OpenAI announces that more than 1 million business customers use its tools directly for everyday work. Surprised? If you think of banks, stores, labs and digital platforms, there are already big companies — like AMEX, Cisco, Target and Thermo Fisher Scientific — integrating AI into operations and customer experiences.
What OpenAI announced and why it matters
The main news is clear: more than 1 million organizations actively pay for OpenAI solutions, either with ChatGPT for Work or by consuming models from its developer platform. That makes OpenAI the fastest-growing enterprise platform in history, according to their own statement.
Why is this relevant to you, entrepreneur or professional? Because when a technology scales like this, internal processes change: pilots get shorter, deployments face less friction, and many companies are already reporting ROI.
Key data highlighted in the announcement:
- 800 million weekly users in the ChatGPT experience, which accelerates enterprise adoption.
- 7 million seats of
ChatGPT for Work, growing 40% in two months.ChatGPT Enterpriseseats grew 9x year-over-year.
Tools and improvements that are driving adoption
OpenAI lists several capabilities launched to move teams from testing to production faster:
-
Company knowledge: lets ChatGPT reason using enterprise tools like Slack, SharePoint, Google Drive and GitHub, backed by a version of
GPT-5optimized for working with tools and providing citations. So you can ask it to find the latest contract in SharePoint and summarize key clauses. -
Codex: a model for generating and refactoring code; its use rose 10x since August. Cisco, for example, cut code review time by 50% and shortened projects from weeks to days.
-
AgentKit: makes it easier to build and deploy enterprise agents. Carlyle reported that the AgentKit evaluation platform reduced development time by more than 50% and improved agent accuracy by 30%.
-
Multimodal and real-time: from the Image Generation API and Sora 2 for visual and video creation, to
gpt-realtimeand the Realtime API for voice agents in production. Combined, these let you work with text, images, video and audio in a single flow.
Concrete cases and measurable results
Not everything is promise: there are concrete numbers.
-
A Wharton study shows 75% of companies report positive ROI and less than 5% see negative returns. That aligns with what OpenAI observes in the field.
-
Indeed uses OpenAI APIs in its Invite to Apply feature and gets 20% more applications and 13% more hires.
-
Lowe's equips staff across more than 1,700 stores with Mylow Companion, an in-store app powered by OpenAI models.
-
Intercom accelerated its development cycles from quarters to days by using OpenAI as the base for its customer service agent.
-
Databricks integrates OpenAI intelligence where enterprise data already lives, making it easier to build high-quality agents.
Also, popular platforms and apps are connecting their products to ChatGPT: Canva, Figma, Zillow and Spotify, among others. In conversational commerce, players like Shopify, Etsy, Walmart, PayPal and Salesforce are building new experiences through the Agentic Commerce Protocol.
What does this mean for small businesses or for you?
If you run an SMB or work in product, this raises practical questions: is it worth integrating AI now? how much should you invest in infrastructure and governance? The good news is consumer mass adoption reduces friction. Pilots are faster because users already know the interface, and there are templates and tools that speed up production.
However, it’s not automatic magic. Real value appears when you pick clear use cases, care for data quality, and put in place security and compliance measures.
What to watch in 2026
OpenAI says this is just the beginning and aims to rethink the operating system of work. In 2026 watch for:
- How real productivity metrics evolve beyond initial ROI.
- What regulatory frameworks emerge and how they affect enterprise deployments.
- Competition in multimodal models and agents ready for production.
If you already work with AI, use the new integrations to standardize processes. If you haven’t started yet, begin with a small, measurable use case: customer service, automating repetitive tasks, or decision support.
Mass adoption also brings responsibility: transparency, quality measures and human oversight remain essential.
Original source
https://openai.com/index/1-million-businesses-putting-ai-to-work
