The adoption of cloud computing solutions has increased rapidly over the past few years. Companies these days are looking for solutions that can facilitate cost savings. This can be done by making use of cloud computing, since it offers hosted data storage solutions. Owing to this, the use of deep learning technology has also increased significantly. The architecture of cloud computing supports scalability and virtualization, along with offering storage for a huge amount of data, thereby making it ideal for deep learning algorithms.

Deep learning is essentially a part of the machine learning (ML) technology, and deals with exploring and building algorithms which allow computers to adapt and learn continuously. Due to the complex relationship of data sets, implementation of analysis methods including, regression analysis and hypothesis testing becomes hard. Deep learning technology, however, allows systematic coding and categorization of data sets, which enhances visibility when it comes to errors in datasets. This further decreases the requirement for humans to analyze every set for comparison manually.

Owing to these factors, the global deep learning market is predicted to generate a revenue of $102.4 billion by 2030, increasing from $3.7 billion in 2019, exhibiting a 35.2% CAGR during the forecast period (2020–2030), as stated by a P&S Intelligence report. The major components of the deep learning technology are service, hardware, and software, out of which, the demand for hardware components has been higher in the past.

Hardware components, such as storage devices and graphics processing units, help in storing a vast amount of data for deep neural networks and training deep learning models. Other than this, the demand for deep learning software is also projected to rise considerably in the coming years, as enterprises are adopting these software for several applications, including signal recognition, voice assistance, and image recognition. Retail, BFSI, manufacturing, automotive, and healthcare are the key industries that make use of the deep learning technology.

Among these, the automotive industry made the most use of deep learning in the past, however, its adoption is also projected to grow substantially in the healthcare industry in the coming years. The healthcare industry is not only widely adopting deep learning but other AI technologies, including ML and big data, for supporting researchers and medical professionals in analysis and data extraction for better medical outcomes. The growing of the healthcare industry will further drive the demand for deep learning in the near future.

Geographically, the deep learning market was dominated by North America in 2019 because of the enhanced IT infrastructure and technological advancements. Moreover, the demand for deep learning in the region is growing for a number of applications, including image recognition on social networks, product recommendation, and voice assistance. Other than this, the Asia-Pacific region is also projected to make wide adoption of deep learning, owing to the rising investments in AI technologies by industries and governments.

Hence, the market is being driven by the increasing adoption of cloud computing and need for reducing costs in businesses.