From impact to regeneration: Bioremediation of petroleum-derived compounds enhanced by biosurfactants and AI

Environmental contamination from petroleum hydrocarbons remains a persistent challenge for land and water ecosystems, with well-documented ecotoxicological, socioeconomic, and public health impacts. This study aimed to systematically review literature published between 2000 and 2025, synthesizing evidence on petroleum impacts, current bioremediation technologies, and the emerging roles of biosurfactants and artificial intelligence in optimizing these processes. The methodology involved a structured search in the Scopus database, using combined keywords related to bioremediation, petroleum, and biodegradability, followed by bibliometric analysis and mapping of international patents. In situ and ex situ bioprocesses were compared regarding mechanisms, limitations, and applications, while recent literature was examined to identify technological trends and scientific gaps. Results show a steady increase in scientific output since 2014, with China, India, the United States, and Brazil leading research efforts. Biosurfactants are highly effective in solubilizing, dispersing, and removing hydrocarbons, especially those derived from agro-industrial waste—a strategy extensively documented in recent patents. Additionally, AI-based approaches, including AutoML, neural networks, and predictive modeling, are emerging tools capable of optimizing fermentation conditions, predicting molecular properties, and improving remediation performance. It is concluded that integrating biotechnology, biosurfactants, and artificial intelligence creates a new paradigm for remediating oil-contaminated areas, enhancing efficiency, accuracy, and sustainability. This convergence offers environmentally safer, economically viable solutions aligned with the circular economy and Sustainable Development Goals, while also revealing gaps and opportunities for developing autonomous bioprocesses with minimal environmental impact.