Jobs at Risk in the AI Era: A 2026–2036 Career Guide for India’s Workforce

Jobs at Risk from AI by 2036: Careers That May Shrink and Skills to Build

By: Javid Amin | September 2026

The next decade will bring major changes to the workplace, but the future is unlikely to be as simple as a list of jobs that disappear and another list that remain untouched.

Artificial intelligence is already changing how businesses handle routine tasks, analyse information and deliver services. The more important career question is what happens to the people performing those tasks — and which skills can help them move into work that requires judgement, adaptability, technical knowledge and human connection.

For Indian students, working professionals and career changers, the most useful strategy is to understand where automation pressure is rising, where human expertise remains valuable, and how to build a career that can adapt through 2036.

Jobs Most Exposed to Automation: What Could Change by 2036?

Automation is most likely to affect work that follows predictable rules, uses structured information and can be completed digitally with limited variation.

That does not mean every worker in these occupations will lose their job. It means the number of people required to perform certain tasks may decline, while the remaining roles become more specialised.

1. Data Entry and Information Processing

Data entry is among the clearest examples of work exposed to automation.

Optical character recognition, document processing software, automated form filling and AI-assisted data extraction can reduce the need for manual transcription.

The US Bureau of Labor Statistics projects a 25.5% decline in employment for data entry keyers between 2024 and 2034. This is a US occupational projection, not an India-specific forecast or a prediction that 95% of all data-entry tasks will disappear.

How workers can adapt

People with data-entry experience can build on their existing knowledge by learning:

• Spreadsheet analysis and data quality management.

• Database fundamentals and SQL.

• Business intelligence tools.

• Document automation.

• Data privacy and verification.

• Administrative coordination and customer support.

The advantage is not simply learning a new software tool. It is moving from entering information to understanding, checking and using it.

2. Telemarketing and Scripted Customer Outreach

Telemarketing is vulnerable where conversations follow standard scripts and the objective is repetitive outbound contact.

AI voice agents, automated calling systems and digital customer-service tools can handle portions of this work. However, complex sales, relationship management and sensitive customer interactions still require different capabilities.

The BLS projects a 21.4% decline in US telemarketer employment between 2024 and 2034. That figure describes the occupation in the United States and should not be treated as a forecast for India’s call-centre workforce.

A better direction for sales professionals

Workers can move toward:

• Consultative selling.

• Account management.

• Customer success.

• Business development.

• Sales analytics.

• Complex negotiations.

These roles still use technology, but they depend more heavily on understanding customer needs and building relationships.

3. Cashiers and Bank Tellers

Retail and banking are changing through digital payments, self-service systems, mobile banking and automated transactions.

The WEF lists cashiers and bank tellers among the fastest-declining job categories in its 2025–2030 employer projections. The US BLS separately projects a 13% decline in teller employment from 2025 to 2035, partly because customers increasingly use online banking and banks need fewer tellers per branch.

Yet a bank teller’s work is not necessarily limited to counting cash. Some employees also handle customer relationships, account services and financial guidance.

Where the opportunity may move

Banking professionals can strengthen their prospects through:

• Financial literacy.

• Digital banking support.

• Fraud detection.

• Compliance.

• Customer relationship management.

• Financial product knowledge.

In retail, customer experience, store operations and technology-enabled supervision may offer more resilience than purely transactional work.

4. Clerical, Payroll and Administrative Roles

Scheduling, filing, routine reporting and payroll processing are increasingly supported by enterprise software and AI-enabled workflows.

The WEF identifies clerical and secretarial workers as among the job categories expected to experience the largest absolute declines through 2030. Its report also identifies accounting, bookkeeping and payroll clerks among the declining roles.

The important distinction is between routine administration and higher-level coordination.

An administrative professional who manages sensitive information, supports executives, coordinates complex projects or handles stakeholders may have a different outlook from someone whose work consists almost entirely of repetitive data processing.

