{"id":23928,"date":"2026-01-12T15:29:25","date_gmt":"2026-01-12T14:29:25","guid":{"rendered":"https:\/\/kauz.ai\/?p=23928"},"modified":"2026-04-30T15:45:18","modified_gmt":"2026-04-30T13:45:18","slug":"ai-in-companies-a-review-and-outlook-based-on-7-ai-theses","status":"publish","type":"post","link":"https:\/\/kauz.ai\/en\/blog\/ai-in-companies-a-review-and-outlook-based-on-7-ai-theses\/","title":{"rendered":"AI in companies: A review and outlook based on 7 AI theses"},"content":{"rendered":"

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Three years of generative AI in corporate practice: this phase was characterized by initial scepticism, occasional euphoria, numerous pilot projects and a steadily growing dynamic in almost all areas of the company. We are experiencing a time of profound change. It is becoming increasingly clear that companies that had the courage early on to systematically test and expand the use of artificial intelligence are now creating measurable advantages for themselves – be it through efficiency gains, new scope for action or at least the ability to remain economically stable during one of the longest periods of recession. AI will remain the dominant field of activity for many companies in 2026, but will be the subject of increasingly controversial debate. Above all, the requirements are increasing: Pure demos and error-prone agents are no longer enough. Users and companies expect reliable, productive results. <\/span><\/p>\n

Based on leading studies on the use of AI in companies and supplemented by our own practical experience at Kauz.ai, we dedicate this blog post to the following questions:<\/span><\/p>\n