The development of observing capacity to provide informative and robust biodiversity assessments is crucial to evaluate progress against international agreements and to underpin evidence-based conservation and informed management strategies. Better understanding of biodiversity patterns and their dynamics requires automated biodiversity monitoring, harmonization of sampling methods and better coordination of sampling efforts. Yet, resolution, calibration, standardization, ground-truthing and cost-effectiveness remain critical challenges for most techniques that enable automated biodiversity monitoring. BioBoost+ addresses these challenges by improving non-invasive, efficient, and high-frequency sampling of marine zooplankton, benthos and fish through digital imagery (Theme 1). BioBoost+ combines state-of-the-art Artificial Intelligence (AI) technology with an unprecedented training set of fit-for-purpose images of a wide range of taxa, including habitat-forming species (seagrass meadows, shellfish beds, and macroalgal canopies), indicator species of ecological and economic importance (e.g., coastal fish, lobsters), invasive species, and understudied taxa (faunal assemblages in the plankton and harboring within macroalgal canopies, macrozoobenthos, and rare fish). Continuous data streams will be generated through networks of cameras using cost-effective technologies to enable real-time acquisition and distribution of biodiversity data. The proposed technological advancements will be used to: 1) Improve monitoring of marine ecosystems, including ongoing restoration interventions and Marine Protected Areas (MPAs), through direct testing and validation of real-time biodiversity assessment to be exported across European and non-European waters (Theme 2); 2) Develop image analysis of seabed habitat maps to capture large-scale phenomena, such as habitat fragmentation, thresholds, regime shifts and species invasions in vulnerable ecosystems (e.g., seagrasses and macroalgal forests), which are relevant to assess the Good Environmental Status of ecosystems (Theme 2); 3) Improve the sensitivity of a range of policy-relevant biodiversity indicators to multiple stressors, including climatic and anthropogenic drivers of change, using the Essential Biodiversity Variables (EBVs) framework (Theme 2 and Theme 3); 4) Engage with prominent Citizen Science marine programs, such as the Reef Life Survey (RLS), to broaden the spatial scales of sampling through digital images and to evaluate the pros and cons of automated approaches for taxa identification (Theme 1 and Theme 2). By delivering cost-effective methodologies for high-frequency monitoring of species abundance and diversity and improved indicators of change, BioBoost+ will boost national and regional monitoring programs and provide science-based support to assess progress towards the achievement of national and international conservation targets.