Published: 30 Dec 2025 | Reading Time: 5 min read
Just a few years ago, web developers, testers, and data entry operators were at the heart of every IT company. Today, AI-powered automation tools can perform many of these repetitive tasks faster, smarter, and more accurately than humans.
"AI won't replace you, but someone using AI will."
For students and early professionals, this shift isn't a threat; it's a signal. The IT world isn't shrinking; it's transforming. Understanding how AI in web development is changing helps you focus on the roles that will define the next decade.
According to the World Economic Forum's 2025 report, nearly 23% of existing tech roles are set to transform due to AI and automation. At the same time, new opportunities are emerging in areas where creativity and technology meet, such as cloud automation, ethical computing, and AI-enabled development.
India's tech layoffs in 2024–2025 have largely affected routine, execution-heavy roles, not core engineering talent. Large IT services companies cut staff mostly in areas where repetitive operations were replaced by automation, cloud migration, and AI capabilities.
Companies are not hiring fewer; they are hiring differently.
Companies including Amazon, Microsoft, Intel, and India's own TCS laid off more than 112,000 tech jobs in 2025 as they restructured roles around the adoption of AI and automation-driven processes.
These were once common fresher entry points. Today, recruiters expect tool fluency + problem-solving, even at the entry level.
This shift explains why some roles shrink while others grow.
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.
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.
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.
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.
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.
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 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.
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.
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.
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 Role | Why It's Shrinking | What Students Should Pivot To |
|---|---|---|
| Manual Test Engineer | AI test generation, self-healing scripts, and coverage tools now automate 70–80% of test creation. | SDET / QA Automation (Selenium, Playwright, Cypress, AI testing tools) |
| Basic Front-End Developer | AI UI generators and component libraries reduce pure layout & CRUD work. | Front-end + UX + Performance + Accessibility |
| Data Entry / Support Roles | RPA and AI agents handle structured data and ticket workflows. | Data Analyst / Automation Ops |
| Maintenance-Only Developer | AI code assistants handle bug fixes, refactors, and minor enhancements. | Backend Engineering, System Design, DevOps |
| Traditional System Administrator | Cloud auto-scaling, managed infrastructure, and AI monitoring reduce manual operations. | Cloud Engineer / DevOps / SRE |
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.
| Emerging Role | Why It's Growing | Entry Skills Needed |
|---|---|---|
| AI-Assisted Full-Stack Developer | Over 90% of IT teams now use AI-accelerated coding to ship faster with smaller teams. | MERN or Java, Git/GitHub, Copilot/Replit, basic system design |
| Automation / DevOps Engineer | Cloud + AI reduce manual operations, but increase the need for pipeline and reliability ownership. | Linux basics, CI/CD, AWS/Azure, Docker, monitoring tools |
| AI Integration Engineer | Companies prefer plug-and-play AI APIs over building models from scratch. | APIs, backend logic, Python/JS, prompt engineering |
| Data Platform Engineer (Junior) | AI systems depend on clean, reliable, real-time data pipelines. | SQL, Python, ETL basics, data pipelines |
| SDET / QA Automation Engineer | Testing is shifting from manual scripts to intelligent, automated validation. | Selenium, Playwright/Cypress, API testing, AI test tools |
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.
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.
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.
In each instance, AI improves the significance of human judgment while decreasing repetitive work.
As execution speeds up, businesses want individuals who can:
This is how new IT roles emerge, not by removing people, but by raising the level of responsibility expected from them.
Recruiters increasingly look for candidates who can:
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.
In 2026, recruiters don't expect freshers to know everything, but they do expect them to show applied capability.
Industry-aligned learning helps students:
This directly addresses the gap that leads to confusion around why tech layoffs are happening for some graduates but not others.
Students from non-tier-1 colleges or without internships often lack:
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.
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.
| Skill Area | Why it Matters |
|---|---|
| Prompt Engineering | Knowing how to communicate ideas clearly to automation tools helps you get accurate, useful results faster. |
| Full Stack + Tool Fluency | Developers who combine cutting-edge automation techniques with conventional coding will continue to be in great demand. |
| Data Handling & API Integration | Many modern apps rely on AI APIs, analytics, and data pipelines; knowing how to integrate them is a key skill. |
| Cybersecurity & Ethics | As automation scales, understanding security and ethical coding practices becomes essential for trust and compliance. |
| Continuous Learning | Technologies evolve rapidly. The ability to adapt, self-learn, and apply new skills ensures long-term career growth. |
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.
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.
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.
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.
Focus on three areas:
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.
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.
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.
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.
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).
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.
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.
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.
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."
Tech layoffs are usually attributed to a combination of:
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.
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.