AI is Shrinking Entry-Level Tech Jobs

It’s happening, and it’s happening fast. AI is automating tasks that used to be handled by junior developers, leading to a steep drop in entry-level tech jobs. A 2024 study by the Burning Glass Institute and SHRM found that job postings for entry-level tech roles have declined by over 20% in the past year—largely due to AI taking over routine work.

Big Tech has responded by cutting new graduate hires by up to 25%, favoring experienced professionals who can supervise, refine, and optimize AI tools rather than perform entry-level tasks themselves.

AI is now handling jobs that once helped new coders get their footing, including:
🔹 Basic coding and debugging (GitHub Copilot, Amazon CodeWhisperer)
🔹 Financial and market research (ChatGPT, BloombergGPT)
🔹 Software setup and infrastructure management (Terraform, Ansible)

📌 Example: Microsoft laid off 6,000 employees in early 2024—many of them software engineers—while expanding AI-powered Copilot features across its product suite. This signals a shift in priorities as AI takes over more development tasks.

Experts agree: Entry-level coding jobs aren’t disappearing entirely—but they are evolving significantly.

💡 How Coders Can Stay Ahead of AI

If you want to future-proof your career, the key is adapting and expanding your skillset. Here’s how to stand out:

🚀 Find a Specialized Niche
AI struggles with highly regulated and complex fields. Developers who focus on:
✅ Healthcare tech
✅ Financial compliance systems
✅ Legacy programming (COBOL, Fortran)
✅ Embedded systems in hardware
...will remain in high demand.

💡 Work on Complex Projects
AI excels at routine coding but lacks the judgment needed for high-level development. Engineers who manage:
✅ System architecture design
✅ Multi-platform integrations
✅ Performance optimization
...will be difficult to replace.

🤖 Use AI to Your Advantage
Rather than competing with AI, integrate it into your workflow:
✅ Automate repetitive coding tasks
✅ Speed up debugging and testing
✅ Refactor legacy code efficiently
📌 Example: A developer using GitHub Copilot to generate function templates—but refining and securing them manually—stays in control while working smarter.

📜 Prioritize Documentation
AI-generated code is often messy and hard to follow. Developers who:
✅ Write clear, maintainable code
✅ Add comments and usage examples
✅ Build internal documentation
...will remain essential for long-term projects.

🔧 Expand Beyond Traditional Coding
AI is creating new roles in tech. Skills like:
✅ AI integration for business workflows
✅ Effective prompt engineering
✅ AI model fine-tuning
...will open up fresh opportunities.

🌍 Keep Learning & Stay Informed
AI is evolving quickly. Staying ahead means keeping up with:
✅ AI security and ethics
✅ Human-AI collaboration
✅ Regulatory frameworks (EU AI Act, U.S. Executive Orders)

🧠 Final Thought
The future of coding isn’t just about writing code—it’s about understanding how AI fits into the bigger picture. Developers who embrace AI as a tool rather than a competitor will be the ones who thrive in this new landscape.