Artificial intelligence is no longer a promise of the future. It's in search results, in the emails you receive, in the ads you see, in the content TikTok recommends to you and even in the résumés companies filter.

You don't need a degree in computer science to start working with AI. What you do need is to understand how it works, how it's applied in different contexts and what skills you can train according to your profile.

Why train in artificial intelligence now?

According to data from the Microsoft LATAM 2024 AI Report, 68% of companies in the region already use AI in at least one operational area.
In addition, a study by McKinsey Global highlights that demand for hybrid profiles with AI knowledge grows faster than purely technical ones.
The question isn't whether it will impact your industry, but when.

What can you study if you're interested in AI?

Here's a summary of possible learning paths, with real career outcomes:

1. Data Analysis with AI

You learn to work with databases, create automated reports, and apply simple predictive models to improve decisions.
Career outcomes: data analyst, business analyst, product analyst.
→ See the Data Analysis career at Coderhouse

2. Prompt Engineering and productivity with generative AI

You master tools like ChatGPT, Gemini, Claude or Midjourney, but beyond basic use. You learn how to automate processes, generate content and personalize outputs.
Career outcomes: creative assistant, applied AI specialist, copywriter with AI.
→ See the Artificial Intelligence course at Coderhouse

3. Workflow automation (No Code + AI)

You design and automate repetitive tasks by connecting tools with AI (Zapier, Make, Notion AI, etc).
Career outcomes: operations analyst, process assistant, automation consultant.
→ More about no-code tools and AI

4. UX/UI with a focus on AI-driven products

You understand how to design experiences in products that include machine learning, chatbots, personalization or conversational interfaces.
Career outcomes: UX designer in technology products, CX in platforms with intelligent assistants.
→ See the UX/UI Design career at Coderhouse

What are companies looking for today?

“We're not looking for AI experts. We're looking for people who understand it, use it with judgment, and help us integrate it into our processes”.
— HR Manager at a fintech (Source: internal Coderhouse survey 2024)

According to the LinkedIn Economic Graph report, the most sought-after emerging profiles in 2026 include:

• Specialist in AI applied to content

• Data analyst with knowledge of Python and ML models

• UX designer with a focus on intelligent interfaces

• Automation strategist with No Code tools

And on sites like Glassdoor LATAM and Talent.com, the average salaries of these profiles range between USD 900 and USD 2,500 depending on the country, the role and the level.

How to start if you have no previous experience?

1. Choose a focus: data, content, design, product.

2. Start with a short, practical course, not with dense theory.

3. Put together a portfolio: demonstrations, screenshots, videos of real AI use.

4. Share it on LinkedIn. Document your learning, don't wait to be an expert.

5. Apply for jobs where AI isn't the center, but is an advantage.

→ See examples of portfolios in this Towards Data Science guide

Conclusion

Studying AI isn't just learning technology. It's understanding how to solve real problems with new tools. The market is already asking for these profiles. And the sooner you start, the more of an advantage you'll have.

Explore the artificial intelligence courses and related career tracks at Coderhouse and start building your high-value profile for 2026.

If you'd like to keep exploring this topic, you can also read how to use AI to boost your professional profile.

Recommended Coderhouse courses

If you want to understand and apply artificial intelligence in your work, Coderhouse has programs for all levels:

• Introduction to Artificial Intelligence Course: to understand how AI models work and start applying them from scratch.

• AI Automation Course: to automate workflows with tools like n8n and Make, without needing to code.

• AI Engineering Course: for developers who want to integrate language models into real applications.