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Authorities in Prayagraj district, Uttar Pradesh have identified nearly 42,000 ineligible applicants on the beneficiary list of the Pradhan Mantri Awas Yojana Gramin (PMAY-G) after deploying artificial intelligence (AI)-based verification, officials said in the past week. The new system, introduced last year as part of an upgraded application process, required applicants to complete a mobile self-survey by submitting personal details and photographs of their dwelling units. Out of 1,64,953 applications received from across 23 development blocks, AI flagged 61,566 cases as suspicious where uploaded images suggested ownership of pucca houses. Field verification confirmed about 42,000 of those as ineligible for the rural housing scheme. The process to remove these names from the PMAY-G beneficiary list is underway, as authorities focus on curbing misuse and ensuring that support reaches genuinely eligible rural families.
Authorities in Prayagraj district have intensified scrutiny of applications under the Pradhan Mantri Awas Yojana Gramin (PMAY-G), identifying nearly 42,000 applicants as ineligible following a combined artificial intelligence (AI) and field verification exercise, officials confirmed in the past week. The initiative follows an upgraded application process introduced last year that mandates a self-survey by prospective beneficiaries. Advertisement
Under the revised framework, prospective beneficiaries were required to submit their personal information along with photographs of their current dwellings via a mobile application as part of an initial eligibility screening. The AI system analysed these images across patterns such as construction quality, presence of permanent structures and roofing materials, to flag cases that appeared inconsistent with the scheme's eligibility norms.
District officials said that out of 1,64,953 applications received from across 23 development blocks in Prayagraj, the AI tools flagged 61,566 applications as potentially suspicious. These cases were subsequently referred to local officials for detailed physical verification. Following field checks and corroboration with other data points, roughly 42,000 applicants were confirmed as ineligible because they appeared to own or reside in permanent, pucca houses a key disqualifier under the rural housing scheme.
The verification process is now moving towards formally removing these names from the PMAY-G beneficiary list, a step that authorities said is necessary to ensure that limited housing subsidies are reserved for genuinely eligible rural households. Officials overseeing the programme emphasised that AI is intended to support, not replace, field verification by human teams, and that subsequent actions will comply with scheme rules and audit protocols.
Project Director of the District Rural Development Agency, Bhupendra Singh, stated that the system's automatic scans were able to identify features such as concrete walls and permanent roofing reliably, which were instrumental in distinguishing ineligible applicants from genuine beneficiaries during subsequent field inspections. Singh added that action will be taken against those found to have falsely claimed eligibility, in line with programme regulations.
The detection of such a large number of ineligible applicants highlights both the potential and the challenges of integrating AI into public service delivery, particularly in large-scale welfare schemes like PMAY-G where accurate targeting of benefits is crucial for effectiveness and equity.
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