AI in Wildlife Conservation Monitoring Market
The global AI in wildlife conservation monitoring market was valued at $1.8 billion in 2023, and is projected to reach $16.5 billion by 2032, growing at a CAGR of 28.4% from 2024 to 2032. The market is driven by the urgent need to combat biodiversity loss and poaching, utilizing AI-powered tools for real-time animal tracking, habitat monitoring, and data analysis. Advances in AI technologies, such as machine learning and image recognition, enable more efficient monitoring of wildlife populations and contribute to proactive conservation efforts.
Market Introduction and Definition
Artificial Intelligence (AI) in animal conservation refers to the application of AI technologies to enhance and support efforts aimed at conserving wildlife species and their habitats. This emerging market leverages AI's capabilities in data analysis, predictive modeling, and pattern recognition to address various challenges in animal conservation. AI systems are used to analyze large datasets collected through sensors, satellite imagery, and field observations to monitor species populations, track migration patterns, detect poaching activities, and assess habitat health. AI enables conservationists to make informed decisions quickly and efficiently by automating and optimizing data processing tasks, facilitating proactive conservation strategies. The AI in animal conservation market includes a range of stakeholders, including conservation organizations, research institutions, governmental agencies, and technology providers, all working collaboratively to protect biodiversity, mitigate human-wildlife conflicts, and promote sustainable conservation practices globally.
Key Takeaways
The AI in animal conservation monitoring market study covers 20 countries. The research includes a segment analysis of each country in terms of value ($Million) for the projected period 2023-2032.
More than 1,500 product literatures, industry releases, annual reports, and other such documents of major AI in animal conservation monitoring industry participants along with authentic industry journals, trade associations' releases, and government websites have been reviewed for generating high-value industry insights.
The study integrated high-quality data, professional opinions and analysis, and critical independent perspectives. The research approach is intended to provide a balanced view of global markets and assist stakeholders in making educated decisions to achieve their most ambitious growth objectives.
Key Market Dynamics
AI in the animal conservation market presents many opportunities, driven mainly by its capabilities in monitoring, data analysis, and predictive modeling. One significant opportunity lies in AI's ability to enhance monitoring efforts. Drones equipped with AI-powered cameras conduct aerial surveys of remote and expansive habitats, providing detailed insights into wildlife populations and their habitats. This technology enables conservationists to monitor species more effectively, detect illegal activities such as poaching in real-time and assess habitat changes promptly, which is crucial for timely conservation interventions. Furthermore, AI excels in data analysis by processing vast amounts of data from various sources such as satellite imagery, camera traps, and acoustic recordings. Machine learning algorithms can detect patterns in animal behavior, identify species from images, and analyze environmental parameters. Such capabilities enable conservationists to derive actionable insights quickly, improving decision-making processes and resource allocation. However, several challenges restrain the widespread adoption of AI in animal conservation. One major restraint is the high initial costs associated with acquiring and deploying AI technologies, including hardware like drones and advanced software for data analysis. In addition, there is a significant learning curve for conservationists and researchers to effectively utilize AI tools and interpret the outputs correctly. This requires investment in training and capacity building within conservation organizations.
Government Rule and Regulation
In the U.S., while there are no specific regulations exclusively for AI in animal conservation monitoring, technologies used in wildlife research and conservation are governed by environmental laws such as the Endangered Species Act (ESA) of 1973 and the Marine Mammal Protection Act (MMPA) of 1972. These laws mandate the protection of endangered species and marine mammals, respectively, and agencies such as the U.S. Fish and Wildlife Service (USFWS) and NOAA manage their implementation. The use of AI technologies for wildlife monitoring and research would need to comply with these regulations, including obtaining permits for research involving endangered species.
