Saturday, November 26, 2022

IoT-Based AI and ML Services Market Will Touch $3.6 billion in 2026

By Sudipta Choudhury - August 02, 2021 3 mins read

IoT data-enabled technologies have proved essential to lessen public anxiety, monitor patients, and prepare the infrastructure for new outbreaks, reveals a new study.

The next trend of Internet of Things (IoT) analytics development will ultimately converge with data and analytics – particularly the big data domain. Concurrently, the value in the technology stack is moving beyond hardware and middleware to analytics and value-added solutions, including machine learning (ML) and artificial intelligence (AI).

IoT data analytics segment is less affected

According to a recent ABI Research study, ML and AI services are projected to grow within the IoT domain with a CAGR of roughly 40% – reaching $3.6 billion in 2026. While the widespread pandemic affected many industries, the IoT data analytics marketplace has been less affected.

Also Read: Four Reasons Why Cloud Migrations Could Fail

In fact, several newly emerging cloud-native data-enabled analytics vendors have benefited from COVID-19. Many technology vendors are now easing access to ML and AI toolsets through various deployment features at the edge, cloud, and on-premises, and by consumption using platform-as-a-service (PaaS) and software-as-a-service (SaaS).

As explained by Kateryna Dubrova, Research Analyst at ABI Research – “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.”

Certainly, COVID-19 has highlighted the value of rapid deployment solutions – this indicates the hardware-agnostic SaaS. Besides, organizations like AWS, C3, and Google have successfully promoted their products and analytics capabilities (both toolsets and environment) by building centralized repositories for the COVID-19 data.

This unprecedented era accelerated AI and ML usage in IoT

At present, these data lakes are public and are not monetized. However, it is projected that those firms will attempt to use the data lakes to make products for sale to healthcare in the future. From a technology viewpoint, the data lakes could be the first step for developing or testing data visibility as well as streaming analytics services.

Also Read: Four Strategies for Businesses to Sustain the Speed of Innovation

Clearly, COVID-19 has showcased the public cloud’s healthcare sector ambitions expanding into biomedicine, pharmaceutical, and telemedicine. Big data and analytics may not have a remedy for this virus; however, IoT data-enabled technologies proved essential – to lessen public anxiety, monitor patients, and prepare the infrastructure for new outbreaks.

The usage of advanced technology has accelerated amid the pandemic — however, Greenfield AI projects have seen a notable slowdown. The AI and ML in the IoT are at their initial adoption stage. The need for data-enabled infrastructure development has hindered the rapid adoption of machine learning on an operational level since 2020.

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Sudipta Choudhury

Marketing professional with experience in B2B and MR industry. Skilled in Marketing, Strategy Making, Copywriting and Content Creation, Sales, and SEO with excellent Communication Efficiency. Holding a dual master's degree focused on Marketing from IBS, Pune and ICFAI University.

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