The notification chimed on my phone: “Order received – Rs. 20 for 3.2 km delivery.” I looked at the address, started my bike, and began what would become a two-month journey into India’s platform economy. By the time I delivered that first order—a 20-minute hunt through narrow lanes to find a customer’s house in the dark—I had earned my first Rs. 20 as a gig worker. More importantly, I had begun to understand the vast gap between the gig economy’s promises and realities.

The app does not just facilitate work—it monitors, evaluates, and controls every aspect of it. Location tracking runs continuously, monitoring speed, route efficiency, and idle time.

This wasn’t planned research. In September 2024, while studying rural employment programmes in Maharashtra, I kept encountering young migrants who moonlighted as delivery workers.  As NITI Aayog projected India’s gig workforce would triple to 23.5 million workers by 2029-30, I realised that understanding this growth required more than interviews and surveys. It required experiencing the algorithm’s control first-hand.

Entering the Algorithm

Becoming a delivery partner proved deceptively simple. After downloading the app and providing basic details (phone number, bank information, and Aadhaar card), I encountered the first revealing requirement—Rs. 400 sign-up fee plus Rs. 2,000 for branded clothing and delivery bag, deductible from future earnings. The platform extracted payment before I had earned a single rupee.

What the platform did not require was equally telling. No driving licence verification, no helmet confirmation, and no safety training for work involving constant road navigation. I was registering not as an employee but as an “independent contractor” using “aggregator services”—legal language that shielded the company from employment obligations while maintaining operational control.

The training videos, available in multiple Indian languages, covered app navigation thoroughly but offered little about worker rights, transparency about earnings or dispute resolution. I could skip entire sections—a design prioritising quick onboarding over worker preparation. Within hours, I was approved to start deliveries, though insurance coverage would only activate after two successful orders.

Algorithms Become Bosses

Working for a platform means surrendering to digital management in ways traditional employment rarely demands. The app does not just facilitate work—it monitors, evaluates, and controls every aspect of it. Location tracking runs continuously, monitoring speed, route efficiency, and idle time. Push notifications arrive constantly, pressuring workers to stay online during peak hours or accept additional orders.

The incentive structure reveals sophisticated behavioural control. Daily and weekly bonuses appear achievable but require completing lengthy shifts—often six to 10 hours—and maintaining high acceptance rates. Rejecting more than three orders during a shift triggers penalties, forcing workers to accept unprofitable deliveries. When I set my maximum delivery distance to 4 kilometres, the system still assigned me an 8-km order I felt compelled to accept.

Earning calculations remain deliberately opaque. Workers cannot see customer locations before accepting orders, making informed decisions impossible. This control extends beyond work hours. The platform’s internal marketplace encourages workers to spend earnings on company-branded merchandise, phone accessories, and investment products. Frequent notifications about discounts pressure workers to convert labour into platform-specific consumption, tightening economic dependence.

True Cost of Every Delivery

During my shifts, I met Vishal, a 34-year-old delivery partner who had moved to Nagpur from a small town in Vidharbha three years earlier seeking better employment opportunities. After struggling to find stable work, he turned to food delivery 18 months ago. Our conversation during restaurant waits revealed the hidden economics that platforms never discuss.

When delivery deadlines grew tight, the temptation to cut corners increased. “I’ve paid Rs. 2,000 in signal-jumping fines this year,” Vishal admitted.

“My phone plan costs Rs. 400 monthly for 2GB daily data,” Vishal explained. “But during peak hours, especially when I work 10-12 hour days, I need top-ups. The GPS and constant app usage drain data faster than you’d think.” His total monthly mobile expenses, including extra data packages, averaged Rs. 600. Six months earlier, he had replaced his smartphone after the old one developed lag issues that cost him orders. The Rs. 14,000 replacement, bought on EMI, still consumed Rs. 1,200 monthly from his income.

Vehicle maintenance proved costlier than expected. Puncture repairs were necessary roughly once monthly due to Nagpur’s uneven roads and construction debris, costing Rs. 50 each time. Regular bike servicing, chain adjustments, brake repairs, and minor fixes averaged Rs. 800 monthly. “I carry a power bank that cost me Rs. 1,500,” he said, patting his delivery bag. “My phone battery dies twice daily from constant GPS tracking and customer calls.”

