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Business Management Review | Friday, June 17, 2022
Since their emergence, the two technologies that have become the cynosure of all eyes in the technology industry are artificial intelligence (AI) and the Internet of Things (IoT). These technologies have helped companies bring significant innovations in multiple processes and applications.
The IoT technology allows smart automation of many devices, vehicles, buildings, and others by allowing them to host algorithms and perform functions through AI-enabled solutions. The AI-enabled software will enable users to manage the IoT data at speed and scale without human intervention. The software also supports handling the complexity of IoT technology without compromising accuracy.
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The existing AI algorithms designed for viewing, analyzing, and acting, are deployed primarily as a single agent where intelligence occurs independently. Therefore, these unique algorithms cannot greatly influence a company's operations.
Nevertheless, Social AI can be the answer to addressing the issue as it can combine all the results of individual occurrences, enabling businesses to gain significant insight. For instance, the algorithms in driverless cars are not just focused on a particular vehicle; rather, it optimizes the distribution of traffic in a congested situation by combining data from all the other vehicles.
Integrating IoT data in AI-enabled software can help make distributed smart agents. These combinations will support companies in different decision-making processes by allowing a shift from default internet-connected devices to a collection of interacting smart agents.
Smart agents can also help predictive maintenance as AI-based software can use IoT data to analyze equipment health. Predictive maintenance can help companies maintain their equipment's health and prevent mechanical failure.
The vast majority of investment in the IoT industry is concentrated on providing innovative solutions to consumers. However, businesses have now started to use IoT technology in more enterprise and B2B operations. As a result, companies need AIOPs to handle the complexities of enterprise and B2B IoT data.
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