Who gets to decide that isn\u2019t a side issue<\/a>\u2014it\u2019s the core. And between no AI at all and handing everything over to a big corporation, there\u2019s a middle way. It\u2019s not nearly as complicated as it sounds.<\/p>\n\nThe second hurdle: it has to work day to day<\/h2>\n\n
So it doesn\u2019t sound too easy, here\u2019s an honest warning. There\u2019s a second hurdle, and it has nothing to do with protecting data\u2014it\u2019s about everyday reality. An AI is a bit like a new employee. It needs onboarding, well-structured information, and clear tasks that fit your business. Without that groundwork, it goes wrong. And that happens often.<\/p>\n\n
Depending on the study, between 70 and over 90 out of 100 AI projects in companies end up delivering nothing. They either don\u2019t make money or never really land in day-to-day operations. The RAND research group in the US puts it at around 80 out of 100; a well-known MIT study even puts it at 95 with no noticeable effect. The reason is almost always the same: in the demo, everything shines. In real life\u2014with real data and real processes\u2014it collapses. What matters isn\u2019t the prettiest demo, but the preparation and the place where the whole thing runs. We\u2019ve built up this experience over years with open software<\/a>.<\/p>\n\nThe middle way: your own AI<\/h2>\n\n
The goal is your own AI\u2014one that nobody else can access, that belongs to you, and that you control. Not one where your data goes in at the front and eventually comes back out at someone else\u2019s. That\u2019s exactly what we build at Aivie for small and mid-sized companies. Instead of renting from a big provider and putting your data into a shared pool, you get your own space\u2014tailored to what you actually need.<\/p>\n\n