The fuel mathematics was stark. With petrol at Rs. 103 per litre in Nagpur, Vishal’s bike consumed approximately 1.8 litres daily, covering 60-70 km across lunch and dinner shifts. His monthly fuel bill reached Rs. 5,100—over a third of his gross earnings. “City traffic forces you to idle at signals and in jams, which kills mileage,” he observed.

Traffic violations represented an unpredictable expense. When delivery deadlines grew tight, the temptation to cut corners increased. “I’ve paid Rs. 2,000 in signal-jumping fines this year,” Vishal admitted. “The app doesn’t consider real traffic conditions when setting delivery times.”

Despite racing through traffic, navigating confusing apartment complexes, and ensuring orders reached customers hot and fresh, Vishal rarely received additional compensation. “There’s no tip culture here like in other big cities,” he explained. “I make sure food reaches customers within the promised time, sometimes risking my safety to avoid delays, but customers just take their order and close the door. I don’t even remember when I last received a tip—maybe twice in the past 18 months, and both were just Rs. 10-20.” The app’s tipping feature, while available, remained largely unused by Nagpur customers accustomed to fixed pricing.

The platform extracted additional costs through mandatory expenses. The branded delivery bag cost Rs. 2,000 (deducted from earnings), and replacement after wear required personal expenditure. The company t-shirt, while provided, required constant maintenance. “My wife washes my uniform twice a week because it gets dirty and sweaty from riding in traffic and heat,” Vishal said. “She spends extra time and money on detergent, but platforms never count this household labour.” The frequent washing meant buying replacement shirts every few months as the fabric wore out quickly.

“People see the delivery charge and think we’re getting rich,” Vishal concluded.. “They don’t see what it actually costs to keep this bike running, my phone charged, and myself healthy enough to work tomorrow.”

When we calculated his monthly expenses—fuel (Rs. 5,100), maintenance (Rs. 800), mobile costs (Rs. 600), phone EMI (Rs. 1,200), punctures (Rs. 50), and fines (Rs. 170 average)—they totalled Rs. 7,920. From his gross monthly earnings of Rs. 14,000, this left Rs. 6,080 as actual income, or roughly Rs. 200 per day for 10-hour shifts.

The long-term health costs remained uncounted. After 18 months of delivery work, Vishal experienced persistent back pain from prolonged riding and poor bike ergonomics. “My back hurts every evening, but I can’t afford to take breaks or see a doctor regularly,” he said. “This work is aging my body faster than it should.” The platform provided basic accident insurance but nothing for occupational health issues that develop gradually.

“People see the delivery charge and think we’re getting rich,” Vishal concluded with a wry smile. “They don’t see what it actually costs to keep this bike running, my phone charged, and myself healthy enough to work tomorrow.”

Encounters on the Street

My interactions with customers, restaurant staff, and fellow workers revealed the social dynamics underlying platform capitalism’s facade of seamless service. Customers tracking their orders in real time often grew frustrated when deliveries were delayed due to traffic, unclear addresses, or slow restaurant preparation. The app’s promise of precision—“delivered in 30 minutes”—created unrealistic expectations that workers ultimately managed.

“There’s no respect in this job. My wife tells me to change into the company t-shirt midway, not wear it from home. People don’t talk nicely and sometimes create issues about payment.”

Restaurant experiences varied dramatically. Established outlets treated delivery workers professionally, maintaining separate pick-up counters, and providing wait-time estimates. However, the growing ecosystem of “ghost kitchens”—unmarked food operations within residential buildings—presented unique challenges. These businesses, optimised for app-based ordering, often lacked proper signage, or dedicated pick-up areas. I spent considerable time navigating narrow residential lanes searching for kitchen operations hidden within apartment complexes, guided only by vague app directions.

Conversations with other delivery workers, typically during restaurant waits or traffic stops, revealed shared frustrations across platforms. A 32-year-old partner working for a competing service captured a common sentiment: “There’s no respect in this job. My wife tells me to change into the company t-shirt midway, not wear it when leaving home. People don’t talk nicely and sometimes create issues about payment.”

Promise and Reality

India’s policy response to gig work reveals the tension between recognising worker needs and maintaining platform flexibility. Rajasthan became the first state to pass comprehensive gig worker legislation in July 2023, establishing a welfare board and mandating 1-2% transaction fees from platforms to fund social security. The law requires platforms to register workers and provide transparent data about earnings and commissions—information companies have historically guarded closely.

