map marker United Kingdom | 06 April 2026
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Mariya Krestyanska Summerfield, Associate in Offshore Renewables at WSP, is helping redefine how marine biodiversity is monitored in offshore wind. Working at the intersection of realtime AI, marine ecology and nature‑inclusive design, Mariya is advancing new approaches to digital ecology across global offshore renewables markets. Following her recent presentation at Marine Renewables Canada, she explores how AI‑enabled monitoring is strengthening environmental evidence, supporting adaptive management, and shaping the future of sustainable marine development.

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1- What motivated you to focus on real-time AI species recognition for marine biodiversity monitoring, and why is this technology so important for the offshore wind industry right now?

Offshore wind is expanding at an unprecedented pace, but for years, marine biodiversity monitoring has relied on traditional, human-led visual surveys: snapshots in time that are expensive, limited and sometimes inconsistent. The emergence of AI has created a huge opportunity to do things differently. What excites me about AI-enabled monitoring is its ability to bridge the gap between ecology and technology. We can now “see” marine life in real time, at scales and resolutions that were previously impossible. For developers, this means faster consenting and stronger evidence; for ecologists, it means better data to inform our advice. Ultimately, everyone benefits: especially the environment, as it enables smarter, more adaptive decisions. Over the past two years, I’ve been driving this agenda within WSP, helping shape our capabilities and partnering with innovators globally. What I’ve seen is that AI, not only fills a technical gap, but it also elevates our role as consultants, enabling WSP to advise with more confidence, more precision and more foresight.

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2. What are the main challenges in implementing AI-driven monitoring, and how does it compare to traditional methods?

The biggest challenge is balancing rapid industry growth with environmental accountability. Traditional surveys are still important, but they’re limited: expensive, seasonal and often subjective. AI flips that model. With automated video analysis and machine learning, we can monitor continuously and reduce human error to help build robust ecological baselines. This approach empowers our ecologists with richer, verified data that underpins early design solutions and supports long-term adaptive management. The current challenge lies in ensuring that everyone including engineers, regulators and developers alike, can use this data effectively and are prepared to adapt their practices in response.

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3. Can you share practical examples of how AI monitoring is being applied, and what lessons have been learned so far?

We’re seeing exciting pilots, often in collaboration with technology partners. For example, we’re working with a company that builds artificial reefs from recycled shells, a true circular economy approach. These reefs are being monitored using AI to detect, classify and track species in real time. While these aren’t yet WSP-led projects, we’re developing our own pilots and looking for developers to partner with. One key lesson is the importance of collaboration between engineers, ecologists, and data scientists. The technology alone isn’t enough; it’s how you integrate it that matters. AI turns static data into a living feedback loop, giving developers confidence in their environmental performance and providing regulators with richer evidence. 

One of the most rewarding aspects of this work has been the momentum it has created across WSP’s global network. Teams from the UK, Canada, the US, and Europe are now exploring how AI- enabled monitoring can accelerate project timelines, reduce uncertainty, and support Future Ready® design. Our teams have become shapers of how marine digital evidence will be used in policy, consenting and operational decision-making worldwide.

4. How is real-time AI monitoring changing stakeholder engagement, especially with local communities and educational institutions?

When people can actually see what’s happening below the surface, everything changes. Real-time footage, species dashboards and visual analytics make biodiversity tangible, not just abstract data. We anticipate these tools will transform engagement across the board, helping schools, communities and policymakers connect with offshore projects in a more immediate, visual way. For example, live video feeds from reef structures have sparked excitement among children and educators. By turning complex ecological data into something people can see and relate to, AI humanises science and builds trust, the foundation of social licence. In a sector that has often struggled with transparency, this kind of visibility could be a genuine turning point.

5. What are the biggest hurdles to scaling up AI-driven biodiversity monitoring and how can these systems be effectively integrated into industry frameworks?

The technology is advancing quickly, but the real challenge now lies in governance and consistency. We need shared standards across regulators, developers and data providers so that AI-generated insights are comparable in quality. Every marine environment is different, but what matters is that data capture, validation and reporting follow recognised frameworks. Integration should start at the design and consent stages, not after installation. Early data collection helps calibrate algorithms to local species and conditions, improving detection accuracy and ensuring later results reflect true ecological change. If we get that alignment right, we move from isolated pilots to a credible, scalable system that supports national biodiversity targets and faster, evidence-based consenting.

With WSP’s Future Ready® approach, our teams act as a bridge, bringing together all the relevant parties to design pilots, validate approaches and ensure new solutions are robust and scalable. This means that we’re helping clients adapt to new policy landscapes and also shaping those landscapes to deliver sustainable outcomes for the industry and the environment.

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6. Looking ahead, how might real-time AI monitoring shape future policy and operational decisions in marine renewable energy?

Real-time AI monitoring is already starting to change how we think about evidence in marine policy and offshore development. Instead of relying on one-off surveys, regulators can access continuous, verified data that shows what’s really happening. This reduces uncertainty and supports more flexible, adaptive management. As more projects use consistent data methods, it becomes easier for governments and industry to compare sites and technologies over time, potentially shaping new national biodiversity indicators and speeding up consenting for projects with positive environmental outcomes. The next big step will be recognising digital monitoring as part of official environmental guidance. Looking further ahead, I see AI, environmental DNA (eDNA) and satellite sensing working together to create a shared digital picture of the ocean, helping everyone make faster, better-informed decisions that support both clean energy and healthy marine life.

Ultimately, we want to ensure that WSP remains ahead of the curve from adapting to leading the change. Realtime AI monitoring is just the beginning of a broader shift towards digital marine ecology, and WSP is uniquely positioned to help shape what that future looks like.

AI in marine ecology is still in its infancy, but the potential is enormous. As Mariya notes, “You have to recognise the potential ahead of time and invest in your own capabilities. The technology is in constant development. Those who are ready will be ahead.”
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