Which IT Job Roles are Disappearing, and Which Ones are Emerging?

Many traditional IT roles that involved any sort of repetitive coding, manual system testing, and trivial system maintenance are either taking a backseat or disappearing altogether. As AI takes over routine tasks, professionals need to evolve toward more analytical and tool-driven roles.

Manual Testing and QA

A decade ago, manual testing was a major part of software development. Testers manually created test cases, ran scripts, and validated every bug fix.

But with the AI impact on software development, this repetitive workflow is being transformed. AI automated testing tools like Testim, Mabl, and Functionize are capable of generating test cases, anomaly detection, and self-healing scripts on code changes. However, this doesn’t mean the end of testing careers, just a career evolution.

This doesn’t mean testing careers are ending; they’re evolving. Manual testers who learn AI-based automation frameworks and tools like Selenium with AI support can move into higher-value roles such as Automation QA Engineers or Test Architects.

Basic Front-End Development

Earlier, every button, layout, or navigation bar was hand-coded by front-end developers. But AI in web development has made this process smarter and faster.

Tools like V0, Framer, and Uizard can generate complete UI designs and React components from text prompts or wireframes. This means that the demand for purely execution-based front-end work, such as converting Figma designs to HTML, is declining.

However, developers who understand UX logic, accessibility, and component optimization are still essential. In short, AI is removing routine coding, not creative front-end thinking.

Data Entry and Support Roles

Support and data-related occupations are among the first to be automated. These days, AI agents, chatbots, and Robotic Process Automation (RPA) systems handle tasks like creating reports, routing tickets, and classifying documents.

For example, companies use AI-driven CRM systems that auto-fill records, analyze customer sentiment, and generate reports.
As a result, traditional data entry and first-level support roles are declining. But those who upskill in data analytics, automation workflows, or AI operations can move into higher-paying tech support or analyst positions.

Maintenance-Only Software Engineers

In older software companies, engineers worked on code maintenance, such as debugging, patches, and small feature updates. Now we have self-healing systems that are completely AI-based and can detect and correct runtime errors in automated code. Code assistants like GitHub Copilot and Tabnine will actually predict bugs and suggest fixes while optimizing them before they get deployed.

This shows how AI in web development is changing; engineers who rely only on routine maintenance are being replaced by systems that do it faster and more reliably.
Future-ready developers must focus on architecture, automation pipelines, and scalable design instead.

System Administrators (Traditional IT Support)

System administrators used to handle servers, networks, and user setups by hand, from implementation to update installation and system health monitoring. These days, cloud platforms and AI-based monitoring systems have automated a large portion of that job.

Platforms like AWS CloudWatch, Azure Monitor, and Datadog use predictive AI models to detect system failures, optimize performance, and even auto-scale servers based on traffic.

Traditional sysadmins are evolving into Cloud or DevOps Engineers, who design and maintain scalable, automated systems instead of manually troubleshooting them. Those who don’t upskill risk being left behind as infrastructure becomes code-driven and AI-optimized.

Database Administrators (DBAs)

Long ago, DBAs were needed to manage data storage, indices, and backups. Now, database management tools such as Oracle Autonomous Database and Snowflake AI use AI to automatically optimize queries, automatically find anomalies, and repair corrupted files.

Routine DBA tasks such as performance tuning and manual backups are getting automated. The role is not disappearing completely; it is transitioning into Data Platform Engineering and AI, DataOps, where specialists monitor automated systems instead of doing everything manually. Next, gen DBAs will be concentrating on data strategy, AI-driven analytics, and database security, besides the routine of maintenance.

Bottom Line:

AI is not eliminating the need for tech jobs; it is eliminating repetitive tasks.

Jobs focused on manual tasks, maintenance, or repetitively doing things are going away, while jobs that involve AI-related work, analytics, and creativity are increasing.

