Edge computing also means that manufacturers may be able to deploy sensor-enabled devices for automation, which can lower costs. Here too, skilled workers are needed to deploy those devices, as are people with a background in AI and machine learning to optimize a plant’s processes. Data scientists may also be required, for sifting through the torrents of new sensor-generated information to identify the valuable bits that will make for a more efficient, competitive operation. And keep in mind: With so many devices connected to a network, security is a critical consideration, meaning cybersecurity skills are essential.
The healthcare field offers its own range of possibilities and requirements. For example, 5G promises to give people in rural communities access to medical specialists without traveling to and from a big city. Such uses will require AI-enabled cameras, 3D imaging, and the integration of sensors and other equipment, as well as new technologies that might include holography—all of which demand the skills to operate and maintain those systems.
Another example is a hospital seeking to deploy a 5G network to automate data input from mobile devices, rather than from within dedicated work areas. While that invariably will require integration with legacy systems, 5G leaders like T-Mobile for Business and our deep ecosystem of partners can tend to the middleware or underlying technologies that weave those pieces together through managed services.
In either of those healthcare contexts, or any other involving sensitive medical information, security and privacy are paramount concerns. Whatever the field or industry, any organization with an IT department very likely has people on staff who understand the basics of cybersecurity. But 5G’s capacity to handle so many devices transmitting vast stores of data—in an IoT environment, for example—means being mindful of the potential need to either upskill or expand the security team.