Are Gig Workers Counted in India’s Labour Data? A Deep Dive into Policy, Gaps

Why in the News?

The 2025 Union Budget made significant provisions to recognise gig and platform workers by extending them coverage under various social protection schemes. 

• However, the latest Periodic Labour Force Survey (PLFS) 2025, despite including some technical upgrades, failed to explicitly capture gig and platform work within its classification framework. 
• This raises concerns about the statistical invisibility of one of India’s fastest-growing labour segments and the implications this has for policy delivery and economic planning.
• As gig work continues to shape the future of employment in India, questions about its legal recognition, labour protections, and most crucially, its representation in national labour statistics have gained renewed attention.

Background

What is Gig and Platform Work?

The Code on Social Security, 2020, was India’s first legal framework to define and distinguish gig and platform workers:

• Gig Worker (Section 2(35)) – A person who engages in income-generating activities outside of a traditional employer-employee relationship.
• Platform Work – Work enabled by digital platforms that connect service providers with consumers to deliver specific services or solve defined problems.

This includes roles like:

• Food delivery agents (Zomato, Swiggy)
• App-based taxi drivers (Ola, Uber)
• Freelancers on digital platforms (Upwork, Fiverr)
• Logistics workers and online tutors

NITI Aayog’s Projection

In its 2022 report, NITI Aayog estimated that:

• India’s gig workforce would expand from 7.7 million in 2020–21 to 23.5 million by 2029–30,
• Constituting nearly 4% of total livelihoods in India by the end of the decade.

Yet, this growing segment remains poorly captured in official data, undermining evidence-based policymaking.

Features of India’s Labour Data on Gig Work

The PLFS, conducted by the Ministry of Statistics and Programme Implementation (MoSPI), is India’s principal labour force survey. It technically includes gig workers under the general ‘economic activity’, but offers no dedicated classification.

Workers are absorbed into generic categories such as:

• Self-employed
• Own-account worker
• Casual labour

This method misses the specificities of gig work, including:

• Multiple job roles (across different platforms)
• Task-based payments, not time-based wages
• Algorithmic control, not employer supervision
• Absence of a stable or formal contract

Legal Recognition in Policy

Despite definitional ambiguities in data, legal instruments have tried to formalise gig work:

• Chapter XIII of the Code on Social Security mandates the creation of a Social Security Fund for gig and unorganised workers.
• Section 6 of the Code also establishes a National Social Security Board to design welfare schemes.

Further, the e-Shram portal launched by the Ministry of Labour aims to register unorganised workers, including gig workers, and provide them with a Universal Account Number (UAN).

State Welfare Extensions

Some gig workers have been included in:

Challenges

Statistical Invisibility

The biggest challenge is the absence of a distinct classification in PLFS. Without coding, gig work separately:

• Their specific employment vulnerabilities remain hidden.
• Social protections cannot be targeted effectively.
• State and central governments cannot estimate their actual numbers, income volatility, or job mobility.

Misclassification in Surveys

Gig workers are often clubbed with:

• Self-employed: Even though they don’t fully control their work process or pricing.
• Own-account workers: Though they depend on algorithms, are monitored digitally, and often work on-demand, unlike a traditional small trader or shopkeeper.

This flattens the hybrid and digital nature of gig work.

Lack of Specific Survey Instruments

The PLFS does not:

• Ask about platform-based work
• Capture digital dependencies
• Differentiate between single-employer and multi-platform workers
• Record algorithmic control, task-based payments, or surge-pricing models

This leads to an underestimation of the economic and social risk profile of gig workers.

Unstable Employment, Invisible in Data

Most gig work:

• Is part-time or seasonal
• Offers no job security or a written contract
• Lacks grievance redressal mechanisms
• Includes no provision for sick leave, maternity leave, or work-hour limits

PLFS only checks whether a person worked in the last week or year, not how secure, fair, or inclusive that work is.

Dependence on Big Tech Algorithms

Unlike informal workers, gig workers are governed by digital platforms:

• Task allocation, pay, and performance rating are decided by algorithmic systems, not managers.
• Work conditions can change without notice, based on terms of service updates.

These dimensions are unique to the gig economy, yet remain uncaptured in PLFS methodology.

Way Forward

Introduce a Distinct Classification in PLFS

MoSPI should:

• Introduce a new “Digital Labour” or “Platform Work” category
• Add survey modules asking:
  • Whether work is app-based
  • Number of platforms used
  • Nature of control over work (algorithm vs employer vs self)
  • Frequency and volatility of income

This would make gig workers statistically visible.

Create a Gig Work Supplement to PLFS

Similar to how NSSO created:

• Unorganised sector supplements
• Migration surveys

A separate Gig Economy Labour Force Module could be introduced every 3–5 years to:

• Estimate numbers
• Track trends in earnings, hours, and job mobility
• Measure access to benefits and digital infrastructure

Ensure Interoperability with e-Shram and Aadhaar

Gig worker data from:

• e-Shram portal
• UAN-linked platforms
• Digital ID cards

This would allow cross-checking of:

• Beneficiary lists
• Policy reach
• Income records

Strengthen State Labour Boards

State-level boards under the Social Security Code should:

• Register gig and platform workers proactively
• Extend medical, housing, skilling, and accident insurance
• Establish helplines and grievance platforms for platform-related issues (e.g. wrongful deactivation, unfair pay cuts)

Engage Platforms in Reporting

Gig platforms (Zomato, Uber, Urban Company) can be made data partners:

• Report anonymised data on active workers
• Share attrition and churn rates
• Disclose earnings brackets and service areas

This could enable real-time policy monitoring.

Legislate a Gig Workers’ Bill of Rights

Based on global best practices (e.g. California’s Proposition 22, UK Supreme Court ruling in Uber v Aslam), India could:

• Define minimum wages
• Regulate work hours
• Mandate insurance
• Ensure human-led grievance resolution
• Prohibit unilateral termination without recourse

Such legislation would complement data collection by protecting real rights.

Conclusion

Gig work is no longer peripheral; it is central to India’s urban informal economy, particularly for the youth, women, and migrant populations. Recognising it in laws is a start, but without accurate, disaggregated labour data, no real welfare architecture can be built.

The 2025 PLFS missed an opportunity to formally integrate gig work into its classification, despite growing state attention and welfare intent. As India prepares for a future led by digital labour, it must urgently redesign its labour surveys, recognise the hybrid and vulnerable nature of gig work, and provide them with the visibility they deserve in both data and policy.

MAINS PRACTICE QUESTION

Discuss the unique nature of gig and platform-based work in India. Why is it important to create a separate classification for them in national labour surveys like the PLFS?

PRELIMS PRACTICE QUESTION