Seven careers in high demand driven by artificial intelligence and how to prepare for them

The growth of artificial intelligence is creating new opportunities for professionals who develop the technology, adapt its applications to business environments, and evaluate its outcomes. Some roles require advanced technical training, while others combine expertise in business, communication, and data analysis.

The World Economic Forum’s Future of Jobs Report 2025 lists artificial intelligence and machine learning specialists among the occupations projected to experience the highest growth by 2030. LinkedIn, meanwhile, identified AI engineer as one of the standout roles in its 2025 global survey of emerging jobs.

Below are seven careers linked to this market and the needs that arise as organizations adopt the technology.

1. Artificial Intelligence Engineer

Develops AI-based applications by integrating models, data, and software to solve specific problems. Examples include virtual assistants, recommendation systems, and automated solutions. The role typically requires expertise in programming, mathematics, and data science.

2. Machine Learning Engineer

Creates and refines models that identify patterns in datasets. The work involves preparing data, testing results, and improving application performance. Proficiency in statistics, programming, and model evaluation is essential.

3. Prompt Engineer

Designs and tests instructions that guide generative AI tools to produce more appropriate responses for specific tasks. This role may involve experimentation, result evaluation, and defining usage standards, and can be integrated into product, content, or technology positions.

4. AI Trainer and Evaluator

Contributes to improving AI tools by classifying responses, identifying errors, and comparing results against established criteria. Depending on the project, proficiency in languages, programming, or specific fields such as law and finance may be required. Many opportunities are offered through temporary or task-based contracts.

5. AI Product Manager

Connects user needs to the development of technological solutions, setting priorities, monitoring tests, and coordinating engineering, design, and business teams. In addition to market knowledge, it is crucial to understand AI’s capabilities and limitations to assess whether a product effectively solves the intended problem.

6. AI Governance and Ethics Specialist

Helps organizations establish rules for the responsible use of AI, assessing risks, documenting decisions, monitoring data protection, and ensuring compliance with standards. Expertise in law, information security, risk management, and technical aspects may be relevant.

7. AI Integration Specialist

Works to incorporate AI solutions into existing company processes and systems, mapping tasks, connecting tools, and overseeing implementation. The role requires an understanding of workflows, problem-solving skills, and, depending on the position, knowledge of programming and system integration.

How to prepare for these careers

The path varies depending on the desired role. Those aiming for engineering roles should focus on programming, mathematics, and data science. For product, integration, and governance roles, business knowledge, project management, and risk assessment skills can complement technical training.

Learning to use AI tools is a good starting point, but practical projects help demonstrate skills. Creating a simple application, documenting an automated process, or evaluating a tool’s results are effective ways to build a portfolio.

Staying updated on job requirements and developing skills aligned with the chosen field is a more consistent way to prepare for market changes.