Will AI Wipe Out Entry‑level Jobs?

As generative AI proves capable of generating code, summarizing legal documents and drafting marketing copy, many early‑career professionals wonder whether there will be any “entry‑level” jobs left. ISC2’s 2025 survey of cybersecurity professionals captures this anxiety: 52 % believe that AI tools will reduce the need for entry‑level staff, yet 31 % expect AI to create new entry‑level positions. Capgemini’s research finds that employees predict 32 % of entry‑level tasks will be performed by AI within the next year. But rather than a mass elimination of junior roles, the data points toward an evolution in what those roles entail.

From task execution to oversight and orchestration

Generative AI excels at producing first drafts, summarizing information and automating repetitive tasks. For instance, a junior marketing analyst might currently gather data, build a spreadsheet and create a presentation; AI can now automate much of that workflow. However, AI often needs human supervision to contextualize its output, ensure accuracy and adjust messaging for different audiences. Capgemini’s study reports that 6 in 10 managers and 71 % of employees expect entry‑level jobs to shift from “creation” work to reviewing and refining AI outputs.

This shift implies that early‑career professionals will spend less time on rote tasks and more on critical thinking and judgment. Reviewing AI‑generated reports requires domain knowledge and an understanding of organizational context that AI lacks. Moreover, as AI becomes better at generating content, human creativity and nuanced communication become even more valuable. Entry‑level employees who can interpret AI outputs, question anomalies and communicate insights will be indispensable.

The emergence of new roles

AI isn’t just changing existing jobs—it’s creating entirely new categories of work. Capgemini’s study notes that 81 % of leaders and managers expect roles like data curators, AI‑ethics specialists and algorithm trainers to emerge. These positions require a blend of technical and soft skills: understanding AI models, ensuring data quality, enforcing ethical guidelines and communicating findings to stakeholders. For early‑career workers, these roles offer an opportunity to enter the field at the intersection of technology, ethics and business.

Similarly, the boom in prompt engineering (crafting queries to get useful outputs from AI systems) has created new job opportunities. While prompt engineering might sound esoteric, it draws on skills familiar to many entry‑level workers: clear writing, critical thinking and subject‑matter expertise. Companies are already hiring prompt engineers to shape the responses of generative AI tools, suggesting that the next generation of entry‑level roles could involve guiding AI rather than competing with it.

Generational perspectives

Younger workers are optimistic about these opportunities. JumpCloud’s survey shows that 82 % of IT professionals under 34 believe AI will be a net positive for their organization. They also recognize the need to adapt; nearly 46 % worry about AI’s impact on their jobs, suggesting they’re keenly aware of both risks and opportunities. Older workers are less likely to adopt AI tools, nearly 50 % of tech professionals aged 55+ have never used generative AI, but they may bring valuable context and industry knowledge to mentoring roles.

Implications for organizations and talent pipelines

For organizations, the evolving nature of entry‑level work requires a rethinking of recruitment, onboarding and career development:

1. Redesign early roles. Update job descriptions to emphasize critical thinking, collaboration and AI supervision. Recruit for adaptability rather than just specific technical skills.

2. Provide structured training. Offer robust training programs to teach AI literacy, data governance and ethical principles. Many employees view training as the most important factor for AI adoption. By investing in early‑career training, companies build a pipeline of talent ready to navigate AI‑augmented roles.

3. Mentorship and cross‑functional exposure. Pair early‑career employees with mentors who can help them contextualize AI outputs and learn best practices. Encouraging rotations across departments can also help junior staff understand how AI interacts with different business functions.

4. Create new entry‑level roles. Positions focused on prompt engineering, AI ethics and data curation provide a clear pathway for early‑career workers. By framing these roles as entry points, companies can attract diverse talent and ensure that AI adoption is both responsible and inclusive.

AI will undoubtedly reshape entry‑level jobs, but fears of a wipeout are overstated. Routine tasks will be automated, but new responsibilities (reviewing AI outputs, ensuring data integrity, and upholding ethics) will rise in their place. Organizations that proactively redesign entry‑level roles, invest in training and create new pathways for junior employees will not only future‑proof their workforce but also cultivate a new generation of AI‑savvy professionals.