Since late 2023, custom GPTs have been the easiest way to give ChatGPT a standing job: a proposal writer with your house style, a tutor loaded with a course pack, a support helper that calls your own API. Millions were made. Plenty of teams quietly depend on a handful of them.
In September OpenAI said they are going. Their replacement is plugins, a format ChatGPT now shares with Codex. If you built a GPT, or your team relies on one somebody else built, the next two months matter. The migration button does a lot of the work. It does not do all of it.
The dates
OpenAI's help page and the coverage around it give this schedule (OpenAI's migration FAQ; Virtualization Review):
| Date | What happens |
|---|---|
| 11 September 2026 | Change announced in the ChatGPT release notes; Enterprise admins notified |
| 22 September 2026 | Target for the migration tool and in-app banner to appear in Enterprise workspaces (a target, not a promise) |
| 26 October 2026 | Planned end of new custom GPT creation in affected Enterprise workspaces. Existing GPTs keep working |
| 11 December 2026 | Scheduled retirement. Custom GPTs stop running and leave the GPT directory |
| 11 February 2027 | Latest date for Enterprise customers with an approved deferral |
OpenAI says the date shown in your own account or workspace notice can differ, so check that first. Users on r/ChatGPTPro also noticed changes rolling out from mid-September (thread).
What migrates, and what gets left behind
The built-in migration copies the parts of a GPT that are just text and files. Everything that was a setting, a connection or a relationship with users stays behind.
| Part of your GPT | After migration |
|---|---|
| Instructions | Become a skill inside the new plugin |
| Knowledge files | Copied as reference files |
| Connected apps | Added to the plugin as apps |
| Custom actions (your own API calls) | Not transferred. Rebuild with an available app or a custom MCP server |
| The model you picked | Not carried over. Enterprise workspaces get their defaults |
| Existing conversations | Not moved into the plugin |
| Sharing settings and who had access | Reset. The plugin starts private; you install and share it again |
| Drafts and unpublished edits | Ignored. Only the latest published version migrates |
Two more details catch people out. After you migrate, the original GPT becomes read-only and you cannot delete it; it simply runs until retirement. And if you only use someone else's GPT, access to it does not give you access to its replacement. You will need the creator to share the plugin with you.
What a plugin actually is
A custom GPT was a separate copy of ChatGPT with its own personality and settings. A plugin is a package of capabilities you add to ChatGPT or Codex. It can hold one or more skills (instructions plus resources for a repeatable job), an MCP server that exposes tools and outside systems, or both. ChatGPT and Codex share one plugin directory (Virtualization Review).
That is a real shift, and not everyone likes it. The most upvoted complaint on r/ChatGPTPro this month comes from someone who has built GPTs for three years. Their point: a GPT starts every chat clean, without your saved memory or personal custom instructions, which is exactly what you want for a predictable work tool. Projects and plugins solve different problems (r/ChatGPTPro). OpenAI's own guidance concedes that a migrated plugin may respond differently and asks you to retest.
So treat migration as a rebuild with a head start, not a copy.
A one-hour plan per GPT
1. Take an inventory. List every GPT you made or rely on, who uses it and how often. Retire the ones nobody has opened since spring rather than migrating them.
2. Save what will not move. Copy the instructions into a document, export the knowledge files, write down the model you chose, and note every custom action and the API behind it. Screenshot the sharing settings.
3. Write a test set before you touch anything. Eight to ten real prompts your users send, with what a good answer looks like. Run them through the old GPT now and save the answers. This is the step most people skip, and it is the only way to know whether the plugin behaves.
4. Tidy the instructions into a skill. GPT instructions often grew by accretion. A skill works best with a clear purpose, when to use it, inputs, steps only where order matters, and the output format. Our prompt library has a ready-made "Prepare a Custom GPT for Migration to a Plugin" prompt that does this rewrite and drafts the test set for you.
5. Migrate. When the option appears, go to My GPTs, choose Migrate to plugin on the GPT, review the details and follow the steps.
6. Rebuild custom actions. If an app already connects to the service, use it. Otherwise this is a job for a developer: wrap the API as an MCP server and add it to the plugin. Budget time for it, especially in Enterprise, where publishing and sharing plugins need specific admin permissions.
7. Run the test set again on the plugin, compare side by side, and adjust the skill until the answers you care about match.
8. Share it and tell people. Install, share with the same group, and send the new link. Anyone who bookmarked the old GPT will otherwise discover the change on 11 December.
If a plugin is the wrong shape
Not every GPT needs to become a plugin.
- Personal helpers with a few files may be fine as a ChatGPT Project with instructions and documents attached, as long as you are happy for your memory and custom instructions to apply.
- Shared prompts that need no files or tools can live as a prompt your team copies. A simple shared document beats a product nobody can maintain.
- Work that has to stay predictable across tools can move to an equivalent elsewhere. Claude's Projects and Skills and Google's Gems cover similar ground, and a skill written as a plain instruction file travels between assistants more easily than a GPT ever did.
Whichever route you take, keep the written instructions and test set somewhere you own. This is the second time OpenAI has replaced its extension format; the first plugin system was retired in 2024. Owning the text makes the next change cheaper.
The short version
You have until 11 December, later only with an Enterprise deferral. Instructions, files and connected apps come across in one click. Custom actions, your chosen model, conversations and sharing do not. Save those now, build a small test set, migrate, retest and reshare. For a deeper look at how agents and add-ons change your risk, our piece on what summer 2026 changed for agent security explains why pinned, reviewed plugins matter, and the AI agents directory lists the MCP tooling you may need for rebuilt actions.