Artificial Intelligence in Forestry: A Comprehensive Analysis of Current Applications and Future Perspectives

This study systematically analyzes artificial intelligence (AI) applications in forestry management, exploring current implementations, challenges, and future perspectives. A review of 580 articles from Web of Science (211) and Scopus (369) databases (2021-2025) identifies key themes where AI is transforming forestry practices. Forest Monitoring and Management Systems (30.4%) and Digital Transformation (23.6%) dominate current research, followed by Resource Optimization (17.1%) and Biodiversity Conservation (14.6%). Significant opportunities are noted in productivity enhancement, risk analysis, biodiversity conservation, and carbon management through AI. However, challenges such as data quality, resource constraints, operational complexities, and regulatory requirements remain. Emerging trends like human-centered AI, digital twins, and integrated sensor networks show promise. This analysis offers valuable insights for forestry professionals, researchers, and policymakers, providing a framework to understand AI's potential and limitations while emphasizing balanced integration for environmental sustainability and operational efficiency.