ChatGPT is having a major outage today. Sessions are failing to load. Prompts hang or return errors. OpenAI says it is experiencing issues and is working on a fix. I am tracking the impact in real time, and what it means for teams that now treat AI as core infrastructure.
What happened
Starting earlier today, many ChatGPT users could not start or continue chats. Some saw blank screens after login. Others could not send messages at all. The app stalled at handshake steps that usually take seconds.
OpenAI has acknowledged a service disruption affecting ChatGPT. The company has not detailed a root cause yet. There is no timeline for full restoration at the time of writing. The status page notes degraded performance and availability. Updates are ongoing as the team investigates.
If your workflows assume ChatGPT is always available, treat this as a wake up call. Build for failure, not just for speed.
What I am seeing right now
In repeated tests across multiple accounts and networks, the service behavior is inconsistent. Some requests return quickly. Others time out or show a generic error. Refreshing helps in some cases, but long sessions drop without warning.
Technical symptoms
The pattern points to a control or session layer under strain. Authentication completes, then the conversation pane fails to load state. That suggests trouble with a middle tier such as routing, rate limits, or a cache layer. It could also be a rollout gone wrong. A bad deploy often produces bursty errors, not a clean cutover. To be clear, this is informed analysis, not a confirmed cause.
What is not clear yet
We do not know if the API for developers is equally affected. We also do not know if the incident is tied to a cloud provider event, a model serving issue, or a recent feature change. OpenAI has not shared details on blast radius or mitigation steps.
There is no sign that user data is lost. This looks like availability and performance trouble, not a data integrity incident.
Why this outage matters
AI is now the front door to work for many teams. Engineers lean on ChatGPT for code help. Writers draft and edit with it. Sales and support teams use it for replies and summaries. When the door jams, everything behind it slows down.
This incident shows the risk of relying on a single AI endpoint. Traditional SaaS outages are annoying. AI outages are different. They block not just access, but the reasoning engine that powers many tasks. The more tasks you automate with prompts, the wider the impact when prompts cannot run.
How OpenAI is communicating
OpenAI flagged the issue and is posting status updates. That is good practice and helps teams gauge impact. What is missing so far is a clear scope, a probable cause, and a rough recovery plan. Even a high level signal helps, for example, authentication problems versus model serving issues. That lets customers switch to the right fallback.
When the dust settles, the postmortem will matter. Customers will want to know the root cause, what changed, and what will prevent a repeat. Clear incident classes, better regional isolation, and circuit breakers all help reduce ripple effects.
Bookmark the OpenAI status page and enable alerts. Set a simple rule. If response time jumps or errors rise, shift to a backup.
What teams should do now
- Pause non critical runs and queue them for later.
- Switch to a backup generative tool if your policy allows it.
- Keep a local library of common prompts and outputs.
- Update your runbook with a clear escalation path.
If you build on ChatGPT, add health checks around every call. Fail fast and fail safe. Cache validated outputs where you can. Consider a second model provider for high risk jobs. If that is not possible, create a “human in the loop” mode that activates during outages. Also, set internal service level goals for AI tasks. If a call exceeds that limit, route to the fallback.
Finally, talk to your compliance team. Make sure any backup tool meets your data rules. Outages are not the time to improvise with unapproved apps.
The bottom line
Today’s ChatGPT outage is a sharp reminder. AI is amazing, but it is still software that runs on fallible systems. Reliability is now the feature that matters most. OpenAI is working to restore service. Teams should work to restore resilience. The best time to plan for the next disruption is before it arrives.
