Laid off from IT: 5 career paths to pivot to in 2026

Not everyone is being laid off. According to data from Index.dev, 44% of companies cite AI as one of the reasons for restructuring. However, only 9% admit that AI has actually replaced people. More often, it simply reduces the need for new hires.

The situation in Central Asia is similar. In 2024, Kazakhstan's IT market grew by 36.3%, reaching 1.74 trillion tenge, the number of specialists increased to 187,000, and the average salary in the industry rose to 673,000 tenge, reported Astana Hub. At the same time, 509 employers were competing for application developer positions at the beginning of 2026. The market is growing while simultaneously reducing headcount—simply because these are different people with different skills.

Let's examine five areas for retraining in 2026.

Cybersecurity

There are almost no layoffs here. The share of job vacancies requiring information security skills grew from 2% in 2024 to over 4% in 2025. Moreover, employment in the industry is projected to grow by 29% by 2034, as writes Cogent University.

For developers and sysadmins, transitioning here is the easiest: there is no need to learn the domain from scratch; it is sufficient to build security on top of existing skills. Useful skills include cloud security (AWS, GCP, Azure), zero trust architecture, DevSecOps, penetration testing, and knowledge of standards such as ISO 27001 and SOC 2.

Data and Analytics

People who can turn numbers into decisions are always needed—even when budgets are cut. According to data from Robert Half, AI analysts, DevOps engineers, data analysts, and cloud engineers are among the fifteen percent most in-demand roles in the market. Salaries for skills in data analytics and development are growing faster than others.

There is a nuance: the lifespan of a technological skill has shortened to approximately two and a half years, the same study notes, citing Harvard Business Review. Learning once is no longer enough; skills must be continuously updated.

What to learn to enter the field: Python or R, SQL, visualization in Tableau or Power BI, and basic statistics. Bonus points for the ability to work with text, audio, and video as data.

Cloud Engineering and DevOps

Surprisingly, it is the cloud, not AI, that has become the number one area where IT specialists invest their own efforts. According to data from Pluralsight, out of 2.9 million people in their database, the most are learning cloud technologies. Business leaders also name the cloud as the main growth area for 2026.

For entry, knowledge of one provider—AWS, Azure, or GCP—is sufficient, along with Docker, Terraform, Ansible, Python, and Git. Demand for FinOps—cloud cost management—is growing separately, because infrastructure bills are rising faster than budgets, as noted by Cogent University.

AI and ML Engineering

It is important not to confuse two things. One thing is developing AI systems; another is knowing how to use them. The latter is quickly becoming basic literacy for the entire industry, rather than a separate profession.

According to QA's forecast, in 2026, AI products are moving away from simple chatbots toward systems with orchestration and continuous retraining. Prompt engineering—the ability to precisely formulate tasks for neural networks—is becoming as basic a skill as internet search once was.

It is easiest for developers to transition here if they know how to integrate AI models into products and evaluate their quality—not just use ready-made chatbots. LinkedIn already calls AI literacy one of the main hiring requirements in technology.

AI Compliance and Risk Management

This is the newest and most unoccupied of the five areas. Companies are integrating AI into finance, customer service, and supply chains—and they need people who ensure these systems comply with regulatory requirements, do not produce errors, and do not create unnecessary risks. QA calls this one of the main trends of 2026 alongside AI development itself.

This is a niche at the intersection of technology, law, and risk management. It is well-suited for those with experience in testing, product management, or information security—and the willingness to understand how models work and what can go wrong.

What is the result

None of these five areas require starting a career from scratch. A developer can retrain as an AI engineer or a cloud security specialist. A tester can transition into DevSecOps or AI compliance. An analyst can grow into a data engineer.

In 2026, the market pays not for a diploma or for the line "worked in IT" on a resume. It pays for specific specialization built on top of basic skills. And the faster this specialization appears, the faster a new job is found.