Recent developments suggest broader policy momentum. In the budget for 2025, the union government announced health insurance coverage for gig workers through the PM-JAY scheme, with 10 million workers expected to benefit immediately. A pilot programme launched in September 2024 registered four major platforms—Urban Company, Zomato, Blinkit, and Uncle Delivery—on the e-Shram portal, preparing the infrastructure for nationwide social security coverage.

However, implementation remains challenging. The central government’s Code on Social Security, 2020 recognises gig workers as a separate category but lacks finalised rules across most states. While Rajasthan’s law is progressive, it does not classify gig workers as employees or integrate existing labour protections. Karnataka has introduced a similar draft bill in 2024, but enforcement mechanisms remain unclear across state boundaries.

The inconsistent regulations across states create confusion for mobile delivery platforms trying to follow the rules. They also make it difficult for workers to carry their benefits with them when working in different states. More fundamentally, these measures focus on social security while avoiding the core question of whether gig workers should have collective bargaining rights, minimum wage protections, and the ability to challenge algorithmic management decisions.

Broader Economic Logic

My two-month experience illuminated how the gig economy represents not disruption but acceleration of existing trends towards worker insecurity. Platforms have successfully created a workforce that assumes traditional employer responsibilities—equipment provision, risk management, and skill development—while discarding  traditional worker protections around wages, working conditions, and job security.

This model’s political economy becomes clearer when considering its timing and context. India’s gig economy emerged during formal job creation struggles and agricultural distress, providing platforms with workers seeking income opportunities. The rural youth I originally interviewed often relied on family support to purchase the smartphones and motorcycles essential for platform work—sometimes from earnings in government welfare schemes like the Mahatma Gandhi National Rural Employment Guarantee Scheme and PM Kisan Samman Nidhi.

More significantly, I experienced how a platform transforms workers into algorithmic subjects, responsive to digital stimuli designed to maximise platform value rather than worker welfare.

Platforms benefit from what economist David Weil calls “fissured workplace” dynamics, where lead firms control value chains while avoiding direct employment relationships. This structure allows them to maintain market position and profit margins while regulatory and economic risks fall on individual workers.

NITI Aayog’s optimistic projections assume platform job creation will address India’s unemployment challenges. However, my experience suggests such work often represents economic desperation rather than genuine choice. The absence of social protection, health benefits, or retirement security makes gig work a survival strategy rather than a sustainable career path for most participants.

Towards Dignity

Looking back over those two months, I delivered roughly 30 orders and earned approximately Rs. 1,200—an amount that barely covered fuel costs for my journeys. More significantly, I experienced how a platform transforms workers into algorithmic subjects, responsive to digital stimuli designed to maximise platform value rather than worker welfare.

The gig economy’s rapid expansion in India reflects broader failures in creating dignified employment opportunities for the country’s growing workforce. Rather than addressing structural economic problems, platforms exploit them, converting unemployment and underemployment into profit-generating mechanisms.

India needs more than the current patchwork of welfare measures. Essential reforms should include transparent algorithmic management, where workers understand how earnings are calculated and orders are assigned. Platforms should bear responsibility for equipment costs, health insurance, and accident coverage rather than externalising these to workers. Most importantly, gig workers need meaningful representation in decisions affecting their livelihoods, whether through recognised unions or platform governance structures.

The workers I met deserve more than algorithmic management disguised as entrepreneurial opportunity. They need recognition that their labour—delivering food in all weather conditions, navigating chaotic traffic, maintaining professionalism despite customer frustration— constitutes essential work that deserves basic dignity and security.

The Rs. 20 I earned for my first delivery represents more than a wage. It symbolises the distance between the gig economy’s promises and its realities, between platform rhetoric about empowerment and workers’ lived experience of navigating an increasingly precarious economic landscape. As India’s policymakers celebrate the gig economy’s growth potential, they should remember that behind every platform’s success story are millions of workers trying to make ends meet in an economic system that privatises their risks while socialising their benefits.

Until this gap closes, India’s gig economy will remain a source of survival rather than prosperity for those who power it. The true measure of success will not be transaction volumes or platform valuations, but whether these workers can build stable, secure lives for themselves and their families. That transformation requires acknowledging that flexibility without security is not freedom—it is precarity by design.

Kasim Saiyyad is a PhD candidate in applied economics and management at Cornell University, New York, and a Tata-Cornell Institute Scholar. His research focuses on agriculture, livelihood, and nutrition economics in low- and middle-income countries.