IoT 2.0? Machine learning and AI services worth €3 bn in revenue in 2026

Simultaneously, the value in the technology stack is shifting beyond the hardware and middleware to analytics and value-added services, such as machine learning and other kinds of AI. ABI Research estimates that machine learning and AI services in the IoT domain will grow at a compound annual growth rate (CAGR) of nearly 40%, to $3.6 billion (€3.04 billion) in 2026. While COVID-19 impacted many industries, the IoT data analytics market has been less affected. In fact, many newly emerging cloud-native, data-enabled analytics vendors have benefited from COVID-19. "Since industries are transitioning to'remote everything', out-of-the-box solutions for remote monitoring, asset management, asset visibility, and predictive maintenance are in high demand and exemplify market acceleration. "Vendors, such as DataRobot, are now easing access to ML and AI tool sets through different deployment options at the edge, on-premises, and the cloud, and through consumption using Platform as a Service (PaaS), and Software as a Service (SaaS)," explains Kateryna Dubrova, Research Analyst at ABI Research. "All and all, the COVID-19 pandemic highlighted the importance of rapid deployment solutions, such as hardware agnostic SaaS." Companies like AWS, C3, and Google also have been successful in promoting their products and analytics capabilities (tool sets and environment) by creating centralized repositories for COVID-19 data. Currently, these data lakes are public and are not monetised, but ABI Research expects those companies will attempt to use the data lakes to create products for sale to the healthcare market in the future. From a technology perspective, the data lakes could be the first step for creating and testing data visibility, and streaming analytics services. COVID-19 has showcased the public cloud's healthcare industry ambitions expanding into pharmaceutical, biomedicine, and telemedicine. Big data and data analytics might not have a remedy for the virus, but IoT-data enabled technologies proved essential to lessen public anxiety, to monitor patients, and prepare the infrastructure for new outbreaks. "AI and ML usage has accelerated during the pandemic – however, greenfield AI projects have seen a significant slowdown.