India’s gig and quick-commerce sectors have surged to nearly 12 million workers in FY 2024–25, up from 7.7 million in 2020–21. It is expected to double by 2030, according to industry estimates. With blue-collar gig hiring rising 92% in 2024, delivery and mobility platforms are onboarding workers faster than their compliance teams can process them.
The rapid hiring cycle has raised concerns about safety, fraud, and identity-based risks, pushing companies toward AI-led verification that can validate identities, detect anomalies, and monitor compliance in real time. However, adoption remains uneven, creating significant vulnerabilities in a workforce that underpins India’s hyperlocal economy.
Companies like Melento (formerly SignDesk), Ongrid and Unstop are showcasing how AI is changing compliance and verification workflows and why digital maturity remains a bigger challenge.
The Push to AI-Native Compliance
Melento, a compliance-focused platform that processes over 50 million documents annually across banks, NBFCs, and large corporations, has seen AI reshape its contract management engine.
The company’s founder and CEO, Krupesh Bhat, said AI now performs the first layer of contract reviews. “It helps identify the template and runs the first review based on the playbook that’s created. It does redlining, highlights risks in contracts, and even tracks milestones and deliverables,” he said.
Bhat added that AI can automate complex actions, such as alerting teams, processing payments, or generating legal notices. Yet the hesitation does not come from the fear of AI. “Clients don’t fear AI, they just want clarity on its purpose, boundaries and oversight,” he said.
The regulatory landscape contributes to that uncertainty. There is still no consistent rulebook for gig-worker compliance, and state-wise enforcement is fragmented. Instead, the sector is informally guided by emerging principles such as algorithmic accountability, fairness in worker classification, transparent decision-making and minimal data use.
Memento is already reorienting itself for this shift. “We are transforming into more of an AI-native product company,”Bhat said. “AI allows us to launch new products and new features quickly. On a net headcount basis, I may not be able to reduce the number of people, but I’ll be able to offer more services and solutions in the market.”
Adoption Bottleneck
While AI tools are becoming stronger, Bhat said adoption depends entirely on an organisation’s existing processes. “Many internal processes still rely on email and spreadsheets. They negotiate contracts manually and lack a contract repository. AI is two steps ahead of where many companies are in their automation journey,” he noted.
The gap is particularly evident in the gig economy, where many partners are small vendors or franchise operators with limited digital infrastructure. This mismatch between AI capability and operational readiness remains India’s most significant compliance risk.
Beyond compliance platforms, AI is now handling hiring at scale. At Unstop, which works extensively with campus and early-talent applicants, AI now powers nearly 80% of the screening workflow, from assessments to document verification and fraud detection.
Ankit Agarwal, Founder and CEO of Unstop, said hiring volumes have grown three to five times, making AI unavoidable. “It flags anomalies in resumes, identity mismatches, and other risks with over 92% accuracy, he said. “AI automates the first layer of verification, cutting manual review time by 70% and ensuring every candidate goes through a uniform, skills-first evaluation.”
To strengthen fairness, Unstop trains its models on anonymised, balanced datasets across demographics and income groups. “Bias prevention starts with data hygiene,” Agarwal said. The platform uses human-in-the-loop validation for every risk flag, conducts monthly audits and routes a case for manual review if AI confidence drops below 85%.
Selective Automation
At Ongrid, a background verification company, AI is applied more selectively, often as a complement to human oversight. Its chief technology officer, Ajay Rao, said AI helps accelerate parts of the process. “AI helps flag potential discrepancies and speeds up verification, but human review is still critical, especially when dealing with sensitive PII and legal compliance,” he said.
Rao added that generative AI models are increasingly useful for extracting structured data from documents, analysing risk patterns and identifying missing information.
Cost, Infrastructure Remains a Barrier
Meanwhile, Memento’s Bhat highlighted a persistent challenge. “The trust associated with AI is one of the main hurdles. Even though we don’t use customer data to train our models, some clients worry about data privacy,” he said.
Another challenge is the cost of AI systems. For many Indian companies, it’s easier to hire entry-level staff than pay for AI tools. “AI is expensive, usage-based and still requires complementary digital tools,” Bhat explained.
Advanced AI systems, especially LLM-driven workflows, require strong infrastructure, reliable data flows and dedicated compliance governance. For companies operating on thin margins, these overheads can outweigh the benefits, slowing adoption even when risks are high.
Melento’s has built its internal AI playbook around explainability, human oversight, and auditability. Every reviewer action or AI decision is logged, traceable, and reviewable, a requirement that many clients insist on before giving a go-ahead for AI deployment.
Growing Marketing and Widening Gaps
India’s identity-verification and background-check industry is expanding rapidly, supported by the rise of gig platforms, BFSI and shared-services firms.
The country’s identity verification market size reached $451.1 million in 2024. IMARC Group, a leading market research company, expects the market to reach $1.72 billion by 2033, with a growth rate (CAGR) of 16% from 2025-2033.
Industry analyses also indicate rising identity-related discrepancies in logistics and delivery-led sectors. These trends have intensified demand for AI-assisted verification, particularly in high-velocity environments where human teams struggle to keep pace with scale.
Despite the barriers, the advantages are driving adoption. “AI is transformative when combined with human expertise. It allows our teams to focus on higher-value tasks while AI handles routine data processing,” Rao said.
As India’s gig economy continues to expand, the pressure to build faster, safer and more transparent verification systems will only grow. AI may not replace compliance teams, but it is rapidly becoming their most critical tool, especially in a labour market where trust, speed and scale are inseparable.
The post AI Redefining compliance verification for India’s Gig Economy appeared first on Analytics India Magazine.