Abstract : The pest control market is experiencing rapid growth, driven by increasing urbanization, heightened health concerns, and a growing emphasis on hygiene practices. As cities expand and populations rise, the demand for effective pest control solutions continues to surge, with projections indicating the market will reach USD 38.6 billion by 2030, growing at a compound annual growth rate (CAGR) of 5.2%. The review systematically examines the current trends, challenges, and opportunities within the pest control industry, with a particular focus on advancements like Integrated Pest Management (IPM) and the role of consumer behavior in shaping pest control practices. A key feature of the review is its interdisciplinary approach, which merges insights from environmental science, public health, and business management, offering a comprehensive perspective on pest control strategies. To ensure a robust review of AI-driven advancements in pest control, studies published in 2024 were selected based on relevance, quality, and geographical significance. The process prioritized empirical research, theoretical analyses, case studies, and reviews focusing on AI applications like machine learning, IoT, and integrated pest management. A global scope was adopted, emphasizing regions with significant pest control challenges. Data extraction included methodologies, outcomes, and environmental impacts, highlighting AI’s potential to enhance efficiency and sustainability. Synthesized findings identified key trends, challenges, and opportunities, emphasizing AI’s transformative role in eco-friendly pest management and guiding future research and innovations. The findings highlight that the integration of artificial intelligence (AI) technologies significantly enhances pest detection, optimizes resource allocation, and promotes sustainable practices in pest management. AI-driven systems can offer more precise monitoring, early detection of pest infestations, and targeted interventions, reducing reliance on chemical treatments and minimizing environmental impact. However, the review acknowledges challenges such as regulatory hurdles and environmental concerns, which may slow the widespread adoption of AI in pest control. Furthermore, limitations in the review include potential biases in the studies selected and disparities in technology adoption across regions, which may limit the generalizability of the findings. Looking ahead, future research should focus on the socio-economic impacts of AI applications in pest control and assess their long-term effectiveness, particularly in diverse agricultural settings. Overall, the review serves as a valuable resource for stakeholders including researchers, practitioners, and policymakers guiding the development of sustainable pest control strategies that align with evolving consumer expectations, regulatory frameworks, and environmental sustainability goals.