AI-900 Practice Question: Describe Artificial Intelligence workloads and considerations
What is the difference between narrow AI and general AI?
⚠ Common exam trap
Candidates often confuse 'narrow' with 'less capable' and choose Option A, not realizing that narrow AI is actually highly effective within its domain but fundamentally limited in scope compared to the hypothetical general AI.
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
✓
Narrow AI excels at one specific task; general AI would have human-like intelligence across all domains
Narrow AI (also called weak AI) is designed and trained to perform a single specific task, such as image recognition or language translation, while general AI (strong AI) would possess the ability to understand, learn, and apply intelligence across a wide range of tasks at a human-like level. General AI remains a theoretical concept and has not been achieved, whereas narrow AI powers virtually all current AI systems, including those on Azure like Computer Vision and Language Understanding (LUIS).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Narrow AI is more powerful than general AI
Why it's wrong here
This confuses performance on specialized benchmarks with overall capability. Narrow AI (e.g., AlphaGo) can beat humans at a defined game, but general AI would be able to learn and execute any intellectual task a human can, making it incomparably more powerful in scope. Because modern systems are narrow, they lack the flexibility and reasoning that general intelligence would possess.
- ✓
Narrow AI excels at one specific task; general AI would have human-like intelligence across all domains
Why this is correct
This correctly identifies the core distinction. Narrow AI (also called ANI) is trained for one function—such as object recognition or language translation—and cannot transfer skills across domains. General AI (AGI) would possess human-level cognitive abilities, allowing it to reason, learn, and adapt to any task, though such a system has not yet been achieved.
- ✗
Narrow AI runs on-premises; general AI runs in the cloud
Why it's wrong here
Where AI runs is an infrastructure choice, not an intrinsic property of the model. A narrow AI chatbot can be hosted on-premises for privacy, while cloud deployment is used for scalability and cost—regardless of whether the model is narrow or general. General AI remains theoretical, and neither its development nor deployment is tied to a specific hosting environment.
- ✗
Narrow AI is for businesses; general AI is for consumers
Why it's wrong here
The business/consumer split misrepresents how AI is deployed. Narrow AI like recommendation engines and voice assistants serves both enterprise workflows and individual users, and a future general AI would be equally applicable across markets. The real distinction is not who uses it but whether the system is task-limited or universally intelligent.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI-900 practice question is part of Courseiva's free Microsoft 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 AI-900 exam.