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In today’s challenging technology landscape, AI is the key to visualizing the end-user experience and resolving elusive network issues. But not all AI is built equally. It’s important to completely understand and trust the decisions AI makes so you can reap the full benefits, such as informed decision-making, risk reduction, increased user adoption, better governance, and faster system improvement. The problem is, traditional AI doesn’t let your IT team see how its algorithm handles decision making. You need explainable AI (XAI) to be able to trace and understand AI’s decision-making processes. Join Juniper data scientists and ServiceNow for a webinar to learn about the differences between traditionally black box AI and truly explainable AI. Using several AI capabilities of Juniper Mist as examples, they will describe how the machine algorithms work and the science behind them, giving you the ultimate lens into user experience. You’ll also learn how: To enhance your trust in AI’s capabilities by understanding how AI achieves its outcomes to positively impact networks and network operations A customer improved Wi-Fi experience with real-time insights into issues like authentication anomalies during users’ wireless connections AI can proactively identify and resolve issues to deliver the best user experience To evaluate networking vendors’ AI offerings with confidence using explainability as a tool