What jobs will grow thanks to artificial intelligence?

For years, the debate around artificial intelligence has had a single focal point: the jobs that will disappear.
A new reading of data from the Bureau of Labor Statistics, however, partially overturns this perspective.
In the years leading up to 2033, AI will not only act as a force of substitution: in many sectors it will function as a demand accelerator, increasing the need for professionals capable of building, governing, and interpreting increasingly complex systems.

AI doesn’t only eliminate jobs: it often creates new demand

For years, public debate on artificial intelligence has revolved around a single axis: the jobs that will disappear. The focus has been almost obsessive on negative effects, automation risks, layoffs, and professions potentially becoming obsolete.

This narrative, however, is partially misleading. A closer reading of projections from the Bureau of Labor Statistics (BLS), published in the Monthly Labor Review under the title “Incorporating AI impacts in BLS employment projections: occupational case studies,” shows a more nuanced picture.
Artificial intelligence will not act only as a substitute for human labor, but also as a powerful accelerator of opportunity, especially in sectors where technology lowers costs and expands total demand.

The key point is simple: when AI makes certain activities faster and cheaper, it does not always reduce overall work. More often, it shifts it, specializes it, and expands it. This emerges clearly from the BLS analysis, which connects the impact of AI with U.S. employment projections through 2033.

Software developers: +17.9%

The most evident category is software developers, projected by the BLS to grow by 17.9% through 2033.
This may seem paradoxical in an era where generative models can write code, fix errors, and propose solutions in seconds.

Yet it is precisely this acceleration that creates more demand.
If development becomes cheaper and faster, software becomes accessible to more companies, more industries, and more use cases. New products, applications, and digital services emerge. In this way, total software demand grows faster than the reduction in time required to produce it.

In addition, people are needed to design, test, integrate, and maintain AI systems themselves. AI never becomes autonomous enough to eliminate engineers; instead, it requires engineers with more advanced skills, capable of building architectures, managing data, ensuring security, and handling integration with existing systems.

Personal financial advisors: +17.1%

Another group expected to grow is personal financial advisors, projected at +17.1%. Here the driver is less technological and more human.

Robo-advisors can automate part of decision-making, but they do not replace trust, relationships, or the ability to interpret a client’s goals, fears, and constraints. Personal finance—especially for affluent households, retirees, and individuals with complex assets or objectives—remains an area where experienced, identifiable guidance is perceived as necessary.

Studies show that older clients and those with higher wealth tend to distrust purely automated financial decisions.
They seek empathy, stability, and accountability: qualities a human expert can provide, but an algorithm cannot.

Database architects and administrators: +10.8% / +8.2%

Among the most AI-favored professions are also database architects (+10.8%) and database administrators (+8.2%).

This growth is consistent with AI adoption.
Generative systems only work if they are powered by high-quality data, solid infrastructure, and well-governed architectures. In theory, AI promises simplicity; in practice, companies continue to struggle with fragmented systems, inconsistent data, and outdated infrastructure.

The more AI enters business processes, the greater the need for those who make those processes reliable.
Hence growing demand for technical profiles capable of integrating platforms, managing data pipelines, ensuring quality, and preventing system errors.

This is crucial because it shifts the center of gravity of innovation. It is not enough to “use” AI: it is necessary to build the environment in which AI can actually function.

Financial and investment analysts: +9.5%

Financial and investment analysts are also among the professions with strong growth potential, at +9.5%.

AI excels at rapid computation and analyzing large volumes of data.
But long-term investment decisions require more: macroeconomic context, understanding political risk, evaluation of market relationships, and the ability to take responsibility.

In other words, machines help us see faster, but humans still decide better when the picture is ambiguous.
Institutional investment decisions are not just numbers: they are estimates, scenarios, interpretations, and responsibility.

Electrical and electronics engineers: +9.1%

On the industrial side, electrical and electronics engineers are expected to grow by 9.1%.

Here the driver is not purely digital: electrification, grid modernization, expansion of data centers, and the growth of the electric vehicle ecosystem all matter.

AI can support design and optimization, but it does not replace the physical implementation of complex systems, nor the technical responsibility that accompanies major infrastructure.

Structural growth in these sectors is expected to last for decades, with AI acting as a support rather than a substitute.

Civil and aerospace engineers: up to +7.9%

The same logic applies to civil and aerospace engineers, projected by the BLS to grow up to +7.9%.

Here the decisive factor is regulatory: public safety, standards, and professional certification require human oversight.
AI can accelerate simulations, drafts, and calculations, but it cannot assume final responsibility for projects that must hold up technically, legally, and socially.

In fields such as construction, infrastructure, and aerospace, the law requires a qualified engineer to review and sign off on every project.

AI can speed up calculations, but legal accountability and final quality control remain firmly human responsibilities.

What makes a job resilient to AI

The real dividing line in the AI era is not between those who use technology and those who do not. It is between those who perform standardized tasks and those who work under ambiguity, context, and responsibility.

The most resilient and growing professions share three core features:

• Human interaction and advisory work: tasks requiring empathy, negotiation, and understanding of personal nuance (such as financial advising).

• Regulatory and safety requirements: professions where law requires human supervision to ensure quality and public safety (such as engineering and law).

• AI implementation itself: professionals needed to navigate integration challenges and maintain digital ecosystems.

AI can generate drafts, summaries, or preliminary analyses, but it does not understand the deeper meaning of an objective, does not independently grasp ethical nuances, and does not always recognize its own mistakes.
This is where human professionals come in: as guarantors of correctness, coherence, and the real intention behind each output.

The director of technology

The message emerging from the BLS is less bleak than often portrayed. AI does not only produce substitution; it also produces specialization, productivity, and new demand for skills.

The fastest-growing jobs will be those that operate at the boundary between machine and reality: interpreting data, governing systems, taking responsibility, and maintaining control when automation becomes too opaque to stand on its own.

For this reason, in the new AI economy, the most important figure will not necessarily be the pure technician nor the traditional manager.
It will be the one who acts as a director: the person who translates computational power into decisions that are useful, safe, and understandable in the real world.