The Challenges of Entrepreneurship on Artificial Intelligence in Latin America

The Challenges of Entrepreneurship on Artificial Intelligence in Latin America

This is the second part of the Blog “About Entrepreneurship in Artificial Intelligence in Latin America”, where we talked about the reality of the industry in the region, and what should be the focus of the enterprises that want to succeed.

This part focuses on what the main challenges are, at least from the perspective of the problems that Wholemeaning has faced.

The Reality of the Market

If you are an entrepreneur in Latin America (Latam) understanding the local market is key to differentiate yourself. To achieve this, it’s important to understand whether a company requires solutions based on Artificial Intelligence (AI) or not. It’s common to listen to companies say they have implemented Big Data and AI solutions, but the amount of data they analyze is so small that it could be analyzed by a person in a very short amount of time.

Generally, one of the biggest problems seen in the region is the difficulty to accessing the data: companies’ information is rarely digitized, and it is not in a single repository, so there is no simple and secure way to access it. When the data is not sorted, it is not only difficult to operationalize it, but the cost of doing so is high, which represents a major problem in the effort of consolidating enough information to be able to give the data meaning.

On the other hand, companies often fear losing control over the processes because they see implementations based on Artificial Intelligence as a black box that gives results, but they do not understand the process behind them. Or the other way around, expectations are so high that they collide with reality and this generates some frustration.

That the solution be as simple and uninvasive as possible was key to Wholemeaning, we did not want to depend on how the users have the data, and we wanted to work on commodity tools. For this, we decided to work with email inboxes from Google and Microsoft. To not decentralize the manager our plugin is installed in the email tool (Gmail or Outlook), and is displayed on the right side of the inbox with information on what they must do to better serve their customers. a simpler solution would be impossible. We do not want companies to adapt to us, which is why Wholemeaning is designed to integrate to the Latin American companies. This is something that is repeated in other companies in the region and is a determining factor for success.

Finding talent

Another issue frequently encountered is how to find talent. Generally, it is thought that finding technical talent is very difficult, and often during selection processes one can think that it does not exist, the truth however is that it is difficult to differentiate. This does not mean that the quality is low, but to work in this area a series of very specific skills is needed.

It is very difficult to find talents in this area, not because they do not exist, but because they get lost in a sea of ​​other talents.

What has given us very good results is working with interns during the summer, meeting them and then asking them to work with us (or to come back when they finish their studies). This allows us to get to know them without having to go through selection processes that sometimes require interviewing between 100 to 500 people.

Rounding up …

Latin America has particularities that make it unique, and that is something that local businesses should take advantage of. It is still easy to differentiate oneself as an AI provider compared to international providers. But the market is big and the opportunity is there. We must know how to maintain focus and know how to deal with the various challenges.

For those interested in knowing a bit more about the Artificial Intelligence ventures in Latin America, there is a very interesting study developed by Everis and Endeavor, which demonstrates with data the real scenario of the region.