How tarot readers are using AI – and what it says about our growing reliance on chatbots for emotional support and advice

· Source: Artificial intelligence (AI) – The Conversation · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Social Sciences & Behavioral Studies · Depth: Fundamental Awareness, short

Summary

A study published in April 2026 investigated how tarot readers are integrating AI into their interpretive practices, revealing a tension between seeking definitive answers and using AI for critical engagement. Tarot, which originated as an Italian Renaissance card game and evolved into a spiritual tool, has seen a resurgence, with a 2025 Pew Research survey indicating nearly 1 in 3 Americans consult such tools annually, largely driven by Gen Z and social media. The research, based on interviews with 12 tarot practitioners, found that while some used AI to simplify complex interpretations and gain confidence, others leveraged it to challenge personal biases and generate alternative perspectives. This adoption highlights AI's growing role as a "modern oracle" for personal guidance, but also raises concerns about emotional dependence and the potential for AI to undermine intuition if not used reflectively.

Key takeaway

For AI scientists developing personal guidance systems, you should prioritize designs that foster critical engagement and self-reflection over those that merely provide definitive answers. Focus on features that help users challenge their own assumptions and explore multiple perspectives, rather than promoting emotional dependence or a "yes man energy." Your goal should be to enhance human intuition, not replace it, ensuring the technology serves as a tool for deeper self-understanding.

Key insights

AI is increasingly used for personal guidance, including tarot interpretation, balancing definitive answers with critical self-reflection.

Principles

Method

Researchers interviewed 12 tarot practitioners about their use of AI in self-readings to understand delegation patterns and AI's influence on interpretations, observing both direct interpretation and bias challenging applications.

In practice

Topics

Best for: AI Scientist, AI Ethicist, Research Scientist, General Interest

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Editorial summary, takeaway, and curation by AIssential. Original article published by Artificial intelligence (AI) – The Conversation.