“The global AI market is entering a new phase in 2020 where the narrative is shifting from asking whether AI is viable to declaring that AI is now a requirement for most enterprises that are trying to compete on a global level,” said Keith Kirkpatrick, principal analyst with Omdia. “AI is likely to trigger major transformations in industries where there is a clear case for incorporating AI, rather than in pie-in-the-sky use cases that may not generate a return on investment (ROI) for many years.”
Demand for AI in the consumer, enterprise, government and defence sectors is growing. Currently, the number of business-to-business (B2B) software opportunities related to AI total 333 and cover 28 industry sectors, with 203 unique use cases. These use cases cover three major categories that are defined by the primary technology enablers of vision, language and analytics. Industry sectors where AI is likely to generate an immediate ROI include consumer (internet services), telecommunications, automotive, healthcare, advertising, business services and retail.
The consumer sector has been particularly successful in tapping the potential of AI due to the availability of an increasingly large amount of data as well as the development of powerful AI algorithms and processing hardware. This is expected to motivate other top AI verticals to leverage the growing use of Internet of things (IoT) data sources, specialized deep-learning (DL) algorithms and high-end processing hardware.
Due to the rising adoption of consumer digital assistants in smart speakers, mobile smartphone devices, automobiles as well as in other consumer devices and services, voice/speech recognition represents the highest revenue-generating use case. The sector is forecasted to rake in a global cumulative revenue of $38.8 billion from 2018 to 2025 and attain annual revenue of $8.8 billion in 2025.
Up to 2025, Omdia estimates that 57 percent of AI revenue will involve perception, with enhancements in vision and language. And moving forward, DL will be the key driving force of the AI market.
Unlike machine learning (ML), DL has improved perception capabilities that enable it to learn the features and rules of data without being told what those features are. This capability has allowed DL to extend to other types of very large datasets, such as those found in investment trading, cybersecurity and healthcare.
Furthermore, many use cases will employ DL or a combination of DL with other technologies like ML, computer vision, natural language processing or machine reasoning. As a result, DL-based human perception derived from vision and language is expected to take over machine learning-based analytics’ role in driving AI in the long run due to the wide range of use cases that will be enabled now and well into the future.
The largest technology category in terms of revenue, DL revenue is expected to grow from $5.1 billion in 2018 to $74.5 billion by 2025, representing 59 percent of the overall AI market in 2025.
