Can you imagine completing your university studies with the hope of your first tech job, only to discover that an AI has taken your place?
Artificial intelligence (AI) promises to revolutionize the future, but it also redefines the present of work: basic tasks that previously paved the way for recent graduates are now rapidly automated.
In this article we clear the fog of dense figures and technical jargon. You will discover why it is so difficult to get that first place today, what the most recent data reveals and, above all, how you can transform this challenge into a competitive advantage.
The entry-level market under pressure
The first job is the springboard that turns academic knowledge into real experience. However, since 2019 large technology companies reduced their hiring of recent graduates by more than half, going from 15% to 7% of new entrants.
Startups, previously a refuge for young talent, are registering similar declines, exceeding the 50% drop in junior incorporations. This setback creates a dilemma: without experience you don’t get the job, and without the job you don’t get experience.
Automation of routine tasks
AI has become skilled at executing repetitive processes: debugging code, generating documentation or analyzing preliminary data no longer require constant human supervision.
Sectors traditionally resistant to change, such as banking (with firms such as Goldman Sachs and Morgan Stanley), apply intelligent systems to optimize workflows, displacing roles that historically served as a school for new professionals.
Key data that sets the trend
Between 2023 and 2024, large technology companies cut the hiring of new graduates by 25% and startups by 11%, while they increased the hiring of profiles with two to five years of experience by 27% and 14%, respectively. This shift reflects the preference for immediately productive talent over in-house training of rookies.
Macroeconomic perspective
The World Economic Forum notes that 40% of employers plan to delegate routine tasks to AI, directly impacting those seeking their first technical job.
Despite this, the global market for technology jobs in sectors such as health, finance and retail will grow by approximately 20% between 2025 and 2034, suggesting that demand does not disappear, but rather increases. transforms.
The other side of AI: new frontiers
Disruption brings with it unprecedented fields: AI ethicists, language model architects, and data governance analysts.
It is projected that between 20 and 50 million AI jobs will emerge by 2030. These roles require not only technical knowledge, but a deep understanding of legal and social implications.
Skills beyond code
Learning to program is still valuable, but it is no longer enough. Professionals capable of designing, training and supervising intelligent systems are in demand. A study by ResumeTemplates.com reveals that 87% of recruiters consider AI experience essential and that 25% of job offers already explicitly require it.
Strategies for new graduates
Investing in online courses on platforms like Coursera or edX is a first step, but the critical thing is to apply what you have learned: develop personal projects (a basic chatbot, a prediction model) and publish them on GitHub. Showing tangible results is more convincing than thousands of hours of theory.
Practical experience outside of traditional employment
The internships and professional internships are still valuable, but today it is convenient to add contributions to open source projects. Participating in collaborative initiatives allows you to face real challenges, establish contacts and build a solid portfolio.
Explore alternative sectors
The adoption of AI in health, finance, retail and technological agriculture multiplies the entry routes. Identifying emerging niches where competition is less can make all the difference for a recent graduate.
Soft skills development
Effective communication, team collaboration and creative problem solving remain irreplaceable. AI projects require coordination between diverse profiles, so those who master these soft skills are one step ahead.
Illustrative examples and practical lessons
To better understand this scenario, let’s imagine an illustrative case: a recent software engineering graduate loses his traditional internship when the company implements an automatic code generation system.
Instead of giving up, he spends several months training in machine learning and collaborates on a fraud detection project on an open source platform.
Thanks to this initiative, you get an offer in a financial innovation laboratory, with a remuneration significantly higher than the average for new graduates.
Practical lessons for your strategy:
- Document each personal project on GitHub or your digital portfolio to show tangible results.
- Adapt your work examples to the employer’s needs, demonstrating mastery of relevant AI tools.
- Be prepared to discuss ethical aspects and bias in AI, a topic increasingly valued in selection processes.
Reinvent yourself to move forward
Artificial intelligence reconfigures the labor market: it reduces traditional access routes, but opens new routes that require training, resilience and creativity.
As LinkedIn’s Aneesh Raman says, “AI is disrupting entry-level jobs, but it’s creating a new landscape full of possibilities.”
Those who are willing to reinvent themselves, demonstrate tangible projects and cultivate soft skills will find their place in the next generation of tech professionals.
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