The European Union (EU) has stringent regulations regarding wildlife protection and data privacy, which could impact the use of AI in animal conservation. The EU's General Data Protection Regulation (GDPR) , implemented in May 2018, regulates the processing of personal data, including data collected through AI technologies used in wildlife monitoring. Conservation efforts in EU member states must also adhere to directives such as the Birds Directive (2009/147/EC) and the Habitats Directive (92/43/EEC) , which mandate the protection of wild bird species and habitats across Europe. India has robust wildlife conservation laws, including the Wildlife (Protection) Act, 1972, which regulates the conservation, management, and protection of wildlife and habitats in the country. The Act empowers the government to establish wildlife reserves, regulate hunting & trade in wildlife, and protect endangered species. AI technologies used in animal conservation monitoring in India need to comply with these regulations, ensuring ethical practices and obtaining necessary permissions from relevant authorities.
In Australia, wildlife conservation is governed by federal and state laws, including the Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act) . This Act regulates activities that impact nationally significant species and ecosystems, including the use of technologies such as AI in wildlife monitoring and research. State governments have their own wildlife conservation laws and regulations that are applied regionally.
Market Segmentation
The AI in animal conservation monitoring market is segmented into technology type, scale of implantation, application, end user, and region. On the basis of technology type, the market is fragmented into machine learning, computer vision, natural language processing, data analytics & predictive modeling, and robotics & drones. On the basis of scale of implementation, it is classified into local or regional initiatives, national conservation programs, and international collaborations & partnerships. On the basis of application, the market is divided into wildlife monitoring & tracking, habitat protection & restoration, anti-poaching measures, wildlife disease detection & management, and conservation policy & planning. On the basis of end user, market is categorized into government agencies & NGOs, wildlife reserves & national parks, research institutions & universities, and conservation-focused companies & startups. Region wise, the market is analyzed across North America, Europe, Asia-Pacific, and LAMEA.
Regional/Country Market Outlook
In the U.S., AI technologies are heavily utilized in monitoring and protecting endangered species across vast and diverse landscapes. For example, AI-powered drones and satellite imagery are used to survey habitats, track animal movements, and detect illegal activities such as poaching. These technologies enable conservationists to gather large-scale data efficiently, which enhances the understanding of ecosystem dynamics and facilitates timely interventions to mitigate threats.
Moreover, in the U.S., there is a strong emphasis on using AI for predictive analytics and modeling. Machine learning algorithms analyze historical data on wildlife populations, climate patterns, and habitat changes to forecast future trends and potential conservation challenges. This proactive approach helps in devising adaptive management strategies and allocating resources effectively. Whereas the UK focuses on integrating AI with traditional conservation methods to address specific challenges in a more localized context. AI-driven image recognition software aids in species identification and monitoring, particularly in areas where direct observation is challenging. In addition, the UK utilizes AI for habitat mapping and restoration planning, leveraging data-driven insights to prioritize conservation efforts and optimize land use.
In August 2023, Citi’s investment makes it the first FX fintech in Latin America to receive investment from a global banking giant, Citi says. It intends to integrate its own FX technology into Rextie’s currency exchange services, and Rextie customers will gain access to a range of other FX features as a result of the investment. The aim is to help turbocharge Rextie’s expansion prospects and give customers faster exchanges at more competitive rates.
In October 2023, Citigroup, one of the world’s largest financial institutions, acquired a stake in Rextie, a promising Peruvian foreign exchange startup. This acquisition marks an important development in Citigroup’s expansion plans in the Latin American market and highlights the growing significance of fintech startups in the region. Citigroup’s acquisition of a stake in Rextie underscores the bank’s commitment to innovation and its strategic focus on expanding its presence in emerging markets. This partnership positions both Citigroup and Rextie for success in the evolving landscape of the foreign exchange industry.
In November 2022, HSBC Bank (Singapore) collaborated with Saxo Bank A/S (Saxo) to adopt its end-to-end, self-directed trading infrastructure for equities investments. The collaboration will enable HSBC Singapore to strengthen its equities investment offering to all retail banking customers, including those residing overseas. By incorporating Saxo’s trading infrastructure to HSBC Singapore’s digital platform, HSBC customers will gain access to new platform functionalities, expanded global market access and enhanced user experience.
