Artificial intelligence (AI) will be integrated into the new rural labor law for village business planning, implementation review and fraud detection, according to internal documents seen by HT and officials familiar with the matter who stressed that all administrative decisions will remain in the hands of human authorities.
The new technology is part of the government’s new Viksit Bharat Guarantee for Mission Rozgar and Ajeevika (Gramin), or VB-G RAM G. The statute came into force on July 1, replacing the Mahatma Gandhi National Rural Employment Guarantee Scheme (MGNREGS), increasing the number of guaranteed working days but also introducing changes to how the program is funded and its operational nuances.
While debate over the legislation has focused on replacing the current scheme and mandatory face verification, internal documents reviewed by HT show that the law envisions a much broader digital architecture, where AI operates in three stages: planning, auditing and fraud risk mitigation.
For example, in audits, engineers will digitally map work sites before construction, during work, and after completion, with AI comparing images to report if the project location changes or a different asset is built than the approved one. Likewise, for planning, the technology will read satellite images, watershed maps, and groundwater data to suggest where the check dam should be built — and report whether a similar structure already exists nearby under another scheme.
A senior government official who spoke to HT, requesting anonymity, said the AI will serve as a decision support tool, identifying potential violations and analyzing trends, rather than replacing officials or automatically approving or rejecting projects.
According to the official, the technology ecosystem, including AI-powered functions, is being developed by the Ministry of Rural Development in collaboration with technical agencies, including the National Informatics Center (NIC) and the National Remote Sensing Center (NRSC), and “other technical and implementation partners, as appropriate” — referring to potential third-party contractors.
One of its biggest uses will be village infrastructure planning through the Vixit Gram Panchayat Plan – a long-term development plan that identifies all the infrastructure and public assets needed for the development of the village, rather than just drawing up an annual list of works. The plan will continue to be prepared and approved by the Gram Sabha, but unlike the previous ‘business shelf’, it will rely on scientific planning and convergence with other government schemes, according to an internal ministry document.
He, for example, will identify all the infrastructure the village needs – from roads and water conservancy structures to anganwadis, and community halls. The official explained that while works that fall under the Rural Employment Program will be funded through it, projects that require support from other departments will be linked to schemes run by ministries such as health, agriculture or animal husbandry.
According to the document, planning tools based on artificial intelligence and geographic information systems will be utilized. The planning system will draw on multiple data sets, including rainfall patterns, previous rural employment and assets built under other government schemes.
Fraud detection and auditing
Jobsite mapping that supports fraud detection will be carried out by engineers in three phases – before construction begins, during the course of work, and after completion. According to the ministry document, the system can compare records and report discrepancies.
Technology will also support audits by analyzing complaints and social audit results to identify recurring patterns. For example, if a particular district repeatedly reports late pay, attendance issues or poor-quality work, the system will flag these trends for officials to investigate and take corrective action, the official explained.
The broader digital ecosystem
Workers’ attendance will be recorded through facial verification instead of paper records. “The job site supervisor…will just need to hover his phone camera in front of the worker’s face. The app will take the photo and match it with the photo already downloaded in the electronic muster list. Once the face matches, attendance will be recorded,” a senior official of the Ministry of Rural Development explained to HT, describing how the system works.
Addressing concerns about technology failure, the official said the system includes an exception handling mechanism for cases where facial authentication fails due to poor connectivity, device malfunction or other technical issues. In such cases, supervisors can request an exemption through the app itself, and workers will not be denied employment if their attendance cannot be recorded through face verification.
Records of daily attendance and work will be maintained through electronic attendance lists — digital records that record workers’ attendance, work allocation and wages — while engineers will record measurements of completed works in electronic measurement books instead of paper files, the official said. The same digital system will be used to geo-tag completed assets so their locations can be verified, monitor implementation through real-time Management Information System (MIS) dashboards, and allow workers to file complaints and track them through an online grievance redressal system.
However, digital rights experts have raised concerns about the expanded use of artificial intelligence in the programme. Apar Gupta, a digital rights and constitutional lawyer, said the use of AI in planning, attendance, audits and grievance redressal processes “cannot be treated as a routine administrative upgrade” as the digitization of the earlier MGNREGA had already created barriers to workers getting their statutory entitlements.
Gupta pointed to a 2026 study by Realizing Rights, which analyzed more than 30 million wage transactions and found that Aadhaar-based payments neither improved payment timeliness nor reduced denial rates. He added that research conducted on the attendance app of the National Mobile Monitoring System (NMMS) had documented workers losing wages due to poor connectivity, lack of smartphones and incorrect digital records. The research was conducted by LibTech India, a consortium of researchers and activists who frequently analyze rural employment data.
“Under the VB-G RAM G system, these harms will deepen as algorithmic determination will affect who receives work, which projects are approved or whether a complaint is considered genuine,” Gupta said.
However, the senior official at the Ministry of Rural Development rejected the suggestion that AI would make administrative decisions. The official told HT that AI will only assist officials by identifying patterns, suggesting locations of assets and reporting possible irregularities, while decisions related to recruitment, project approvals, payment of wages and redressal of grievances will continue to be taken by the Gram Sabha or officials as the case may be as per the provisions of the law.
Rohit Kansal, Secretary, Ministry of Rural Development, said the technology-driven governance framework was designed to “enhance transparency, accountability and efficient service delivery while ensuring that adequate mechanisms are in place to handle exceptions and that no genuine worker is deprived of attendance or work due to poor network connectivity, technical glitches or hardware-related issues.”
