluate the return on investment in new technologies, define operating models, and integrate external talent to accelerate the process if necessary.

Q: How does the availability of technical talent impact the ability to scale solutions in the region?
A: The region faces a critical paradox around technical talent in AI and data. On the one hand, the demand for specialized profiles such as data scientists and data engineers has grown faster than the capacity of the educational and professional ecosystem to train them. However, at the same time, the proliferation of low-code and no-code tools allows non-technical profiles to actively participate in automation and analysis processes, which expands the possibilities of technological adoption. This duality requires organizations not only to attract highly skilled technical talent, but also to generate environments where these profiles can scale value through highly complex tasks and not be relegated to operational functions that do not take advantage of their potential.

The ability to scale AI solutions is conditioned by the maturity of technology governance within organizations. We have observed specific cases of companies with multiple active licenses, an excessive production of reports without real use, and a disorderly adoption of tools, which generates unnecessary costs and fragmentation. To maximize the impact of talent and technology, it is essential to establish clear adoption criteria, robust governance models, and a culture of continuous learning that allows us to adapt judiciously to an environment in which everyone, even the most experienced, must remain a lifelong learner.

Q: How is AI adoption expected to advance in the Latin American market over the next few years?
A: There has been a significant evolution in the use of data in Latin America over the past decade, moving from basic reporting efforts to advanced predictive models, automation, and integration with IoT. However, many are focusing on data governance and prompt engineering, essential aspects to maximize the value of Generative AI solutions. Organizations are recognizing that the key is no longer just to access the technology, but to train teams that know how to interact with it strategically and efficiently, especially in contexts with multiple sources of structured and unstructured data.

Although the region is lagging structurally behind more developed markets, it is a mistake to assume that it is at an incipient stage.

Q: What are Brain Food's main expansion priorities for 2025 and 2026?
A: Our priority is to consolidate our position as a benchmark in data and AI consulting in Latin America, with a clear focus on geographic expansion and sector specialization. Mexico is a key market where we already operate with local teams and a consolidated client network, but where we still see high potential for growth. We are also deepening our presence in Colombia and Peru, while strengthening our capabilities in Chile and Brazil. 

We will focus on financial services, retail, mass consumption, transportation, and mining and industrial industries, with customized solutions that respond to the operational and regulatory particularities of each industry. We want to export from the region not only services but also specialized knowledge and highly qualified talent.