{"id":47183,"topic":"ai","source":"Harvard Business Review","title":"Don’t Let AI Make Bad Analytics Worse - Harvard Business Review","url":"https://hbr.org/2026/07/dont-let-ai-make-bad-analytics-worse","url_hash":"23499806ecee1b2480534416cbb100f888606eea","author":"","summary":"<a href=\"https://news.google.com/rss/articles/CBMibEFVX3lxTE1WbkhWaDhSbzlzaDRCNVZRaEh5X3YwVXhtN0ZZOTBsbk56ZnhXbzNvRzRuYnVabzlUUzNOQjQ4M1Z5M0I4akgzdS1URGFwdTVxUWJ4alBYeTI1LTB2NWxob3lKNy1KNG8zdFprYg?oc=5\" target=\"_blank\">Don’t Let AI Make Bad Analytics Worse</a>&nbsp;&nbsp;<font color=\"#6f6f6f\">Harvard Business Review</font>","content":"Summary.\nAI is making data analysis faster and more accessible, but it can also amplify flawed reasoning by producing more answers to the wrong questions. Organizations can avoid that trap by buildingMost companies are building AI analytics as an access problem: How do we let more people ask more questions of more data? But that’s the wrong starting point. 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