Artificial intelligence can improve employee experiences and reduce network downtime. Credit: iStock The hybrid workforce will continue for the foreseeable future, according to the Foundry 2022 Future of Work study. And the trend is affecting hiring and retention, with 62% of IT leaders saying their organizations are guaranteeing flexible work options to stay competitive in the marketplace. Just as important: The technology and systems these employees use must be reliable and secure. Poor connectivity or network downtime not only frustrates users but also eats into productivity. And yet both hybrid and on-site workers are experiencing a high volume of network interruptions, according to a Juniper Networks survey. For example: 38% of hybrid workers said they suffer at least 10 interruptions per week In-office employees cite at least five connectivity issues per week Imagine knowing that at least once a day, your network connection will go down. On the flip side, 92% of respondents to the Juniper study said their productivity would increase by an average of 39% if they had uninterrupted network connectivity. Thanks to artificial intelligence (AI) technologies, your business can now better deliver on employee expectations for seamless connectivity. Proactively reduce network issues “One of the most important enhancements in the networking industry over the past handful of years has been the application of machine learning and artificial intelligence technologies to enhance the operational management, performance, and security of networks,” writes Brandon Butler, Research Manager, Enterprise Networks at IDC, in his report titled “The Role of Session-based SD-WAN in an AI-driven Enterprise.” AI network solutions help get ahead of issues before they become problems. For example, Juniper Mist AI™ delivers end-to-end insights into user experiences such as any issues with latency, uptime, throughput, and capacity. The solution’s combination of AI, ML, and data science enables automated event correlation, root cause identification, anomaly detection, and more. These technologies optimize operations across wireless, wired, and SD-WAN networks. For example, a global technology company sought to improve Wi-Fi connectivity for its 40 offices in 14 countries. The company’s global head of networks said employees are “heavy users of video communications,” making up to 45,000 video calls per day globally. The tech provider’s previous system struggled with reliability and consistent connectivity, so they decided to deploy the Mist AI platform, including the Marvis Virtual Network Assistant (VNA), which proactively helps correct issues in real time to accelerate ticket resolution. “VNA is very cool,” said the global head of networks. “It gives our workers the information they need to troubleshoot their own problems and provides me insight into how everything is working at a macro level.” The company has also been able to proactively identify issues in real time. “I saw on the Mist AI dashboard that the accounting group in London was having a coverage issue, so I proactively brought it up with that team,” the network executive said. “They explained that they were indeed having a poor Wi-Fi experience, but they didn’t want to complain to IT. After fixing the problem, we looked like real heroes for the proactive outreach and attentive service.” The bottom line Enterprises require a proactive, intelligent approach to meet employee expectations for network connectivity — no matter whether they’re working remotely or in the office. Mist AI provides near real-time identification and detection of issues, as well as proactive recommendations and self-healing capabilities. This results in fewer support tickets — and fewer complaints from employees. Learn more about how Mist AI helps you provide reliable network connectivity. Related content brandpost Sponsored by Juniper Networks Give Employees and Customers the Network Experience They Deserve Artificial intelligence technologies are accelerating network performance, while also providing proactive troubleshooting. 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