A practical reskilling route

Administrative workers can consider:

• Project coordination.

• Operations management.

• HR systems.

• Compliance administration.

• Business reporting.

• Client communication.

• AI-assisted workflow management.

The future of administration may be less about manually completing every task and more about ensuring that the whole process works correctly.

5. Basic Content Production

AI can produce drafts, summaries, product descriptions and routine marketing material quickly.

That creates pressure on work where the primary value lies in generating predictable text at scale.

But writing itself is not disappearing.

Research, original reporting, subject expertise, editorial judgement, storytelling and brand strategy remain distinct capabilities.

The WEF’s 2025 report includes graphic designers among declining occupations in its employer projections, illustrating that generative AI is also affecting creative work. It does not establish that all writers or designers will lose their jobs.

How content professionals can remain competitive

The strongest transition is from basic production to higher-value work:

• Investigative and explanatory journalism.

• SEO strategy and audience research.

• Editorial planning.

• Brand storytelling.

• Original photography and video.

• Content performance analysis.

• Fact-checking and source verification.

AI may make the first draft faster. A skilled editor still determines whether the finished work is accurate, useful and worth publishing.

6. Manufacturing and Assembly-Line Work

Industrial automation has existed for decades, but robotics, machine vision and connected production systems are expanding the range of tasks that can be automated.

The WEF identifies robotics and autonomous systems as major forces reshaping employment. At the same time, it expects growth in roles connected to technology, infrastructure and the green transition.

The transition does not mean factories will stop employing people.

It can create demand for:

• Industrial maintenance.

• Robotics technicians.

• Automation engineering.

• Quality control.

• Equipment programming.

• Production supervision.

• Industrial cybersecurity.

A factory worker who learns to maintain or operate automated systems may be better positioned than someone whose role is limited to one repetitive manual task.

Are Doctors, Teachers, Electricians and Therapists Truly AI-Proof?

The answer is no — not in the absolute sense.

They are better described as human-centred or comparatively automation-resistant occupations.

The OECD’s 2025 Skills Outlook identifies physicians, nurses, electricians and other green-infrastructure trades as occupations with high interpersonal or manual components, relatively stable task profiles and growing employment prospects. It also notes that healthcare professionals can benefit from technology that improves productivity.

This is a more useful way to understand the future.

AI may change how professionals work without eliminating the need for the profession itself.

Doctors and Surgeons

Healthcare involves diagnosis, treatment, communication, responsibility and physical intervention.

AI can support medical imaging, information retrieval, documentation and clinical decision-making. But medical practice also involves patient preferences, uncertainty, ethical decisions and accountability.

The OECD’s research on AI skills in health occupations describes physicians and nurses as roles where technology can augment human capabilities, while some routine tasks may become automated.

The future doctor will likely need both medical expertise and digital literacy.

Nurses and Care Professionals

Nursing combines clinical knowledge with direct patient care, observation, communication and response to changing circumstances.

The WEF expects nursing professionals and other care occupations to grow through 2030, driven partly by demographic change and increasing demand for care.

Technology may reduce paperwork or assist patient monitoring, but it does not remove the need for skilled people who provide care and respond to patients.

Teachers and Educators

AI tutoring tools, automated assessment and digital learning platforms can support education.

But teaching also involves classroom management, motivation, mentorship, communication with parents and adapting instruction to the needs of individual learners.

The WEF identifies education-related roles, including secondary and higher education teachers, among the job categories expected to generate significant employment growth globally through 2030.

Teachers who learn to use AI effectively may be able to spend more time on instruction, feedback and student support.

Therapists and Social Workers

Mental health and social care involve trust, confidentiality, empathy, cultural understanding and professional responsibility.

Digital tools may support administration, screening or access to services. They do not make human therapeutic relationships unnecessary.

The WEF expects social work and counselling professionals to benefit from rising demand, while the OECD places human interaction and judgement among the capabilities that influence how occupations are affected by AI.

