At OpenAI Frontiers in San Francisco and London, we brought together leaders from across the globe to share how they’re putting AI to work across industries. Teams shared how they’re moving from experimentation to real-world deployment, using AI to rethink products, workflows, and customer experiences. We also heard from builders and executives on what it takes to bring AI into organizations responsibly, securely, and at scale. A highlight from the series: Sarah Friar and Sam Altman in conversation on what comes next as AI becomes part of how companies operate at scale. Now we're bringing Frontiers to Asia, we look forward to meeting with leaders in Tokyo and Seoul this week!
Derrick Frye
4d
This is the part that matters once an idea leaves demo mode: what happens on the 500th run when context is stale, inputs are messy, or the workflow has to say “I don’t know.” The boring checks around evals, logs, and PII boundaries are usually what make automation usable.
Excited to see how AI is rethinking customer experiences! Looking forward to the insights from Tokyo and Seoul. OpenAI
Excited to see the conversation evolving from AI experimentation to real operational transformation. The next competitive advantage won’t come from adding more tools — it will come from redesigning how revenue systems, workflows, data, and decision-making operate together in an AI-native model. AI doesn’t fix fragmented organizations. It amplifies them. That’s why governance, operational architecture, and revenue accountability matter more than ever. Looking forward to seeing how global enterprises move from isolated AI pilots to truly AI-native operating systems. 🚀
What stands out in this transition from experimentation to deployment is not just scale — but the quiet shift in responsibility AI systems are starting to assume inside organizations. As intelligence becomes operational, the question is no longer what AI can do, but how decisions remain meaningful when they are increasingly delegated to machines. We are entering a phase where computation is not enough. Context will matter just as much as capability. This is where we see the need for an Emotional Layer across Web3 and intelligent systems — ensuring that autonomy does not come at the cost of human alignment. Exploring this direction through EmotiLink OS.
AI is no longer just a concept; it’s reshaping businesses globally. From SF to London, Teams turning AI from a pilot into a core growth engine. Now, this momentum is hitting Tokyo and Seoul
L'integrazione dell'IA nei flussi di lavoro rappresenta un cambiamento epocale per le PMI. Attraverso processi strutturati, possiamo ottimizzare decisioni e operazioni, rendendo la tecnologia un alleato strategico piuttosto che un ostacolo. Guardando al futuro, l'adozione di standard aperti sarà cruciale per garantire che le soluzioni siano adattabili e sostenibili nel tempo. Insieme possiamo costruire un ecosistema dove l'innovazione diventa parte integrante della nostra quotidianità.
l’IA aumenterà la produttività? Probabilmente sì, soprattutto nelle imprese già strutturate: Stanford AI Index segnala che nel 2024 il 78% delle organizzazioni dichiarava di usare IA, contro il 55% dell’anno precedente. a chi andrà quella produttività? Al centro della piattaforma, agli investitori, ai grandi committenti? O anche alla periferia produttiva, ai distretti, ai lavoratori, ai fornitori, ai territori? Se non cambia il paradigma la periferia avrà un nuovo cottimo!
Marc Mora
3d
Le vrai sujet n’est plus de savoir si l’IA est puissante. Elle l’est déjà. Le problème est que beaucoup veulent industrialiser l’IA sans architecture de contrôle sérieuse. À grande échelle, un agent plus capable mais mal borné ne devient pas “responsable” : il devient simplement un risque mieux automatisé. C’est précisément pour cela que j’ai développé CASI : une architecture IA complète, pas un chatbot, pas une stack logicielle, pas un slogan de gouvernance. CASI traite le point critique : le passage langage humain - décision -action. Une entrée humaine n’est pas une autorité. Une sortie IA n’est pas une permission. Une recommandation n’est pas une preuve. Avant toute conséquence, il faut qualification, médiation, séparation cognition / autorité / exécution, gates, refus possible, exécution bornée, audit, fail-closed et hardware défini. Sans cela, le “déploiement responsable” reste du langage corporate. CASI pose le vrai problème : non pas rendre l’IA plus bavarde, mais rendre l’action IA contrôlable, traçable, interruptible et opposable.
Events like OpenAI Frontiers are exactly what the industry needs — real conversations between leaders who are actually deploying AI, not just theorizing. At CoreNuVate IT, we believe the most important shift happening right now is companies moving from AI experimentation to AI integration at scale. The cross-industry dialogues from San Francisco to London and Tokyo represent that evolution in real time. Excited to see the insights shared!