Explore the Deep Learning Market Report 2025

• Industry Growth Overview: The deep learning market size is projected to grow from USD 34.29 billion in 2025 to USD 144.64 billion in 2029 at a compound annual growth rate of 43.3%. On a micro level, the deep learning domain grew at an annual rate of 25.04% as per the Discovery Platform’s latest data.
• Manpower & Employment Growth: The deep learning field employs 330K people globally. The field created 47K new jobs last year, which shows its role as an employer.
• Patents & Grants: The market holds 386K patents and received 2200 grants. It has 19K global applicants, with patent growth at 42.34% annually.
• Global Footprint: Key hubs are the United States, India, the United Kingdom, Germany, and France. Cities like London, New York, and Bangalore lead regional innovation.
• Investment Landscape: The sector saw substantial investments, with an average round value of USD 16.2 million. More than 8000 investors funded 11K rounds across 2400 companies.
• Top Investors: Leading investors include Microsoft, SoftBank Vision Fund, General Motors, and more with combined investments exceeding USD 3 billion.
• Startup Ecosystem: Prominent startups include mlHealth 360 (AI-powered diagnostics), SYGMA.AI (automotive claims management), Tensorleap (model debugging), Nomitri (embedded vision AI for retail), and Adlook (privacy-focused advertising).

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Methodology: How We Created This Deep Learning Report

This report is based on proprietary data from our AI-powered StartUs Insights Discovery Platform, which tracks 25 million companies and 20 000 technologies and trends globally, including detailed insights on approximately 5 million startups, scaleups, and tech companies. Leveraging this extensive database, we provide actionable insights on emerging technologies and market trends.

For this report, we focused on the evolution of deep learning over the past 5 years, utilizing our platform’s trend intelligence feature. Key data points analyzed include:

• Total Companies working on the trend
• News Coverage and Annual Growth
• Market Maturity and Patents
• Global Search Volume & Growth
• Funding Activity and Top Countries
• Subtrends within deep learning

Our data is refreshed regularly, enabling trend comparisons for deeper insights into their relative impact and importance.

Additionally, we reviewed external resources to supplement our findings with broader market data and predictions, ensuring a reliable and comprehensive overview of the deep learning market.

What Data is Used to Create This Deep Learning Report?

Based on the data provided by our Discovery Platform, we observe that the deep learning market ranks among the top 5% in the following categories relative to all 20K topics in our database.

These categories provide a comprehensive overview of the industry’s key metrics and inform the short-term future direction of the industry.

• News Coverage & Publications: The deep learning field featured over 15K news articles and publications last year.
• Funding Rounds: Our database records 11K funding rounds, indicating substantial investment activity.
• Manpower: Employing over 330K workers globally, the sector added 47K new jobs last year.
• Patents: With 386K patents, the domain emphasizes innovation and intellectual property.
• Grants: It has secured 2200 grants, highlighting its success in attracting research and development funding.
• Yearly Global Search Growth: There is rising curiosity on the topic, as demonstrated by an increase of 61.1% in global search interest over the past year.

Explore the Data-driven Deep Learning Market Report for 2025

As per the Business Research Company report, the deep learning market size is projected to grow from USD 34.29 billion in 2025 to USD 144.64 billion in 2029 at a compound annual growth rate of 43.3%.

Similarly, Fortune Business Insights projects the market to grow from USD 24.53 billion in 2024 to USD 298.38 billion by 2032, exhibiting a compound annual growth rate of 36.7% during the forecast period.

Another analysis suggests that the global deep-learning market was valued at approximately USD 96.8 billion in 2024 and is projected to grow at a compound annual growth rate exceeding 31.8% from 2025 to 2030.

The Deep Learning Report 2025 uses data from the Discovery Platform and encapsulates the key metrics that underline the sector’s dynamic growth and innovation.

The market includes 1852 startups and 9700 companies. Over the past year, the industry grew by 25.04%, which reflects increased adoption of deep learning technologies across various sectors.