Electricians, Plumbers and Skilled Trades

Hands-on trades are often discussed as safe from AI because they involve unpredictable physical environments.

That is a reasonable distinction, but not a guarantee.

Tools, robotics, sensors and AI-assisted diagnostics can change how tradespeople work. Yet many repair and installation jobs require physical adaptability, local problem-solving and direct responsibility for the completed work.

The OECD specifically identifies electricians and other green-infrastructure trades among occupations with high manual components and growing prospects.

Electricians who learn about solar systems, electric vehicles, smart buildings and energy management may find new opportunities as infrastructure changes.

Lawyers and Creative Directors

Legal professionals and creative leaders also illustrate why job titles alone are not enough to assess AI risk.

AI can assist with legal research, document review and drafting. It can also generate creative concepts, layouts and visual variations.

But advocacy, negotiation, ethical judgement, client relationships, cultural interpretation and final responsibility remain important parts of many roles.

These professions will change, and some specialisations may face significant pressure. They should not be labelled completely irreplaceable.

A Better Comparison: Automation Exposure and Career Resilience

This table is a practical framework, not a statistically ranked forecast. Automation depends on the specific tasks, technology costs, adoption rates, regulations and business decisions involved. The OECD explicitly notes that real-world outcomes depend on these factors.

The 2026–2036 Career Roadmap: How to Prepare for an AI-Driven Workplace

The most effective career transition is usually gradual.

Not everyone can leave a vulnerable job immediately, and not everyone needs to change professions. A practical plan should account for current income, qualifications, family responsibilities and access to training.

Phase 1: Foundation — 2026 to 2028

1. Identify Your Most Exposed Tasks

Review your daily responsibilities.

Which tasks are repetitive? Which require judgement? Which involve customers, colleagues, physical work or specialised knowledge?

This exercise is more useful than simply asking whether your job title is threatened.

2. Learn the Digital Tools Used in Your Field

Start with the technology that is already relevant to your work.

Examples include spreadsheets, AI assistants, enterprise software, data dashboards, digital communication tools and industry-specific systems.

3. Build One Transferable Skill

Choose one skill that can help you move into a higher-value responsibility.

For an administrative worker, it might be data analysis.

For a content writer, it might be editorial strategy.

For a bank employee, it might be financial compliance.

For a technician, it might be automation maintenance.

4. Create Evidence of Your Ability

Build a portfolio, complete a practical project or document an improvement you made at work.

Employers need to see what you can do, not just what courses you have completed.

Phase 2: Expansion — 2029 to 2031

By this stage, the objective is to move beyond basic AI familiarity.

Develop a Specialisation

Choose an area where technology and domain expertise meet.

Examples include:

• Finance and data analytics.

• Healthcare and digital health.

• Law and cybersecurity.

• Marketing and AI-enabled analytics.

• Manufacturing and robotics.

• Education and digital learning.

Seek More Complex Responsibilities

Look for opportunities to manage projects, work with clients, solve operational problems or improve processes.

Build Professional Relationships

Networking, mentorship and collaboration can help you discover opportunities that are not visible through job advertisements alone.

Phase 3: Mastery — 2032 to 2036

The final phase is not about reaching a point where learning stops.

It is about becoming a professional who can guide others through change.

That may involve:

• Leading teams.

• Managing technology-enabled operations.

• Developing strategy.

• Mentoring junior colleagues.

• Specialising in a regulated or complex field.

• Building an independent consultancy or business.

• Combining expertise from two disciplines.

The specific destination will depend on the industry and the individual’s choices. A strategist, senior technician, healthcare professional or experienced educator may all develop career resilience in different ways.

Long-Term Thinking: The Career Skill That Helps You Prepare Before Disruption Arrives

Long-term thinking is valuable because career decisions have consequences beyond the next job opening.

A short-term approach asks:

What skill can help me get hired today?