Industry Trends:
AI algorithms are increasingly used to analyze images and videos to automatically detect and identify wildlife species. This allows for more efficient and accurate monitoring of population and habitat use. For instance, in August 2023, researchers at the University of Washington developed a technology to identify individual humpback whales based on their tail flukes in drone footage. This innovative approach utilizes machine learning algorithms to analyze patterns and unique markings on humpback whale tails captured from aerial drones. This technology could be used to track whale migration patterns and assess population health.
AI models are used to predict animal movements, habitat use, and population trends, which inform conservation strategies and prioritize areas for protection. For instance, in October 2022, a team at the wildlife conservative society used AI to predict the future range of endangered Amur leopard based on climate change scenarios. This information guides efforts to secure suitable habitat for the species.
Further, AI is facilitating citizen science projects allowing volunteers to contribute to wildlife monitoring through mobile apps and online platforms. This trend increases data collection and raises awareness about conservation issues. For instance, in December 2021, the National Geographic Society launched the “Eild Eatrch” app, which uses AI to help volunteers identify and track various animal species from their own photos and videos.
Competitive Landscape
The major players operating in the AI in animal conservation monitoring market include Conservation Metrics Inc., Enview Inc., Google LLC, IBM Corporation, Intel Corporation, Leonardo, DiCaprio Foundation, Microsoft Corporation, NVIDIA Corporation, Reservoir Labs Inc., and Wildlife Conservation Society (WCS) .
Recent Key Strategies and Developments
In January 2024, the Brady Hunter Foundation partnered with Animal Survival International (ASI) , a non-profit organization that works toward wildlife protection and habitat restoration across the globe. The Brady Hunter Foundation and ASI have joined forces in a collaborative effort to combat the illegal hunting and poaching of animals at the Addo Elephant National Park in South Africa to further amplify their conservation efforts.
In July 2023, Flapmax, a leading artificial intelligence (AI) company, partnered with Intel, the global technology leader, to foster AI innovation and drive economic empowerment in Africa. The collaboration is expected to provide technology access, training, mentorship, and funding opportunities to entrepreneurs in emerging markets, starting with Africa, through the FAST Accelerator program. FAST is designed to help startups that are building cloud-based and AI-enabled products and services supporting communities, companies, and governments.
In December 2020, WWF-Australia and Conservation International, supported with a $1 million grant from Google’s philanthropic arm, launched An Eye on Recovery, a large-scale collaborative camera sensor project. The project installed more than 600 sensor cameras to monitor wildlife in landscapes impacted by last summer’s bushfires, including the Blue Mountains, East Gippsland, Kangaroo Island, and Southeast Queensland.
Key Sources Referred
- weforum.org
- ganzsecurity.com
- skyrora.com
- intercontactnews.com
AI in Wildlife Conservation Monitoring Market Report Highlights
Aspects | Details |
Market Size By 2032 | USD 16.5 Billion |
Growth Rate | CAGR of 28.4% |
Forecast period | 2024 - 2032 |
Report Pages | 243 |
By Region |
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By Technology Type |
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By Scale Of Implantation |
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By Application |
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By End User |
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Key Market Players | Conservation Metrics Inc., IBM Corporation, Microsoft Corporation, Intel Corporation, DiCaprio Foundation, NVIDIA Corporation, Enview Inc, Wildlife Conservation Society, Google LLC, Leonardo, Reservoir Labs Inc. |
The AI in animal conservation monitoring market was valued at $1.8 billion in 2023 and is estimated to reach $16.5 billion by 2032, exhibiting a CAGR of 28.4% from 2024 to 2032.
Increasing data processing efficiency and real-time monitoring are the upcoming trends of AI in Wildlife Conservation Monitoring Market in the globe.
Rising demand for enhanced monitoring and early warning systems is the leading application of AI in the Wildlife Conservation Monitoring Market.
North America is the largest regional market for AI in Wildlife Conservation Monitoring.
Conservation Metrics Inc., Enview Inc., Google LLC, IBM Corporation, Intel Corporation, Leonardo, DiCaprio Foundation, Microsoft Corporation, NVIDIA Corporation, Reservoir Labs Inc., and Wildlife Conservation Society are the top companies to hold the market share in AI in Wildlife Conservation Monitoring.
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