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    AI: The Building Block of Intelligent IoT

    Using the combination of big data, analytics, and machine learning, the internet of things (IoT) and artificial intelligence (AI) together are transforming every industry.  

    AI: The Building Block of Intelligent IoT

    By

    Apac CIOOutlook | Thursday, January 01, 1970

    Stay ahead of the industry with exclusive feature stories on the top companies, expert insights and the latest news delivered straight to your inbox. Subscribe today.

    Using the combination of big data, analytics, and machine learning, the internet of things (IoT) and artificial intelligence (AI) together are transforming every industry. AI is playing a key role in IoT applications and deployments, because of its ability to quickly extract insights from data. AI technologies like machine learning, speech recognition, and computer vision can extract insights from data, automatically identify patterns, and detect abnormalities in data. The effective combination of AI and IoT helps companies avoid unplanned downtime, increases operating efficiency, enables new products and services, and enhances risk management. IoT coupled with AI forms the foundation for improved and entirely new products and services. A number of applications pairing IoT with AI like self-driving cars and smart thermostat solutions help better understand and predict a variety of risks as well as automate the systems. Organizations are incorporating AI and IoT to determine regular access patterns of different tiers of employees or roles, providing insights for future office layouts, and detecting suspicious activity. This enables them to better manage worker safety, financial loss, and cyber threats.

    For enterprises, integrating AI and IoT with their systems gives them a competitive edge in business performance. For instance, in the automotive industry, for connected-cars, BMW’s CarData platform gives drivers access to data shared by vehicle owners and AI capabilities from IBM Watson IoT. In consumer products and retail, replenishment automation and optimization solutions use machine learning to predict demand and optimize inventory levels. Telematics solution providers are integrating machine learning into the auto-insurance industry to create accurate risk models and predict claims behavior.

    With the growing demand for IoT and AI-based services, investments in SaaS and other big data technologies are increasing. Fostering better offerings, productivity, and operations, AI is set to enhance the value of IoT deployments, thereby providing a competitive edge to companies.

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