It’s no secret that every ITOps leader can face an ever-increasing amount of alerts. Since the dawn of digital, alerts have served an important purpose. Sometimes all those alerts can become overwhelming noise, and sorting out what is and is not a priority can become challenging. The good news is that artificial intelligence (AI) and machine learning (ML) are adept at processing large data sets in real time, looking for patterns and being able to aid in decision making.
Artificial Intelligence (AI) has become a buzzword in recent years. From chatbots to self-driving cars, AI has transformed how we live, work, and interact with the world around us. AI technology has been deployed across various sectors, including healthcare, finance, manufacturing, and more, to improve efficiency, accuracy, and decision-making capabilities. However, as AI systems become more complex, monitoring them to ensure optimal performance and prevent issues or errors becomes crucial.
Today’s Cognitive Network Operations Center (Cognitive NOC) is a significant advancement that employs artificial Intelligence (AI) and machine learning (ML) to dramatically modernize and improve network management and operations. Working together, the NOC and IT Process Automation (ITPA) propel superior efficiency and effectiveness of network operations, minimize downtime, lower operational costs, and overcome additional challenges in optimizing network performance.
The quality of customer experience (CX) is declining, according to the American Customer Satisfaction Index. Customer satisfaction is at its lowest point in 17 years: 73.2 out of 100. Many factors are at play here, but there’s clearly an opportunity to improve the experience your customers receive. Adopting new strategies and technologies, such as AI in the contact center, can significantly improve efficiency and competitive advantage in three key ways.
In today’s fast-paced world, app performance equals brand reputation. Customers expect apps that are fast, responsive and available 24/7. That’s where Application Performance Monitoring (APM) comes in. The technology enables businesses to ensure the best possible user experience by monitoring and managing the performance of their applications. But as applications become increasingly complex, identifying and resolving performance issues in real-time becomes increasingly difficult.
