Content sponsored by Zendesk
Data has become the engine of most organizations. Provides lots of information about customers, products, finances, sales, competitors, and more. But managing all this data can be a challenge without the right tools. Many organizations use artificial intelligence, such as robots, to help them manage their data.
The word “bot” is short for robot. It is a form of artificial intelligence that is designed to simulate human activity. Bots can be applied in many ways to automate tasks and organize large volumes of data.
This is how some industries and companies use bots as part of their data management strategy.
Insurance companies are heavy management organizations, often drowning in policy claims, claim forms and compliance documents. Manual processes mean that employees can take weeks or months to process documents. By speeding up policy issuance and claims processing, insurance companies can reduce operating costs and improve customer service.
An insurance company has decided to implement robotic process automation (RPA) to streamline document management. Zurich Insurance Group used RPA to automate policy and claims processes. These were the results:
- The company reduced operating costs by 51%. These cost improvements have saved them more than $ 1 billion.
- They released 25% of the capacity of their operational team, some of whom were redirected to work on the newly established Robotic Center of Excellence unit.
- Payment of claims is a week ago compared to the industry average of 50 days.
- Policy transaction processing has been reduced from 4-5 hours to 40-80 minutes.
The healthcare industry is adopting AI technology to more efficiently manage the large amounts of data it collects and accesses. For example, each disease and medication is assigned a medical code. There are thousands of codes that track a patient’s journey from diagnosis and treatment to insurance and billing claims.
Bots are used to automate many administrative processes and to improve patient care. AI chatbots can help patients look for symptoms or side effects of medications, talk to healthcare professionals, and schedule medical appointments.
Voice recognition virtual assistants can help administrative and medical staff retrieve patient information, medical codes, and other data simply by talking to them. Physicians and nurses can reduce the time they spend documenting the patient’s interaction with speech-to-speech transcription software.
Bots can also be used by patients to manage their health. By downloading a health app to their smartphone, a patient can track their health data, such as blood pressure, diet, exercise, and sleep patterns. Applications can also be used to remind patients with chronic conditions to take their medication on time.
Chatbot software has become an integral part of customer service. Customers want immediate solutions to their problems, and online chatbots can offer them. As a result, consumers embraced chatbots.
Statistics show that 67% of customers have used a chatbot in the last year and 69% prefer to use chatbots because they can provide quick answers to simple questions. This means that your human agents can focus on assisting customers with more complex issues.
Chatbots are a type of conversational AI and should not be confused with Live Chat, which uses a human agent.
Chatbot software is becoming more and more advanced, able to handle queries from initial query to resolution. However, chatbots are not intended to replace human agents and should provide the customer with the option to speak with a human customer support agent.
The Experian 2019 Global Data Management Research report found that most of the companies surveyed believe that almost a third of their data is inaccurate in some way. Ninety-five percent said their business suffered negative impacts due to poor data quality, which led to wasted resources and inefficient business initiatives.
Poor data integrity leads to poor business decisions. But why are so many companies struggling with data integrity? Partly due to poor data management structures and human error. Data management bots are able to more accurately organize large volumes of data.
Let’s look at Pratt & Whitney, the maker of the Geared Turbofan (GTF) aircraft engine that is revolutionizing aviation. The GTF engine improves fuel efficiency and reduces noise and emissions.
Data analysis is important for continuous engine improvement. As such, Pratt & Whitney have placed 5,000 sensors on the engine that generate up to 10 gigabytes of data per second, far more than the aircraft’s standard engine.
More than 1,100 aircraft piloted by 62 airlines are already using the GTF engine, and by January 2022, another 10,000 orders have been received. All those engines provide data to the company - the amount of which reaches zettabytes. Using AI robots, the company can collect and analyze this staggering amount of data to get an accurate indication of engine performance.
Business intelligence is largely data driven. If your data is defective or unused, your company is at a disadvantage. Artificial intelligence helps companies in all industries to better manage their data so that they can make smarter business decisions.