CCNA AI and Network Operations Practice Question

Correct answer & explanation

Options A, B, C, and D are correct. AI models can predict bandwidth congestion by analyzing historical traffic data, enabling proactive capacity planning. Natural language processing (NLP) automates helpdesk ticket responses by interpreting user intent, reducing manual effort. Reinforcement learning can dynamically adjust firewall rules in response to evolving attack patterns, improving threat response without human intervention. Unsupervised learning can cluster behavior patterns to identify unknown device types on the network. Option E ("AI eliminates the need for baseline performance metrics because it learns in real-time") is incorrect because even AI/ML models require baseline metrics to establish normal behavior and detect anomalies; real-time learning does not remove the need for baselines. Option F ("ML models always require labeled training data to be effective in network operations") is incorrect because many ML techniques, such as unsupervised learning (as shown in option D), operate effectively on unlabeled data by discovering patterns and clusters without predefined labels.