Composite AI software provides a platform for integrating and orchestrating different AI models and algorithms to solve business problems.
Composite AI allows different AI components and subsystems to work together, something companies hope will ease integration challenges and nudge artificial intelligence-based initiatives toward success. According to a new report from MarketsandMarkets, the Composite AI market will experience significant growth thanks to the increasing adoption of AI across industries and the integration of cutting-edge tech like deep learning and edge computing. It should reach over $4 billion by 2028 with an astonishing CAGR of 36.5%
One major driver behind the market’s growth is the continued challenge of big data. Companies need AI to process it effectively, and Composite AI software provides a platform for integrating and orchestrating the different AI models and algorithms. Not surprisingly, the software market is expected to hold the largest market share.
The increased use of data mining and machine learning techniques, vital components of Composite AI solutions, are driving adoption in various domains. Data mining and machine learning is expected to grow at the highest compound annual growth rate during the forecast period.
Product design and development play a significant role in Composite AI solutions. These applications enable companies to create, iterate, and improve AI-powered products and services. They also facilitate the development of prototypes and simulations, ensuring the end-user experience is intuitive and personalized.
The report predicts the Asia Specific Region will hold the highest CAGR during the forecast period, driven by advancements made in AI, increasing data availability, and increasing instances of digital transformation initiatives. Key players include many well-known names in the tech space—IBM, SAS Institute, Microsoft, Google, AWS, Salesforce, Oracle, and others.
The future of the market not only looks promising but will likely overcome its most pressing challenges—infrastructure costs and concerns related to data privacy and security.