Numerous studies suggest that Artificial Intelligence (AI) is creating more job opportunities than it is eliminating, while also transforming traditional professions across all sectors. According to experts, the focus should not be on the direction of job opportunities but on the necessary training within our professions to take advantage of the opportunities AI is creating.

Rather than seeing AI as an exclusive threat from Silicon Valley and large tech companies, it is important to recognize its impact on a wide range of sectors. For example, the United Nations Peace Operations Department and the UN Interregional Crime and Justice Research Institute are incorporating AI and Machine Learning experts into their teams.

Despite concerns about the negative impact of AI on the labor market and its potential to develop excessive power, some experts do not see the outlook as so grim. The World Economic Forum noted in a 2020 report that while automation was displacing some jobs, it was also creating new ones. Additionally, Gilbert F. Houngbo, Director-General of the International Labour Organization (ILO), highlighted that technological advances tend to generate more jobs than they eliminate.

According to Janine Berg, an economist at the ILO, AI does not signify the end of work, but rather an opportunity to be more efficient and productive. However, she acknowledges that there are challenges, such as the working conditions of those involved in developing and training AI systems, especially in poorer countries.

Despite the controversies surrounding AI, this technology is already part of our lives, and it is essential to feel comfortable using it in the workplace. There is no need to pursue costly specializations abroad, as Latin America has study centers and training programs that adapt to the demands of the labor market.

In the field of AI, new roles and specializations are being created. Some of these jobs include prompt engineers, AI researchers, experts in natural language processing, robotic process automation specialists, algorithm auditors, and ethics and law specialists related to AI. These roles require a combination of technical and humanistic skills, and the demand for trained professionals in these areas is increasing.

1. Prompt Engineer

Imagine I ask you something, but I don't provide enough information or context about what I need. You’ll likely try to help me, but your response may not be as accurate as if you had more data.

Let’s take this example to the various generative AI models that have become increasingly efficient at understanding natural language, the one you and I use to communicate: the prompt engineer is the person who designs prompts, requests, or premises, and then submits them to an AI tool.

2. AI Researcher

Their role is to identify ways to use AI to overcome problems and limitations within organizations.

They specialize in "understanding large data sets and turning that learning into ideas and plans to develop new AI technologies that data scientists will materialize," says the University of Leeds in the article *What are the Top 5 Jobs in AI?*

An AI researcher should possess what are known as soft skills, which relate to emotional intelligence, critical thinking, resilience, adaptability, among others.

These are key skills, according to the academic institution, because their “role will involve frequent brainstorming to find new methods and approaches.”

3. Expert in Natural Language Processing

This expert is a humanist who masters linguistic models and supports the software development team with language processing, according to the specialist.

Typically, a degree in philology, linguistics, or translation and interpretation is required.

While in-depth technological knowledge is not necessary, specialization in natural language processing or a master’s in computational linguistics enhances the candidate’s profile.

Computational linguistics, an interdisciplinary field that has been around for decades, aims to translate the logic of written and spoken language to machines so that, through model training, they can perform tasks.

This is why behind chatbots, there are not only data scientists and software developers, but also members from other humanistic disciplines such as philosophy and psychology.

4. Robotic Process Automation (RPA) Expert

This role involves managing software systems that automate repetitive and manual tasks in a company.

According to Ibáñez, to train in this field, there are several degree programs in programming, as well as specializations related to RPA.

Companies like Microsoft associate the adoption of RPA by organizations with increases in productivity.

"RPA benefits your business by automating various activities, including data transfer, customer profile updates, data entry, inventory management, and even more complex tasks," they state on their website.

5. Algorithm Auditor

Ibáñez explains that this worker reviews algorithms of systems or applications to ensure they are free of biases that discriminate against people by gender, race, or age.

This role can be filled by someone with a technical background (software developer, computer scientist) or a more humanistic background focused on ethics.

In fact, algorithm auditors must have a practical understanding of how algorithms can affect people.

Therefore, it is important that they work closely with data scientists to regularly review algorithms, ensure they are "transparent, fair, and explainable," and that once released, they maintain impartiality, as noted on the Singularity Experts website.

6. Ethics and Law Specialist with AI Knowledge

"Regardless of where you are in the AI value chain, whether you produce technology, use it, or create content to train it, it is important to have lawyers and ethics specialists who understand AI by your side," says Mathilde Pavis, Associate Professor at the University of Reading’s Law School in England, in an interview with BBC Mundo.

"This will allow you to make sure you’re not doing something that later has to be undone."

As an intellectual property law, ethics, and new technologies specialist, Pavis also advises governments, organizations, and businesses on the impact of AI on managing sensitive data.

She raises some of the main questions AI generates: Do AI systems violate intellectual property rights when trained with information from the internet or social networks? Does this violate privacy rights?