Why Industrial AI Needs More Than Data to Deliver Results

Industrial companies are producing data like never before.

With machinery and storage systems and all kinds of product tracking devices, the companies now have a tremendous amount of information at hand. Still, many companies face difficulties with effective usage of this information.

The problem is not data.

The problem is intelligence.

The Data Gap

Most industrial companies have sensors, software platforms, and reporting systems already. What they need is the configuration of these data sources and the data itself.

This is where AIoT comes in.

AIoT represents the combination of the connectivity brought in by IoT technologies with the analytic capability of artificial intelligence. As a result, it yields systems that can monitor processes and learn how they work.

Advanced rates of analytics became the basis of modern business operations. Customers want to know where their assets are, how their equipment works, and whether the business processes are effective.

Unfortunately, having simply visibility does not help solve operational challenges.

Artificial Intelligence is capable of providing answers to more complex questions for organizations.

Which resources are not being used enough? What operational problems can emerge? What types of maintenance issues are about to happen? How can resources be used more efficiently and effectively? The Future of Artificial Intelligence and Industrial Internet of Things

With the increasing adoption of industrial AI, companies will put more effort into using platforms that integrate data about their operations with intelligent decisions.

Companies that are in the process of undergoing transformation can borrow the experience of those companies that have created an ecosystem based on the AI-enabled Internet of Things paradigm.

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The future of industrial operations belongs to organizations that can turn information into action.