Deforestation in Ghana has shifted from frontier expansion to internal intensification, while forest governance continues to rely primarily on enforcement-based approaches. This desk study examines the structural drivers of forest loss in Ghana and assesses the role of Artificial Intelligence (AI) in enabling transparency and accountability within environmental management systems. Using AI Methodological Hierarchy and Automated Monitoring Pipelines as analytical frameworks, the study assesses how digital monitoring tools interact with institutional and socio-economic drivers of land-use change. The findings indicate that the cocoa sector in Ghana has reached physical limits for expansion in several regions, leading to cultivation in secondary fallows and, in some cases, in protected areas. Evidence shows that a substantial share of cocoa-related forest conversion occurs within legally recognised farms and off-reserve concessions, indicating inconsistencies between regulatory frameworks and land-use outcomes. Although conservation mechanisms have produced notable gains over time, leakage effects and limited community participation have affected implementation. The review highlights that AI-based monitoring systems improve detection accuracy and data integration; however, their effectiveness is shaped by tenure insecurity and inequalities in digital infrastructure.
Dongballe et al. (2026) studied this question.