Global Artificial Intelligence in Forestry and Wildlife Market Size, Share & Trends Analysis Report, By Application, By Technology, By End-use, By Region Forecasts, 2024 - 2032

Global Artificial Intelligence in Forestry and Wildlife Market Size, Share & Trends Analysis Report, By Application, By Technology, By End-use, By Region Forecasts, 2024 - 2032

Global Artificial Intelligence in Forestry and Wildlife Market was valued at US $ 1.7 Billion in 2023 and is expected to reach US $ 16.2 Billion by 2032 growing at a CAGR of 28.5% during the forecast period 2024 – 2032.

The application of artificial intelligence (AI) technologies and solutions to the sustainable management, conservation, and use of forestry and wildlife resources is included in the market for AI in forestry and wildlife. In order to improve many facets of environmental monitoring, biodiversity preservation, and ecosystem management, this market integrates powerful AI algorithms, data analytics, machine learning, and computer vision techniques. Early threat detection, species identification and monitoring, habitat assessment, data-driven decision-making, and the optimisation of forestry operations are some of the key applications in this sector. Utilising AI's potential to solve environmental issues, support sustainable forestry practices, and encourage wildlife conservation are the ultimate goals. This will help ensure that human activity and natural ecosystems coexist peacefully. A wide range of stakeholders are involved in the industry, including governmental bodies, environmental groups, IT companies, and experts in forestry and animal management.

The expanding market for AI applications in forestry and wildlife management is mostly driven by the growing need for sustainable forest management. This junction is in line with the worldwide imperative for responsible environmental management and addresses important concerns. By streamlining logging procedures, boosting reforestation initiatives, and pinpointing locations essential for biodiversity preservation, artificial intelligence (AI) technologies—such as predictive analytics and machine learning algorithms—help manage resources more precisely. AI enables proactive actions and mitigates potential environmental damage by enabling the early detection of dangers, such as disease outbreaks and wildfire risks. The preservation of biodiversity is essential to sustainable forest management, and artificial intelligence is essential to species identification, habitat monitoring, and ecological assessments. AI helps conservation efforts that attempt to save endangered species and preserve ecological balance by offering a deeper knowledge of how human activity affects ecosystems.

“Forest Management segment, by application, to be dominating market from 2023 to 2030.”

Forest management is the most popular use of AI in the forestry and wildlife sector, accounting for more than 47.41% of the market. With a CAGR of more than 26.2%, wildlife conservation is the application of AI in the forestry and wildlife business that is expanding the fastest. Because of its critical role in maximising resource allocation, reducing risk, and improving operational efficiency, forecast management leads the field in artificial intelligence applications for forestry. Forestry professionals may anticipate weather patterns, disease outbreaks, and natural disasters with the use of AI-powered prediction models. This allows them to take preemptive measures to reduce risks and enhance overall forest management practices.

“Machine Learning segment, by technology, to be dominating market from 2023 to 2030.”

With a market share of more than 70%, machine learning (ML) is the top AI technology in the forestry and wildlife sector. With a 26.74% CAGR, deep learning (DL), a kind of machine learning, is gaining traction in the AI industry for forestry and wildlife. Because of its adaptability and widespread use in a variety of applications, machine learning (ML) is the most popular artificial intelligence (AI) application in forestry and wildlife management. Machine learning approaches, which encompass both supervised and unsupervised learning, have demonstrated efficacy in tasks including pattern recognition, picture identification, and predictive modelling.

“Government Agencies segment, by end use, to be dominating market from 2023 to 2030.”

Government agencies are the top end-user of AI in the wildlife and forestry sector, holding a market share of more than 46.32%. With a CAGR of more than 23.54%, conservation organisations are the AI end use in the wildlife and forestry industry that is expanding the fastest. Government organisations are pioneers in using artificial intelligence (AI) to forestry and wildlife management because of their legislative mandates, vast resources, and participation in environmental projects. Government organisations are in a strong position to implement AI technology for effective natural resource monitoring and management because of their dedication to enforcing environmental legislation and their strong infrastructure, which includes satellite networks and extensive data archives.

“North America to be largest region in Artificial Intelligence in Forestry and Wildlife market.”

The largest market for AI in forestry and wildlife is in North America. With more than 45.35% of the global market in 2023, the region has the most market share. The market for AI in forestry and wildlife is expanding at the quickest rate in the Asia Pacific area. Over the next five years, the region is predicted to grow at a compound annual growth rate (CAGR) of more than 32.73%, fueled by rising government investment in AI technologies and expanding private company use of AI solutions. North America's early adoption culture, emphasis on environmental protection, and technology breakthroughs have made the region a leader in the application of artificial intelligence (AI) for forestry and wildlife management. The area has a strong ecosystem of IT businesses and academic organisations that are actively involved in AI development, especially in the US and Canada.

Artificial Intelligence in Forestry and Wildlife Competitive Landscape

The competitive landscape of the Artificial Intelligence in Forestry and Wildlife market involves assessing the competitive landscape to understand the strengths, weaknesses, opportunities, and threats of the industry. Key industry players have recognized that the adoption of Artificial Intelligence in Forestry and Wildlife technology holds the potential for further growth. The growing desire among producers to optimize their production costs has spurred collaborative efforts among companies to scale up their production capacity. This strategic collaboration not only aims to increase revenue but also seeks to establish dominance in the market.

The Artificial Intelligence in Forestry and Wildlife market is highly competitive, with numerous companies vying for market share. Prominent companies in the Artificial Intelligence in Forestry and Wildlife Market include:

Dryad, Ororatech, Microsoft AI, Conservation International, Gridware, Google AI, World Wildlife Fund (WWF), IBM, Amazon Web Services, The Nature Conservancy, SAP, Siemens, NVIDIA, Intel, Hewlett Packard Enterprise, Oracle, Dell Technologies, Fujitsu, Panasonic, Cisco Systems, Samsung Electronics, Mitsubishi Electric, SONY, Hitachi, NEC Corporation, Epson and others.

Recent Developments:

In October 2023, Google AI and WWF collaborated to develop a cutting-edge AI-powered technology that can accurately identify deforestation in almost real-time. This programme, which makes use of satellite data and machine learning, can detect areas where trees have been removed, offering a thorough tracking system for tracking trends in deforestation over time.

IBM and The Nature Conservancy collaborated in September 2023 to develop a cutting-edge AI-powered application designed to help forest managers make knowledgeable decisions about land management. This programme, which combines data analytics and machine learning, provides insightful information about factors including tree growth patterns, possible hazards, and the health of the forest, enabling efficient and sustainable land management practices.