Implementing the Biodiversity Beyond National Jurisdiction (BBNJ) Agreement in a State Centric System: The Role of AI in Data Readiness, Corporate Traceability, and EIA Consistency in Areas Beyond National Jurisdiction (ABNJ)

Yunjoo Cho

Areas Beyond National Jurisdiction (ABNJ) cover most of the ocean but remain governed through fragmented regimes and uneven scientific capacity. The Biodiversity Beyond National Jurisdiction (BBNJ) Agreement aims to strengthen marine biodiversity conservation in these waters through marine protected areas and other area-based management tools, environmental impact assessment (EIA), marine genetic resources and benefit sharing, and capacity building with technology transfer. This paper argues that early effectiveness will depend less on treaty design and more on implementation capacity. The analysis identifies three challenges. First, data readiness in ABNJ is weak for policy use. Long-term time series are limited, biodiversity records are patchy across depth and habitat, and baseline setting and cumulative impact assessment are hard to operationalize. Second, implementation is state-centric, but many pressures are driven operationally by private actors such as distant-water fishing and large aquaculture and seafood supply chains. The key risk is not the absence of direct corporate duties in international law, but weak traceability and uneven due diligence when States must translate treaty duties into operator-facing requirements and reliable information flows. Third, EIA in ABNJ faces jurisdictional ambiguity. Multiple legal anchors can plausibly apply, and uneven discretion may allow avoidance or minimum standard selection. Artificial Intelligence (AI) can reduce friction in data use, support early risk screening, and improve transparency by structuring documents and disclosures into review-ready evidence. However, AI cannot allocate legal responsibility, decide jurisdiction, resolve regime overlaps, or create political agreement. The paper evaluates AI as a support tool, not a decision maker. The policy implication is that data governance and capacity building should come first, with AI used to amplify these foundations. The UN Ocean Decade is framed as a practical space to test shared tools, standards, and capacity pathways that can make BBNJ implementation more workable.