Optimizing Legal Service Delivery Using AI-Based Incentives for E-Marketplaces in India

The rapid digital transformation of India’s legal sector has led to the emergence of e-marketplaces that connect legal service providers with citizens. However, ensuring sustained participation and high-quality service delivery remains a challenge. This research proposes an AI-driven Incentive Optimization Model (AI-IOM) that leverages Reinforcement Learning (RL) and Game Theory to dynamically adjust incentives for legal professionals based on performance, demand fluctuations, and client satisfaction. The proposed model integrates Fuzzy Logic-Based Reward Structuring (FLRS) to personalize incentives and Blockchain-Assisted Trust Mechanisms (BATM) to enhance transparency and reliability in digital legal transactions. Experimental evaluations on real-world legal e-marketplace datasets demonstrate that AI-IOM significantly improves provider engagement, response efficiency, and service affordability while reducing dropout rates. The study highlights the potential of AI-driven incentive structures in fostering a more efficient, accessible, and trustworthy legal e-marketplace ecosystem in India.