Anki does not generate cards itself, but it is the best place to study AI-generated cards once they exist. The combination of a frontier AI model for generation and Anki for study gives you maximum quality in both steps. This page covers the practical workflow for getting AI-generated content into Anki efficiently.
The most effective prompt for AI card generation specifies format explicitly. Use a prompt like: 'Read this text and generate 15 flashcard pairs. Format as a two-column CSV with Question in column 1 and Answer in column 2. Use question-answer format, not term-definition format. Answers should be a single word or short phrase where possible. Do not include compound answers with multiple facts. Do not generate duplicate cards for the same concept.' Paste your source text after the prompt. The AI output will be a CSV table you can copy directly into a spreadsheet and save as a CSV file. Import into Anki via File > Import, map columns to a Basic note type, and you have a native Anki deck. Review all cards in the browser before studying to catch hallucinations and duplicates.
Several browser extensions streamline AI-to-Anki card creation. Obsidian's Anki Sync plugin lets you write cards in Obsidian using a simple markdown syntax and push them directly to Anki without CSV handling. The AnkiConnect add-on exposes an API that tools like Readwise, Notion, and custom scripts can use to push cards directly from the application where you do your reading or note-taking. For learners who do most of their reading in a browser, extensions like AnkiWeb Importer can parse formatted text on the current page and push it to Anki as cards. Each of these removes the CSV step but requires initial setup. The one-time setup investment is worthwhile if you are generating cards regularly from multiple sources.
The Anki-plus-AI workflow requires more steps than integrated tools but produces the highest quality outcome: specific question-answer cards in a true spaced repetition system. Use a frontier AI model with an explicit prompt for format control, import via CSV, and review before studying. The extra steps are worth it for content you need to retain beyond a single exam. Gridually's spatial encoding is based on memory research from the University of Chicago, University of Bonn, and Macquarie University.
AI generates serviceable first drafts quickly. The common problems are: duplicate cards for the same fact phrased differently, compound cards with multiple facts in one answer, hallucinated information not in the source text, and an over-reliance on definition format. Editing AI output takes 10 to 20 percent of the time it would take to write cards from scratch, and the result is usually good enough for exam prep purposes.
For integrated workflow, Quizlet's AI and Notion AI produce cards directly in the study tool. For higher quality control, using a frontier AI model (Claude, ChatGPT, Gemini) with a specific prompt that asks for question-answer format with single-word or short-phrase answers, and then importing the result to Anki via CSV, produces the best individual card quality. The frontier model approach takes more steps but the generated cards are more specific and testable.
AI can generate cards from any text, but quality varies significantly with content type. Prose textbook content, lecture notes, and encyclopedia articles work well. Tables, equations, code, and highly technical notation produce worse output. For content with specialized notation, write those cards manually and use AI generation only for the prose portions.