IT Roles Declining Fastest for Freshers (With Pivot Paths)

These roles are shrinking not because the tech job market is vanishing, but because AI and automation have raised the minimum value expected from freshers. Understanding where demand is moving helps students pivot early instead of reacting late.

Declining Roles & Smart Pivot Paths

As automation replaces traditional jobs, it is also sparking a new generation of tech jobs that will employ coding, creativity, and big-picture fluency with AI. Developers who can learn to leverage AI instead of fighting its advancements are the ones who will lead the future of software development.

Key Insight

Freshers are still in demand, but only in the tech job market that combines coding, tools, and problem ownership. Learning where demand is moving is more important than chasing old entry roles.

As automation and AI reshape the IT landscape, the ability to adapt—through reskilling and upskilling—has become essential for continued career growth. Successful workforce transitions require more than just learning new tools; they demand a shift in mindset, continuous learning, and support from both organizations and policymakers.

Why Retraining and Upskilling Matter

The scale of workforce transition is significant. By 2030, "between 75 million and 375 million might have to change into different jobs and learn new skills" as a result of automation and artificial intelligence, according to McKinsey. Without proactive adaptation, workers risk unemployment or stagnating wages as old roles disappear.  

Strategies for Successful Transition

• Midcareer Retraining: In-demand skills like automation, cloud computing, and AI integration should be the focus of organized programs for professionals in at-risk positions.
• On-the-Job Training: Employers can play a vital role by offering internal training, mentorship, and project rotations to help employees move into new roles.
• Continuous Learning: Lifelong learning, through online courses, certifications, and hands-on projects, ensures ongoing relevance as technologies evolve.
• Labor Mobility and Talent Platforms: Digital platforms can help match workers to new opportunities and facilitate smoother transitions between roles or even industries.
• Support Systems: The financial and psychological burden of changing occupations can be lessened with access to income support, transition help, and transferable benefits.

The Role of Organizations and Policymakers

• Business Initiatives: Employers should make investments in workforce development as part of their social obligation, as well as to close skill gaps.
• Policy Support: Governments may facilitate the changes through such means as unemployment insurance, publicly funded retraining programs, and grants intended for lifelong learning.

Key Takeaway

Workforce transition is not just an individual challenge but a collective effort. By embracing retraining and upskilling, IT professionals can turn disruption into opportunity and build future-proof careers.

AI is not eliminating work in the tech job market. It is changing who does what. Human effort is now directed into decision-making, validation, and system ownership as tasks that were previously performed manually are either automated or aided.

What This Looks Like in Real Teams

• Every line of code is no longer written by a developer. Rather, they examine, enhance, and incorporate code produced by AI into current systems.
• A tester focuses on designing test strategies and edge cases, while AI tools execute and maintain test scripts.
• A cloud engineer defines architecture rules and policies, while automated systems handle scaling, monitoring, and alerts.

In each instance, AI improves the significance of human judgment while decreasing repetitive work.

Why This Creates New Roles

As execution speeds up, businesses want individuals who can:

• Understand how systems work end-to-end
• Decide when AI output is correct or risky
• Take responsibility for outcomes, not just tasks

This is how new IT roles emerge, not by removing people, but by raising the level of responsibility expected from them.

What Recruiters Value Now

Recruiters increasingly look for candidates who can:

• Explain why a solution works
• Use tools thoughtfully, not blindly
• Think beyond syntax and understand workflow and impact

Bottom Line

AI doesn’t reduce responsibility; it moves it upward. New roles appear where thinking, oversight, and ownership are required.

One trend is clear in Indian recruiting teams when new IT positions arise: students who just take theory-heavy courses or sporadic tutorials find it difficult to translate their talents into employment.

This shift explains part of why tech companies are laying off certain entry-level roles, not because of a lack of talent, but due to a skills mismatch. Companies now expect freshers to contribute faster, with less hand-holding.

To move into emerging roles, students need structured, project-based learning, not random learning paths.

What “Job-Ready” Preparation Actually Means Today

In 2026, recruiters don’t expect freshers to know everything, but they do expect them to show applied capability.

