Discover how leaders can build AI-ready organizations using clear strategy, training, governance, and accelerated innovation.
Meeting the demands of the Intelligence Age will require strategic investment in energy and infrastructure. OpenAI’s submission to the White House details how expanding capacity and workforce readiness can sustain U.
Five AI value models show how leaders can sequence AI from workforce fluency to process reinvention and build durable business advantage.
The paper examines how a large embedded systems company is transitioning to an AI‑first organization, focusing on the role of autonomous AI agents in software engineering. Through a mixed‑method study involving 40 workshop participants—scrum masters, architects, managers, and product owners—the authors identify expected impacts on team structure, required competencies, organizational strategies, and developer roles. The study concludes with a concrete roadmap and discusses implications for federated AI team formation, human‑in‑the‑loop practices, and sustainable AI adoption in embedded software engineering.
Innovations for global enterprises solving the world’s hardest problems.
arXiv:2607. 07612v1 Announce Type: cross Abstract: Artificial intelligence is rapidly evolving from generative systems to agentic AI capable of autonomously planning and executing tasks.
Explore our ambitious, people-first industrial policy ideas for the AI era—focused on expanding opportunity, sharing prosperity, and building resilient institutions as advanced intelligence evolves.
Sam Altman has written that we are entering the Intelligence Age, a time when AI will help people become dramatically more capable. The biggest problems of today—across science, medicine, education, national defense—will no longer seem intractable, but will in fact be solvable.
OpenAI has grown a lot. We remain focused on the same core—pursuing frontier AI research that accelerates human progress–but we now also deliver products used by hundreds of millions of people.
OpenAI’s latest line of reasoning models will be used by nation’s leading scientists to drive scientific breakthroughs.
A data-driven look at enterprise AI adoption, showing how organizations move from experimentation to real productivity gains and new capabilities.
How enterprises scale AI: from early experiments to compounding impact through trust, governance, workflow design, and quality at scale.
Now is a good time to start thinking about the governance of superintelligence—future AI systems dramatically more capable than even AGI.