- A
AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs.
This is a key feature of agentic AI: agents use reasoning to select and call tools (e.g., show commands, configuration APIs) to gather data or make changes.
- B
AI agents only monitor network traffic and alert humans for any remediation actions.
Why wrong: This describes traditional monitoring, not agentic AI. Agentic AI agents take action themselves, not just alert.
- C
Tool-calling in agentic AI allows the agent to execute network commands or scripts to collect data and implement changes.
Tool-calling is a core mechanism where the AI agent invokes external functions (e.g., netmiko, RESTCONF) to perform network operations.
- D
A closed-loop remediation workflow continuously monitors network state, detects anomalies, triggers an AI agent to diagnose, and applies corrective actions automatically.
This defines the closed-loop process: monitor, detect, diagnose, act, and verify, all automated without human in the loop.
- E
Closed-loop remediation always requires a human to approve each corrective action before it is executed.
Why wrong: Closed-loop implies automation without manual approval; human approval would break the loop.
Quick Answer
The correct answer is that AI agents autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs, alongside closed-loop remediation that continuously monitors, diagnoses, and applies fixes automatically. This works because agentic AI in network automation relies on autonomous decision-making, where the AI agent selects the next action based on real-time network state, then uses tool-calling through APIs to execute commands or gather data, and finally closes the loop by applying fixes without human intervention. On the CCNA 200-301 v2 exam, this tests your understanding of how automation shifts from passive monitoring to active, self-healing networks—a common trap is confusing agentic AI with simple scripted automation or assuming closed-loop remediation always requires human approval. Remember the mnemonic “ACT”: Autonomous decisions, Calling tools via APIs, and Closed-loop remediation.
CCNA AI and Network Operations Practice Question
This 200-301 practice question tests your understanding of ai and network operations. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Which THREE of the following best describe how agentic AI is used in network automation, specifically regarding AI agents, tool-calling, and closed-loop remediation workflows?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs.
Options A, C, and D are correct because agentic AI in network automation involves autonomous decision-making (A), tool-calling to execute network commands or gather data (C), and closed-loop remediation that continuously monitors, diagnoses, and applies fixes automatically (D). Options B and E are incorrect because they contradict the autonomous nature of agentic AI: B describes a passive monitoring system with human-only remediation, and E states that closed-loop remediation always requires human approval, which is not true for full closed-loop automation.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs.
Why this is correct
This is a key feature of agentic AI: agents use reasoning to select and call tools (e.g., show commands, configuration APIs) to gather data or make changes.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
AI agents only monitor network traffic and alert humans for any remediation actions.
Why it's wrong here
This describes traditional monitoring, not agentic AI. Agentic AI agents take action themselves, not just alert.
- ✓
Tool-calling in agentic AI allows the agent to execute network commands or scripts to collect data and implement changes.
Why this is correct
Tool-calling is a core mechanism where the AI agent invokes external functions (e.g., netmiko, RESTCONF) to perform network operations.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
A closed-loop remediation workflow continuously monitors network state, detects anomalies, triggers an AI agent to diagnose, and applies corrective actions automatically.
Why this is correct
This defines the closed-loop process: monitor, detect, diagnose, act, and verify, all automated without human in the loop.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Closed-loop remediation always requires a human to approve each corrective action before it is executed.
Why it's wrong here
Closed-loop implies automation without manual approval; human approval would break the loop.
Option-by-option analysis
Why each answer is right or wrong
Understanding why wrong answers are wrong — and when they would be correct — is what separates a 750 score from a 900. The 200-301 exam frequently reuses these exact scenarios with slightly different constraints.
✓AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs.Correct answer▾
Why this is correct
This is a key feature of agentic AI: agents use reasoning to select and call tools (e.g., show commands, configuration APIs) to gather data or make changes.
✗AI agents only monitor network traffic and alert humans for any remediation actions.Wrong answer — click to see why▾
Why this is wrong here
This option describes traditional monitoring systems that only alert humans, not agentic AI which takes autonomous actions. Agentic AI agents do not just alert; they actively diagnose and remediate issues.
Why candidates choose this
Students may confuse agentic AI with standard monitoring tools that generate alerts, but agentic AI goes beyond alerting to autonomous action.
✗Closed-loop remediation always requires a human to approve each corrective action before it is executed.Wrong answer — click to see why▾
Why this is wrong here
Closed-loop remediation implies full automation without manual approval; requiring human approval breaks the loop and defeats the purpose of autonomous remediation. The workflow is designed to act automatically.
Why candidates choose this
Students might think human oversight is always required for safety, but closed-loop automation is specifically designed to operate without manual intervention.
Analysis generated from the official 200-301blueprint and verified against question context. The “when correct” sections are what AI assistants cite when candidates ask “what’s the difference between these options?”
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between passive monitoring and active autonomous remediation; the trap here is that candidates may confuse agentic AI with simple alerting systems, forgetting that agentic AI must include decision-making and tool execution, not just notification.
Detailed technical explanation
How to think about this question
Under the hood, agentic AI in network automation often uses a reasoning engine (e.g., a large language model or rule-based system) that parses network state from YANG-modeled data (via NETCONF/RESTCONF) and selects tool calls from a predefined function library—such as 'execute_ping', 'get_interface_stats', or 'apply_acl'. In a real-world scenario, if a link flaps, the agent might call a tool to check interface errors, then another to adjust OSPF cost, all within a closed loop that validates the change before committing, preventing human error.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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AI and Network Operations — study guide chapter
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AI and Network Operations practice questions
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FAQ
Questions learners often ask
What does this 200-301 question test?
AI and Network Operations — This question tests AI and Network Operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: AI agents can autonomously decide which network troubleshooting steps to perform and invoke appropriate tools via APIs. — Options A, C, and D are correct because agentic AI in network automation involves autonomous decision-making (A), tool-calling to execute network commands or gather data (C), and closed-loop remediation that continuously monitors, diagnoses, and applies fixes automatically (D). Options B and E are incorrect because they contradict the autonomous nature of agentic AI: B describes a passive monitoring system with human-only remediation, and E states that closed-loop remediation always requires human approval, which is not true for full closed-loop automation.
What should I do if I get this 200-301 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 more ways this is tested on 200-301
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. Drag and drop the following steps into the correct order for an agentic AI system to remediate a network performance issue using Cisco IOS-XE CLI commands.
hard- ✓ A.Enter global configuration mode, diagnose interface with 'show interfaces', apply QoS policy, enable SNMP monitoring, verify with 'show running-config'.
- B.Enable SNMP monitoring, enter global configuration mode, apply QoS policy, diagnose interface with 'show interfaces', verify with 'show running-config'.
- C.Apply QoS policy, enter global configuration mode, diagnose interface with 'show interfaces', enable SNMP monitoring, verify with 'show running-config'.
- D.Enter global configuration mode, apply QoS policy, diagnose interface with 'show interfaces', enable SNMP monitoring, verify with 'show running-config'.
Why A: The agent first enters configuration mode, then diagnoses the interface, applies QoS, enables monitoring, and finally verifies the changes.
Last reviewed: Jun 11, 2026
This 200-301 practice question is part of Courseiva's free Cisco certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the 200-301 exam.
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