AI Proposed as a Tool to Detect Undeclared Employment
Neural networks could act as reliable filters for illegal and “gray” employment schemes. At the same time, public trust will be the key factor shaping how these AI tools are deployed.
The Expert Center at RANEPA has proposed using artificial intelligence systems to identify undeclared employment. The approach focuses on analyzing tax contributions, workforce anomalies, and patterns such as frequent staff turnover. At the initial stage, according to expert Sergey Bolovtsov, the process could begin with soft notifications to citizens and employers, followed by more formal inspection procedures.
AI is increasingly entering administrative systems, regulatory enforcement, and compliance technology. This approach can help protect workers from informal employment arrangements, including cases where labor relationships are misclassified as civil contracts, leading to the loss of social protections. In practice, the labor market becomes more transparent, the shadow sector shrinks, and unfair competition decreases.
Managing Risk Without Overreach
The proposal has broad potential for phased implementation. One likely path involves introducing risk-scoring and analytics systems for inspections and interagency commissions. In this model, AI acts as a filter, identifying suspicious patterns, correlating data across sources, prioritizing cases for review, and helping oversight bodies allocate resources more effectively.
Analytical platform modules, explainable AI for oversight, and compliance technologies for public agencies could also have export potential. This is particularly relevant for CIS and EAEU countries, as well as other markets where Russian solutions are already in demand. However, both domestically and internationally, public trust will remain the decisive factor. As AI moves deeper into employment oversight, transparency of criteria, strong data protection, and clear appeal mechanisms become critical. Without them, reputational and legal risks could outweigh the benefits.
A Global Structural Challenge
Ensuring the legality of employment markets has become a systemic government priority. In 2025, the Russian government approved a national action plan to combat undeclared employment for 2025–2027. In parallel, Rostrud launched an open registry of employers linked to confirmed cases of illegal employment. In 2026, RANEPA and Moscow authorities demonstrated an AI system designed to detect corruption indicators in oversight activities. Risk analytics and monitoring systems are also used by the Federal Tax Service.
Similar approaches are used internationally. Lithuania has implemented a risk-based inspection system supported by intelligent analytics. Albania has also deployed similar tools, with its 2023–2025 case highlighted by the International Labour Organization as an example of improving inspection efficiency through digitalization. According to the European Labour Authority, undeclared employment remains a significant issue for workers, businesses, and governments alike.
Expanding the Role of AI in Labor Oversight
A single unified AI system to address undeclared employment is unlikely to emerge in the near term. Instead, pilot projects are expected to appear in individual regions, integrated with existing data from Rostrud, the Federal Tax Service, and interagency commissions. Over time, these pilots may scale into broader risk-scoring modules.
In any scenario, demand will grow for applied government AI capable of working with heterogeneous data, explaining its conclusions, and integrating into regulatory processes. AI is becoming not only a service tool but also an instrument of public oversight. This creates new opportunities to bring more of the labor market out of the shadows. For developers, the central challenge is to build systems that combine effectiveness with compliance and legal safeguards.
