Practice Artificial Intelligence MCQs with answers. AI basics, machine learning, NLP, expert systems & more — fully solved for 2026 exams. These MCQs are perfect for NTS, PPSC, FPSC, CSS, OTS, UPSC, GATE, UGC NET, bank exams, university exams, and job interviews. The bold green option ✅ is the correct answer.
AI Basics
1. AI stands for:
a) Automatic Integration b) Artificial Intelligence ✅ c) Applied Internet d) Advanced Input
2. The father of AI is:
a) Alan Turing b) John McCarthy ✅ c) Elon Musk d) Tim Berners-Lee
3. The Turing Test determines:
a) Hardware speed b) If a machine can exhibit human-like intelligence ✅ c) Network security d) Programming skills
4. Which is an application of AI?
a) All of the below ✅ b) Self-driving cars c) Virtual assistants d) Medical diagnosis
Machine Learning
5. Machine Learning is:
a) Programming rules b) Systems learning from data without explicit programming ✅ c) A hardware technology d) A database
6. Supervised learning requires:
a) No data b) Labeled training data ✅ c) Only images d) Unlabeled data
7. Unsupervised learning is used for:
a) Classification b) Clustering and finding patterns in unlabeled data ✅ c) Supervised tasks d) Hardware optimization
Deep Learning & NLP
8. Deep Learning uses:
a) Decision trees b) Neural Networks with multiple layers ✅ c) Simple formulas d) Spreadsheets
9. NLP stands for:
a) New Learning Program b) Natural Language Processing ✅ c) Network Layer Protocol d) Neural Logic Programming
10. ChatGPT is an example of:
a) Computer virus b) Database c) Large Language Model / Generative AI ✅ d) Operating system
11. A neural network is inspired by:
a) Computer circuits b) The human brain ✅ c) Internet protocols d) File systems
⚡ AI Applications
12. An Expert System mimics:
a) A gaming console b) Decision-making of a human expert ✅ c) A type of virus d) A web browser
13. Computer Vision enables computers to:
a) Process audio b) Interpret visual information from images/videos ✅ c) Edit text d) Manage databases
14. Reinforcement Learning trains AI through:
a) Labeled data b) Rewards and penalties ✅ c) Unsupervised clustering d) Manual programming
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