3OpenAI Blog·
OpenAI publishes enterprise guidance on managing AI investments in the agentic era
OpenAI published a blog post advising enterprises on how to manage AI investments as agentic workflows become central, framing the key metric as 'useful work per dollar' rather than traditional cost measures. The post covers efficiency improvement and scaling of high-value agentic workflows. While light on technical substance, it signals OpenAI's positioning toward enterprise buyers evaluating agentic ROI.
Related guides (3)
Related events (8)
The next phase of enterprise AI
OpenAI published a blog post outlining its vision for the next phase of enterprise AI adoption, highlighting products including Frontier, ChatGPT Enterprise, Codex, and company-wide AI agents. The post signals accelerating enterprise deployment across industries. The announcement appears to frame OpenAI's strategic positioning in the enterprise market as agentic capabilities mature.
OpenAI CFO introduces practical AI ROI scorecard framework
Sarah Friar, CFO of OpenAI, published a framework for measuring AI return on investment using four metrics: useful work, cost per successful task, dependability, and return on compute. The piece is positioned as practical guidance for organizations evaluating AI deployments. It signals OpenAI's interest in shaping enterprise adoption narratives around measurable business outcomes.
The State of Enterprise AI 2025 Report
OpenAI has published a report summarizing key findings from its enterprise customer data, highlighting accelerating AI adoption, deeper integration into workflows, and measurable productivity gains across industries in 2025. The report draws on OpenAI's own enterprise deployment data rather than third-party surveys. It serves as both a market signal and a strategic communication about the business traction of OpenAI's enterprise offerings.
A Guide to Which AI to Use in the Agentic Era
A tier-2 commentary piece from One Useful Thing offering guidance on selecting AI systems in the current agentic era, signaling a shift in framing from chatbots to agents as the primary use-case paradigm. The piece appears to survey the landscape of available AI tools and their appropriate applications. As a practitioner-oriented guide, it reflects the growing complexity of the AI tooling ecosystem as agentic capabilities proliferate.
MIT Technology Review: Enterprise confidence in agentic AI as a strategic ROI driver in 2026
MIT Technology Review frames 2026 as an inflection year for enterprise AI investment, citing Gartner's characterization of the moment as one where organizations must align AI projects with strategic business objectives. The piece focuses on agentic AI as the primary vehicle for delivering measurable financial outcomes. It reflects growing executive-level pressure to demonstrate ROI from AI deployments.
Real AI Agents and Real Work
A commentary piece from One Useful Thing examining the practical deployment of AI agents in real work contexts, framing the tension between human-centered work and AI-generated productivity outputs. The piece appears to analyze how autonomous AI agents are changing knowledge work workflows. Published by a Tier 2 source known for applied AI analysis aimed at practitioners and researchers.
OpenAI publishes vision statement on AGI access, safety, and shared prosperity
OpenAI published a blog post outlining their vision for ensuring AGI benefits everyone, with a focus on access, safety, and shared prosperity. The post appears to be a high-level strategic and philosophical statement rather than a technical announcement. As a tier-1 source from OpenAI, it signals the company's public positioning on AGI governance and mission framing.
Rethinking Organizational Design in the Age of Agentic AI
A MIT Technology Review commentary examines the gap between enterprise ambition and readiness for agentic AI adoption, citing survey data showing 85% of organizations want to be agentic within three years but 76% say their current infrastructure cannot support that transition. The piece focuses on organizational design challenges—people, processes, and workflows—as the primary barriers to agentic AI deployment at scale.