Deep Learning Market to Hit $296B by 2031
A new report from Mordor Intelligence projects the global deep learning market will exceed $296 billion by 2031, growing at a compound annual rate of 35.48%. The growth is expected to be driven by broad AI adoption, investment in generative AI, and increased demand for automation in fields like computer vision and robotics.
- The deep learning market is shaped by major technology companies, including hardware providers like NVIDIA, Intel, and AMD, and software and cloud platform providers such as Google, Amazon Web Services (AWS), and Microsoft. - Enterprise AI adoption is a significant driver of market growth, with 72% of organizations now using AI in at least one business function. However, scaling these projects remains a challenge, as fewer than 40% of companies have moved beyond the pilot stage. - A key trend in MLOps is the management of the entire lifecycle of deep learning models, which includes everything from data versioning and governance to continuous training, monitoring for drift, and ensuring security and compliance. Kubernetes is increasingly used as the underlying infrastructure for these workloads, with 50% of companies running AI/ML on it to manage both resource-intensive training jobs and continuous inference services. - For ML engineers, optimizing GPU infrastructure costs is a critical concern, with strategies that include right-sizing instances for specific workloads (e.g., using NVIDIA T4 for inference and A100 for training), leveraging spot instances to reduce training costs by up to 90%, and separating training and inference infrastructures. - The rise of "agentic AI" is a significant trend, with predictions that by 2028, 33% of enterprise software applications will incorporate AI agents capable of autonomous decision-making and completing multi-step tasks. - Venture capital investment in AI is substantial, with AI-focused startups securing about a third of all VC funding in 2024. In 2025, investment in generative AI companies surged, with foundation model providers alone raising $80 billion, which is double the amount from the previous year. - Despite the growth in AI adoption, a significant skills gap remains a primary obstacle. In the EU, nearly 71% of enterprises that considered but did not adopt AI cited a lack of in-house expertise as a key barrier. - The market for deep learning applications is diverse, with image recognition, data mining, and natural language processing (NLP) being key segments. Voice-enabled chatbots and other conversational AI are major applications driving the adoption of NLP and automatic speech recognition technologies.
