# 𝗨𝗻𝗽𝗼𝗽𝘂𝗹𝗮𝗿 𝗼𝗽𝗶𝗻𝗶𝗼𝗻: 𝗠𝗼𝘀𝘁 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗰𝗼𝗻𝗳𝘂𝘀𝗲...
Canonical: https://social-archive.org/tgroenwals/IDudZVjWG6
Original URL: https://www.linkedin.com/posts/andreashorn1_%F0%9D%97%A8%F0%9D%97%BB%F0%9D%97%BD%F0%9D%97%BC%F0%9D%97%BD%F0%9D%98%82%F0%9D%97%B9%F0%9D%97%AE%F0%9D%97%BF-%F0%9D%97%BC%F0%9D%97%BD%F0%9D%97%B6%F0%9D%97%BB%F0%9D%97%B6%F0%9D%97%BC%F0%9D%97%BB-%F0%9D%97%A0%F0%9D%97%BC%F0%9D%98%80-share-7460573018331967488-VisM/
Author: Andreas Horn
Platform: linkedin
## Content
𝗨𝗻𝗽𝗼𝗽𝘂𝗹𝗮𝗿 𝗼𝗽𝗶𝗻𝗶𝗼𝗻: 𝗠𝗼𝘀𝘁 𝗰𝗼𝗺𝗽𝗮𝗻𝗶𝗲𝘀 𝗰𝗼𝗻𝗳𝘂𝘀𝗲 𝗔𝗜 𝗮𝗱𝗼𝗽𝘁𝗶𝗼𝗻 𝘄𝗶𝘁𝗵 𝗔𝗜 𝗶𝗺𝗽𝗮𝗰𝘁. They measure the easy stuff. They just track usage. → How many employees logged in. → How many prompts were written. → How many tokens were consumed. → How many Copilot licenses were activated. That is not impact. That is activity. The real question is different: → Did AI increase revenue? → Did it shorten time to value? → Did it reduce manual handoffs? → Did it free up workforce capacity? → Did it improve customer satisfaction? Most companies do not have an AI adoption problem. They have an AI accounting problem. They cannot clearly show where value is created, who owns it, how it compounds, and when it becomes measurable. You do not scale AI because people are excited. And you do not scale AI because people “use” it. Adoption matters (still), of course. But adoption is only the starting point. The much more important questions is whether AI creates value that is measurable, repeatable, and attributable. Clare Kitching nicely summarized below a practical set of KPIs to start measuring AI impact more seriously. ↓ 𝗜𝗳 𝘁𝗵𝗶𝘀 𝘄𝗮𝘀 𝘂𝘀𝗲𝗳𝘂𝗹, 𝘆𝗼𝘂 𝗺𝗮𝘆 𝗮𝗹𝘀𝗼 𝗲𝗻𝗷𝗼𝘆 𝗺𝘆 𝗳𝗿𝗲𝗲 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://lnkd.in/dbf74Y9E