A long-term approach asks:

What capabilities will help me remain useful as the industry changes?

That does not mean predicting the future perfectly.

It means preparing for more than one possible future.

Strategic Foresight

Strategic foresight involves considering alternative scenarios.

For example:

• What if AI adoption accelerates?

• What if regulations slow adoption?

• What if customers prefer human service?

• What if a new technology changes the business model?

• What skills would remain valuable in each scenario?

Ethical Judgement

AI systems can support decisions, but organisations still need people to consider fairness, privacy, safety and accountability.

This is particularly important in healthcare, finance, law and public services.

Adaptability

The WEF reports that approximately 39% of workers’ existing skill sets are expected to be transformed or become outdated between 2025 and 2030. This highlights why continuous learning matters more than relying on a single qualification for an entire career.

What Indian Workers Should Do Differently

India’s workforce includes graduates, vocational workers, IT professionals, small-business employees, freelancers and millions of people in informal employment.

The impact of AI will not be identical across these groups.

A software engineer may need to learn new development workflows.

A small-business employee may need digital accounting and customer-management skills.

A vocational worker may benefit from training in solar installations or industrial maintenance.

A content professional may need to specialise in research, strategy and multimedia.

The best response is therefore not a single national career prescription.

It is a combination of:

1. Strong foundational education.

2. Practical vocational and professional training.

3. AI literacy.

4. Industry-specific skills.

5. Accessible reskilling opportunities.

6. Human capabilities such as communication and judgement.

The OECD’s 2025 research emphasises that AI can create opportunities as well as displacement, and that education, training and support for affected workers are essential to managing the transition.

Frequently Asked Questions

Will AI eliminate data-entry jobs by 2036?

Data entry is highly exposed to automation, and employment may decline in some markets. However, there is no reliable basis for claiming that all data-entry jobs will disappear worldwide by 2036. Workers can improve their prospects by developing data analysis, verification and workflow-management skills.

Are doctors and teachers safe from AI?

They are relatively resistant to complete automation because their work includes human interaction, professional judgement and responsibilities that technology does not automatically assume. But AI will change how they work, and they will need to adapt.

Should I leave a clerical or cashier job immediately?

Not necessarily. A practical approach is to assess your tasks, learn relevant digital tools, build transferable skills and seek a transition when you have a realistic opportunity.

Is a creative career still worth pursuing?

Yes, but creative professionals should expect AI to change production workflows. Research, originality, creative direction, audience understanding and the ability to use technology effectively can strengthen long-term prospects.

What is the most important skill for the AI era?

There is no single universal winner. Analytical thinking, adaptability, communication, creativity, problem-solving and AI literacy work together to help people remain effective as jobs change.

Final Takeaway: Don’t Predict the End of Work — Prepare for Its Next Version

The future of employment is not a simple contest between humans and machines.

Some routine tasks will become automated. Certain occupations may shrink. New roles will emerge, and existing professions will be redesigned.

The WEF’s research points toward declining clerical and transactional roles alongside growth in technology, healthcare, education and green-transition occupations. The OECD’s analysis reinforces that automation, augmentation and new responsibilities can occur within the same job.

That makes the most useful career strategy clear:

Build expertise in a field, learn to use AI, strengthen your human capabilities and keep preparing for change.

A career does not become resilient because it has a fashionable job title.

It becomes resilient when the person pursuing it can learn new tools, solve difficult problems, communicate clearly and make sound decisions when circumstances change.

The professionals who prepare for that reality will be better positioned for the decade ahead.

Disclaimer

This article is intended for general educational and career guidance purposes. Employment projections, automation estimates and career prospects vary by country, industry, employer, qualification and economic conditions. The forecasts cited from the World Economic Forum, OECD and US Bureau of Labor Statistics should not be interpreted as guarantees of job losses, employment growth or individual career outcomes.

Readers should verify current labour-market information and seek appropriate professional career advice before making major educational or employment decisions. :::