Credit: The Business Research Company

Additionally, the domain has 386K patents and 2200 grants that underscore research and innovation.

The global deep learning workforce numbers 330K professionals, with 47K new jobs created last year. This highlights the industry’s increasing role in job creation.

Key country hubs for deep learning include the United States, India, the United Kingdom, Germany, and France. Major city hubs like London, New York, San Francisco, Bangalore, and Seoul drive innovation in the sector.

A Snapshot of the Global Deep Learning Market

The deep learning field grew by 25.04% annually, which shows increasing adoption across sectors. The ecosystem has 1800+ startups, including 1050 in the early stages, indicating ongoing innovation. Additionally, 300 mergers and acquisitions highlight industry consolidation.

Intellectual property development features prominently, with 386K patents filed by 19Kapplicants globally. The annual patent growth rate is 42.34%. It reflects ongoing advancements in deep learning.

China leads with over 163K patents, followed by the United States with over 109000. This emphasizes their significant contributions to global innovation in deep learning.

Explore the Funding Landscape of the Deep Learning Market

The deep learning domain shows strong investment activity, with an average funding round value of USD 16.2 million. This financial backing reflects investor confidence in the sector’s growth potential.

Our database records over 8000 investors supporting more than 2400 companies.

Moreover, over 11K funding rounds have been closed, showing a consistent inflow of capital for advancements in deep learning technologies.

Who is Investing in Deep Learning Solutions?

The top investors in the deep learning domain have invested over USD 3 billion, showing strong confidence in the sector’s potential.

• Microsoft has invested USD 776.2 million in 10 companies. Microsoft, SoftBank, and partners launched the USD 500 billion Stargate Project to build AI data centers in the USA.
• SoftBank Vision Fund has contributed USD 675.8 million across 6 companies. SoftBank’s Vision Fund 2 invested USD 500 million in OpenAI, valuing it at USD 150 billion.
• General Motors invested USD 598 million in 2 companies. General Motors increased its investment in the Thacker Pass lithium mine in Nevada to nearly USD 1 billion, partnering with Lithium Americas Corp.
• NVIDIA, a leader in AI hardware, has backed 15 companies with USD 521.7 million. NVIDIA invested USD 1 billion across 50 deals, up from USD 872 million last year.
• Goldman Sachs invested USD 411.5 million in 7 companies. Goldman Sachs’ Alternatives division successfully raised over USD 20 billion for its senior direct lending fund, West Street Loan Partners V.
• SAIC Motor directed USD 347.6 million into 2 companies. SAIC Motor and Volkswagen extended their 40-year partnership until 2040, emphasizing a shift towards electric vehicles (EVs).
• Khosla Ventures has funded 13 companies with a total investment of USD 323.6 million. Khosla Ventures led a USD 18.5 million Series A funding round for Rogo, a secure enterprise AI platform designed by and for finance professionals.

Top Deep Learning Innovations & Trends

The deep learning domain evolves rapidly, driven by various trends. These trends show different levels of company activity, workforce growth, and growth rates.

• Deep Reinforcement Learning, led by 150 companies with 4000 professionals, added 700 employees last year. Its 48.99% annual growth rate highlights its applications in autonomous systems and decision-making technologies.
• Neuromorphic Computing, with 500 companies and 12K employees, shows growth in hardware innovation. The sector added 1000 professionals last year, with a 19.79% annual growth rate. It emphasizes energy-efficient and biologically inspired computing systems.
• Artificial Neural Networks, comprising 350 companies and 7000 employees, focus on algorithmic advancements. It added 850 employees last year, reflecting steady workforce growth with a 19.54% annual growth rate. This signals ongoing interest in core deep learning technologies.

Further, the deep learning sector is anticipated to attract investments, particularly in cloud-based technologies and advanced computing hardware, which are crucial for enhancing deep learning.

