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.

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

Data-related and support jobs are among the first to be automated. Tasks like report creation, ticket routing, or document categorization are now managed by AI agents, chatbots, and Robotic Process Automation (RPA) systems.

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)

In the past, system administrators relied on the manual management of servers, networks, and user configurations, from implementation through the installation of updates and system health monitoring. Now, much of that work has been automated by cloud platforms and AI-based monitoring tools. 

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 like performance tuning and manual backups are being automated. The role isn’t vanishing completely; it’s evolving into Data Platform Engineering and AI-DataOps, where professionals oversee automated systems rather than doing everything manually.

Future-ready DBAs will focus on data strategy, AI-driven analytics, and database security, not just day-to-day 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.

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.

AI-Assisted Software Developer

This is one of the most in-demand roles today. An AI-assisted developer uses tools like GitHub Copilot, ChatGPT, or Tabnine to write, debug, and optimize code efficiently. They know how to use AI in web development to automate UI generation, improve performance, and build better user experiences.

Instead of fearing AI, they use it as a co-pilot, increasing productivity while focusing on creative problem-solving. By 2025, developers who can work alongside AI will find themselves 10 times faster and more employable than those who cannot do so.

Machine Learning Engineer (Applied)

While theoretical ML positions require a solid mathematical foundation, along with a model-building background, applied ML engineers design solutions that embed AI into real-world applications. For example, they might adopt AI-powered chatbots, recommendation systems, or image recognition for a web or mobile application.

This is a hybrid role combining software development, API integration, and model deployment.
Students with skills in Python, TensorFlow, or PyTorch can start in this field, even with a limited research background.

AI Integration Specialist

As more companies adopt pre-built AI APIs from OpenAI, Google Cloud AI, or AWS Bedrock, they need experts who can plug these services into custom apps.
That’s where AI Integration Specialists come in.

These professionals know how to:

• Connect AI APIs with existing databases or backends
• Implement speech, vision, or NLP models into workflows
• Design prompt engineering logic for consistent results

This role blends backend engineering and AI orchestration, making it one of the fastest-emerging jobs in the 2025 IT landscape.

Automation and DevOps Engineer

DevOps is already a critical IT function, and now AI is reshaping it. Modern AI-driven DevOps pipelines use predictive analytics to detect potential outages before they happen. Tools like Harness, DataDog, and Jenkins X with AI plugins automate builds, tests, and deployments.

Automation engineers who understand AI-based monitoring, cloud infrastructure, and CI/CD optimization are in high demand. This position is a good fit for problem solvers and reliability in systems.

Ethical AI and Compliance Analyst

As artificial intelligence is present in nearly every digital offering, companies are increasingly concerned about issues such as data privacy, algorithmic bias, and regulation. This is something that makes Ethical AI Analysts a burgeoning profession.

These analysts ensure their AI tools and processes are compliant with global standards like the General Data Protection Regulation (GDPR), International Organization for Standardization (ISO), or some form of AI governance. Even non-coders can enter this field with skills in policy, ethics, cybersecurity, or data management. It’s a rare combination of tech and ethics, and a career that’s expected to grow rapidly over the next decade.

Genetics and Robotics Engineers

IT and life sciences are creating new roles in health care, such as genetics engineers, who apply complex computing tools to analyze genetic data, create new therapies, and advance innovation. Robots also have their own engineers, who design, construct, and maintain robots in industrial, manufacturing, healthcare, logistics, and more, in any place that utilizes drones, for example. Both engineers are involved in designing these machines to be automated and programmed with AI and intelligent software and hardware systems.

Internet of Things (IoT) Specialists

The emphasis for IoT specialists is on connectivity that provides real-time data collection and analysis from connected devices, sensors, and systems. IoT specialists design secure and scalable solutions enabling smart homes, industrial automation, and connected health. As IoT usage continues to expand, the need for experience in integrating devices, security functions and data analytics capabilities continues to grow.

Automated Testing Tool Developers

With the shift toward continuous integration and delivery, automated testing tools are required for making sure the software quality at scale. Organizations leverage the assistance of Developers and Engineers who design, set up, or manage these tools, allowing organizations to have more rapid and more reliable releases.  Being familiar with frameworks such as Selenium, Testim, and/or proprietary AI-powered testing solutions is a definite asset!

Quick Recap: The Future Workforce

The future isn’t about choosing between humans and AI; it’s about humans who know how to use AI effectively.
The AI impact on software development is creating smarter, faster, and more creative teams.

Software development today is about much more than writing lines of code. It has become more about problem-solving, creativity, and effectively leveraging smart tools. Today’s developer uses AI-powered platforms that speed up the process from idea generation to deployment, managing the entire delivery of projects from start to finish.

Key Transformations Shaping the Future of Development

What once took days to accomplish now takes minutes. Developers can turn their design ideas and user stories into usable prototypes instantaneously using advanced automation and predictive modelling tools.

1. Faster Prototyping:

What once took days to accomplish now takes minutes. Developers can turn their design ideas and user stories into usable prototypes instantaneously using advanced automation and predictive modelling tools.

2. Smarter Debugging:

With context-sensitive modern IDEs, developers are now notified of syntax and logic errors in their code automatically, and receive real-time suggestions and fixes of code performance issues. This improves the developer's concentration on logic improvement instead of chasing bugs.

3. Better Collaboration:

Recent cloud-based tools, in conjunction with smart pairing-programming features, allow multiple developers to collaborate on codebases with other developers seamlessly and in real time, which is a huge departure from the previously fairly isolated and distributed coding environments of the past.

4. Enhanced Performance Optimization:

Automated systems evaluate your code, identify inefficiencies, and provide quick recommendations for optimizations. This means websites and apps will run faster, are able to manage larger payloads, and become increasingly secure.

5. Continuous Learning Environments:

Integrated development environments (IDEs) may not only be interactive teachers, but they may also point out best practices, clarify ideas, and help novices learn while they create.

This shift shows the growing AI impact on software development; developers aren’t being replaced; they’re being empowered to work smarter, faster, and more creatively.

Summary: Software development is evolving into a partnership between logic and intelligent systems. Those who understand how to use AI in web development are not just keeping up, they’re leading the change.

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. In various sectors, organizations are using automation and cloud services to enhance the efficiency and effectiveness of routine tasks, resulting in job losses from manufacturing to administrative roles. As organizations build digital infrastructures, hybrid work will be commonplace and require workers to evolve their roles beyond the boundaries established by 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 2025

By 2025, 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.