Industry-aligned learning helps students:

• Build real projects using AI tools instead of toy examples
• Understand complete workflows (design → build → test → deploy)
• Learn how to use AI responsibly, not blindly
• Prepare for interviews that test decision-making and reasoning, not memorization

This directly addresses the gap that leads to confusion around why tech layoffs are happening for some graduates but not others.

Why Structured Programs Matter (Especially in India)

Students from non-tier-1 colleges or without internships often lack:

• Exposure to real-world constraints
• Experience with production-level tools
• Feedback on how the industry actually evaluates skills

By following market expectations early on, structured academies that focus on full-stack programming, cloud basics, and AI-assisted processes can close this gap.

This isn’t about certificates, it’s about reducing the distance between learning and employability.

What Skills Will Keep You Future-Ready?

The future belongs to developers who can combine solid programming skills with adaptability and critical thinking. As tools evolve, your mindset and ability to learn quickly will define your success.

Why Students Should Care

Regardless of whether you are a student, a recent graduate, or an early professional, it's important to know how automation is impacting the world of IT. Recruiters are looking for people who can demonstrate skills, not just theories, anymore.

If you can showcase a project built using modern web tools, for example, automating layout generation, integrating APIs, and optimizing site performance, you’re already proving that you know how to use AI in web development effectively.

A Practical Insight for Learners

The developers of tomorrow won’t just code; they’ll guide smart systems, solve real problems, and think strategically. Learning to use the appropriate tools as early as possible can elevate your future job interview and project showcase efforts.

Despite IT taking the lead in automation and digital transformation, similar processes are underway that are transforming the whole labor market. Automation and cloud services are being used by businesses across industries to improve the efficacy and efficiency of everyday processes, which is leading to job losses from manufacturing to administrative positions. Hybrid employment will become the norm as businesses develop digital infrastructures, necessitating that employees expand their responsibilities beyond what is specified in job descriptions.

With the increase of gig economy platforms and remote work, there are more flexible employment opportunities, but this has also contributed to the insecurity of employment and the absence of benefits. The marketization of unpaid work, including childcare, eldercare, and household service, has created new types of formal jobs, especially since the participation of women in the workforce has increased globally.

Demographic changes, like the ageing population in developed countries, are altering the types of services in demand and stressing public systems. At the same time, operational shifts driven by technology are prompting organizations to seek productivity growth through automation, rather than simply expanding their workforce.

To address the risks of labor displacement, policymakers are exploring solutions like minimum-wage policies, portable benefits, and even a universal basic income. These efforts seek to help workers adjust to transitions and to ensure that the benefits of automation and digital transformation are spread out. Adaptability, ongoing learning and being comfortable with hybrid occupations will be essential for all workers, not only those in IT, as the labor market changes.

The field of software development is rapidly evolving. Traditional, manual work-based roles are beginning to decline as automation-related and creativity-based roles are on the rise. The future of development is not about doing away with developers, but about redefining their role within the development process through new workflows and better collaboration in teams.

Why it Matters in 2026

By 2026, every successful developer will need to understand how AI is changing software development, not just to stay relevant, but to stay employable. The ability to work with intelligent tools, manage data-driven systems, and build adaptive web applications will separate strong candidates from the rest.

Start small. Explore AI in web development by using tools that help with layout design, bug fixing, or testing automation. The more you experiment now, the better prepared you’ll be when these technologies become standard in every IT team.

Key Takeaways

• As traditional, manual repetitive IT-based jobs decline, the need for modifying original work and role-based IT-related jobs continues to expand.
• Learn how to apply your use of automation and AI in a development cycle, in order to improve and increase your creativity and productivity.
• The real benefit of automation and AI in software development is in collaboration, not replacement.
• The future is about continuous learning and reviewing your possibilities to remain relevant in the world of technology.
• Early upskilling helps you stand out and stay future-ready in an automation-first industry.