5 Top Examples from 1800+ Innovative Deep Learning Startups

The five innovative startups showcased below are picked based on data including the trend they operate within and their relevance, founding year, funding status, and more. Book a demo to find promising startups, emerging trends, or industry data specific to your company’s needs and objectives.

mlHealth 360 offers AI-powered Diagnostic Assistant

Canadian startup mlHealth 360 develops AI-powered diagnostic tools for radiologists. Its product Scaida, a cloud-based platform, analyzes medical images to prioritize cases and generate standardized reports.

Scaida Flow offers similar features without the AI module, which aids in case management and report generation.

The startup’s Scaida DetectCT, an AI-driven module integrates into workflows to detect abnormalities in various anatomical regions.

Also, the Scaida BrainCT focuses on identifying brain anomalies. These tools streamline radiology processes, enhance diagnostic accuracy, and improve efficiency allowing healthcare professionals to concentrate on complex cases and improve patient outcomes.

SYGMA.AI streamlines Insurance Claims Management

Moroccan startup SYGMA.AI offers AI-driven solutions for automotive damage assessment. It combines photo capture, AI inspection, and damage detection to streamline vehicle evaluations.

It uses a phone or fixed camera to capture images and inspect them for validity, genuineness, and fraud detection.

The system identifies car body damages, analyzes severity and specific zones, and detects mechanical issues. It also estimates repair and spare part costs to provide a detailed report with damage and cost estimations for each claim.

SYGMA.AI enhances efficiency and accuracy for insurers, manufacturers, and rental companies and simplifies claims and repairs.

Tensorleap provides Debugging and Explainability Platform

Israeli startup Tensorleap builds a deep learning platform that improves model explainability and interpretability.

It analyzes each node in a neural network’s computational graph to extract indicators from all model feature maps.

The startup’s algorithms construct an informative latent space that enables the identification of sample clusters and model interpretations.

It offers features such as guided error analysis, dataset architecture design, deep unit testing, and team collaboration tools.

Tensorleap integrates with any framework and supports various data types that allow data scientists to build reliable neural networks.

Nomitri specializes in Visual Deep Learning

German startup Nomitri develops embedded deep-learning vision AI technology with products like EMSCo, EM-Cart, EM-Pick and Pack, and E.V.A to enhance retail efficiency.

The EMSCo platform uses vision AI for inventory tracking and in-store analytics through edge processing. Its EM-Cart transforms shopping carts into intelligent devices that guide customers, process purchases, and reduce checkout times.

Further, the EM-Pick and Pack system automates item picking and packing in warehouses using on-device AI. The E.V.A. framework supports these solutions with privacy-preserving, energy-efficient edge processing to eliminate cloud dependency.

Nomitri offers real-time performance and data security and allows retailers to optimize operations, improve customer experiences, and reduce operational costs.

Adlook enables Brand Growth through its Platform

Polish startup Adlook develops a brand growth platform that uses deep learning for privacy-focused digital advertising.

Its engine scans the internet in real-time across multiple languages to enable precise cookieless targeting based on context and behavioral insights.

The platform integrates geo-targeting proximity and dynamic creative optimization for location-based, personalized ad delivery without personal identifiers.

The startup features attention pre-bid optimization, real-time attention measurement, and attention-based media buying to enhance ad visibility and engagement while reducing waste.

It leverages cross-screen capabilities to maximize impact across connected TVs and other devices to optimize for high-quality creative delivery and measurable branding outcomes.

Further, Adlook isolates emission signals and embeds sustainability into its bidding process to minimize the environmental footprint of advertising while maintaining performance guarantees.

Gain Comprehensive Insights into Deep Learning Trends, Startups, or Technologies

The deep learning market will continue to grow in 2025 due to advancements in AI applications across industries. Trends like deep reinforcement learning, neuromorphic computing, and artificial neural networks will drive innovation and efficiency. As investments and research increase, the sector will expand, offering new opportunities in automation, decision-making, and computational intelligence.

Get in touch to explore all 1800+ startups and scaleups, as well as all market trends impacting deep learning companies.