This is the most advanced stage of the Visual Transformation, where service organizations can increase call deflection and reduce customer effort with visual, interactive guidance powered by Computer Vision AI. The visual customer assistant can deliver full self-service resolutions without interactions with human agents – think of this as a chatbot that can see. The visual assistant can recognize the product and its parts, identify the issue, and provide the resolution for the customer.
For example, a customer needs help troubleshooting their security system, which is making chirping noises. With autonomous assistance, the customer interacts with a visual tech assistant that can see using the power of Computer Vision AI. The customer is instructed to capture images of the alarm’s control unit. The system recognizes the device and then provides the customer with step-by-step guidance to resolve the issue.
This technology can also be utilized as a visual employee assistant that can offer decision support for agents and technicians by recognizing the problem and supplying the employees with next-best actions to fix the issue. For example, an IT technician completes a server installation job and captures an image of the completed work. With autonomous assistance, a visual tech assistant — powered by Computer Vision AI — recognizes that one of the cables has been placed incorrectly, and supplies the technicians with the steps needed to fix it.
AI is essential for helping CSPs build self-optimizing networks (SONs), which give operators the ability to automatically optimize network quality based on traffic information by region and time zone. Artificial Intelligence applications in the telecommunications industry use advanced algorithms to look for patterns within the data, enabling telcos to both detect and predict network anomalies, and allowing them to proactively fix problems before customers are negatively impacted.
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