1. Are coding jobs disappearing because of automation?

No, most coding jobs aren’t vanishing, but the nature of the work is changing. Many basic or repetitive programming tasks are being handled by automation tools, so developers now focus more on problem-solving, architecture, and tool integration. 

2. What skills should freshers learn if they want to stay employable?

Focus on three areas:

• Strong fundamentals in HTML/CSS/JavaScript and core software logic
• Ability to work with modern development tools, frameworks, and integrations
• Soft skills like communication, adaptability, and continuous learning are essential, as tech roles evolve quickly.

3. How is AI in web development changing front-end or full-stack roles?

Web development is shifting from hand-coding every layout to using smart tools that generate UI elements, handle testing, and add dynamic behaviour. This means developers now manage how things get built rather than writing every piece manually. 

4. Will emerging roles like DevOps and Cloud Architect replace coding roles?

Not replace, but complement and elevate them. DevOps, Cloud Architects, Automation Engineers and similar roles require coding skills plus workflow, system design and automation knowledge. This mix is becoming more valuable than traditional “just write code” roles.

5. How should I approach career planning given the fast changes in job roles?

Think of your career as evolving, not fixed. Start with a solid foundation, then pick one or two “modern” specialities (automation tools, cloud, data integration) and keep learning. Build a portfolio showing you can adapt, not just code.

6. Did Amazon lay off tech workers?

Yes. As part of higher cost and efficiency efforts, Amazon reportedly slashed over 14,000 people in 2025, which had a big impact on corporate and tech functions. Meanwhile, the business reinvested in areas like artificial intelligence. Up to 30,000 business employment might be eliminated in late 2025, according to larger projections.

7. Why are tech companies laying off workers?

A number of causes, including economic instability, automation, the adoption of AI, overhiring during epidemic expansion, and the need to cut expenses, have contributed to tech layoffs in recent years. Many companies are reducing positions associated with conventional, repetitive work and reorganizing teams to concentrate on high-growth areas (including cloud, AI, and automation).

8. Are tech layoffs still happening?

Yes. In many tech businesses throughout the world, layoffs will continue until 2025-2026. Over 200,000 individuals have been impacted so far this year by hundreds of IT companies cutting staff, according to independent trackers. Layoffs are still a part of a larger workforce restructuring rather than a singular occurrence, even though the pace may change over time.

9. Did Microsoft lay off employees?

Yes. Microsoft has announced many rounds of layoffs in 2025, including 6,000 in May and 9,000 more in July, affecting various divisions as part of the company's reorganization and efficiency measures.

10. Does Tech Mahindra lay off employees?

There isn’t widely reported data showing a major formal layoff announcement from Tech Mahindra in 2025 specifically. However, the Indian IT sector overall has seen job cuts, attrition, and “silent layoffs” as firms restructure for AI, cloud, and automation work, which may affect staffing indirectly. 

11. Is AI causing tech layoffs?

AI is one of the key contributing factors to layoffs, but it is rarely the sole cause. Companies often cite AI adoption alongside cost-cutting, efficiency drives, automation of routine tasks, and changing skill demands as reasons for workforce reductions. In many cases, AI is part of strategic realignment rather than direct “replacement.” 

12. What is the reason behind tech layoffs?

Tech layoffs are usually attributed to a combination of:

• Economic pressures and slowing growth
• Over-hiring during pandemic and early-growth periods
• Automation and AI are reducing reliance on repetitive roles
• Restructuring to focus on future-oriented skill areas
• Cost-reduction and operational efficiency goals

Many tech companies are reorganising their workforce toward roles requiring higher-order technical skills (cloud, AI integration, DevOps, automation), which can lead to cuts in legacy or less strategic positions. 

13. What determines how fast automation impacts IT job roles?

The speed of change depends on labor-market dynamics, wage levels, and how quickly organizations and workers adapt. Regulatory and social acceptance also play a role in how rapidly automation technologies are adopted and reshape IT job demand.