In an era of AI (artificial intelligence) and the IoT (Internet of Things), enterprise applications are continuing to evolve, and CPG (consumer packaged goods) companies are taking note and moving to new applications. The result will be greater efficiency, improved visibility, and businesses that are embracing the latest emerging technologies.

According to IDC, the use of artificial intelligence and ML (machine learning) is occurring in a wide range of applications from ERP (enterprise resource planning) and manufacturing software to content management, collaboration, and user productivity. Artificial intelligence and machine learning are being considered by most organizations today. IDC expects that AI will be the disrupting influence changing entire industries throughout the next decade.

Many of the CPG companies are beginning to identify how to best leverage AI today—which is still the early stage for many. On The Peggy Smedley Show earlier this month, Peggy Smedley spoke with Qingbin Yuan, senior director, R&D international,. The Hershey Co., about how to use the technology to predict and formulate product to meet the consumer needs.

In other recent news, Nielsen announced it is growing its analytic relationship with General Mills, meaning General Mills will use Nielsen’s new Connect platform, which can help expand the view into the consumer marketplace to provide a deeper understanding of customer needs, while also enabling faster decision making.

Another example of innovation for the enterprise in general comes from Oracle OpenWorld, which took place in September. It announced availability of its AI-trained voice with Oracle Digital Assistant, which means enterprise customers can use voice commands to communicate with their enterprise applications.

One company leaping into Industry 4.0 is Titan Intl., which is a manufacturer of off-highway wheels, tires, assemblies, and undercarriage products. The company has moved its core business processes to Oracle Cloud applications for finance, supply chain, and manufacturing.

The objective? To build a smart factory. It is automating manual processes and using data from sensors to improve insights into inventory. A second phase will introduce this automation to more production areas and the final phase will include machine monitoring on the shop floor so Titan can better understand the health of its machines and do predictive maintenance.

While using AI in a factory environment is just one example, the trend toward leveraging more data throughout a large enterprise continues. In many cases, the objective is to enhance communication and bring transparency to a business, all while improving efficiencies.

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