The future of work is changing faster than most of us expected. Artificial Intelligence (AI) is no longer just a buzzword—it’s actively reshaping how businesses run, what tasks humans perform, and which roles are on the chopping block. According to Forrester, nearly 70% of repetitive IT tasks will be automated by 2026, and Gartner predicts that by 2025, AI will eliminate millions of entry-level positions across tech.
But here’s the other side of the story: while some roles are disappearing, new opportunities are opening at an unprecedented pace. The real question isn’t whether your job is safe—it’s whether your skills are adaptable enough to stay relevant.
In this article, we’ll explore five tech roles disappearing the fastest because of AI, and then we’ll break down the careers and skills that are rising in demand.
1. DevOps Engineers
DevOps was designed to automate software delivery pipelines, but now AI is automating DevOps itself. That means the very engineers who built automation systems are starting to see their jobs shrink.
AI-powered tools like GitHub Copilot, AWS CodeWhisperer, and Azure DevOps AI Assist can now:
- Write pipeline code automatically.
- Perform real-time log analysis and alert suppression.
- Suggest rollback strategies during failed deployments.
- Auto-remediate deployment errors with minimal human input.
A Forrester study predicts that by 2026, nearly 70% of DevOps tasks will be AI-driven. While DevOps roles won’t vanish overnight, the demand for large teams of engineers will decline. Instead, companies will rely on smaller platform engineering teams who manage AI-augmented deployment systems.
🔑 What this means for you: If you’re in DevOps, focus on platform engineering, cloud-native design, and security-driven automation. These areas require strategic thinking—something AI still can’t replicate.
2. Entry-Level Software Engineers
Traditionally, tech companies hired teams of junior developers to write basic code, fix bugs, and build simple applications. But now, AI is doing much of that heavy lifting.
For example:
- GitHub reports that 46% of code commits on their platform are already AI-assisted.
- OpenAI’s Codex can generate backend systems, APIs, and unit tests directly from natural language prompts.
- Startups that used to hire three junior developers now hire one senior engineer plus AI tools to get the same work done faster.
This doesn’t mean software engineering is dead—it means the entry-level path into the industry is changing. Companies want senior engineers who can oversee AI outputs, improve efficiency, and ensure security.
🔑 What this means for you: If you’re new to software development, focus less on raw coding and more on systems design, problem-solving, and AI tool integration. Learn how to prompt AI effectively and validate its work.
3. Manual QA Testers
In the past, QA testers manually ran regression tests, validated user flows, and logged bugs. That repetitive work is exactly what AI excels at.
Modern AI QA platforms can now:
- Autogenerate test cases.
- Simulate end-to-end user behavior.
- Detect anomalies and log bugs automatically.
Accenture, for example, eliminated over 10,000 manual QA roles after implementing AI-driven test automation.
Instead of manual testers, companies are moving toward QA architects, test automation engineers, and TestOps specialists—roles that design, maintain, and optimize AI-driven QA pipelines.
🔑 What this means for you: Learn automation frameworks like Selenium, Cypress, or Playwright, and pair them with AI testing platforms. You’ll move from repetitive testing into designing systems that test themselves.
4. Tier 1 & Tier 2 IT Support
Think about the last time you contacted IT support—maybe you needed a password reset, VPN configuration, or help with a printer. Those are exactly the kinds of problems AI is now solving instantly.
Companies using Microsoft Copilot and ServiceNow AI report a 60–70% drop in Tier 1 support tickets because AI chatbots and virtual assistants now handle common requests without human intervention.
Instead of large support teams, companies are moving to “zero-touch IT”, where AI agents solve basic issues automatically and escalate only complex problems to humans.
🔑 What this means for you: The future of IT support lies in specialized problem-solving, system integrations, and cybersecurity. Routine troubleshooting is going away, but experts who can handle escalated incidents will remain in demand.
5. Basic Data Analysts
Data is everywhere, but the way we process it is changing fast. Entry-level analysts who spend their time pulling spreadsheets, building dashboards, and generating reports are at risk of being replaced.
AI tools like Tableau GPT, Power BI Copilot, and Google Cloud AutoML can already:
- Pull data from multiple sources.
- Generate clean dashboards automatically.
- Write natural-language insights from raw numbers.
Gartner predicts that by 2026, 75% of “data stories” will be generated by AI without human input.
This doesn’t mean data jobs are disappearing. Instead, the focus is shifting toward data strategy, advanced analytics, and business decision-making—areas where human context and critical thinking still matter.
🔑 What this means for you: If you’re in analytics, shift toward data science, machine learning engineering, or business intelligence strategy. Learn Python, SQL, and cloud data platforms to stay competitive.
Future-Proof Careers AI Can’t Replace (Yet)
While these five roles are shrinking, AI is simultaneously creating new career paths. The most future-proof careers are those that combine technical expertise with strategic thinking, creativity, or human judgment.
Here are some of the AI-proof (or AI-enabled) jobs growing fast:
- Cloud Engineers & Architects – designing and scaling cloud infrastructure for AI applications.
- AI/ML Engineers – building, training, and deploying AI models.
- Cybersecurity Analysts – protecting systems from increasingly AI-driven threats.
- AI Product Managers – combining technical skills with business strategy.
- AI Ethics & Compliance Officers – ensuring companies use AI responsibly.
How to Future-Proof Your Career
If you’re worried about AI taking over your role, here’s what you can do:
- Upskill Continuously – Learn cloud, AI, and automation tools. Certifications like AWS Solutions Architect or Google Cloud Professional Data Engineer are in demand.
- Focus on Strategy, Not Tasks – AI is great at repetitive work, but humans are better at critical thinking, leadership, and innovation.
- Leverage AI, Don’t Fear It – Use AI tools to speed up your workflow instead of avoiding them. The best jobs will go to those who know how to work with AI, not against it.
- Build a Portfolio – Employers now want proof of your hands-on skills. Contribute to open-source projects, create case studies, and document your AI-driven workflows.
Conclusion
AI is not destroying jobs—it’s transforming them. Roles like DevOps engineers, manual QA testers, Tier 1 support agents, junior developers, and basic data analysts are all shrinking, but this doesn’t have to be bad news.
The professionals who survive and thrive will be those who adapt quickly, embrace AI as a partner, and shift into high-value roles that require creativity, judgment, and strategy.
The future belongs to those who can learn fast, adapt to new tools, and use AI as a force multiplier. The question isn’t whether AI will take your job—it’s whether you’ll learn the skills that make you irreplaceable.
