TLDR;
OpenAI introduced apps inside ChatGPT and previewed tools for developers to build them. Brands can offer interactive services without customers first visiting their websites. An app is worth the investment when it completes a useful task reliably and uses customer data appropriately.
What happened
OpenAI introduced apps inside ChatGPT and an Apps SDK preview for developers. Apps can surface interactive experiences in the conversation and be invoked in relevant contexts, creating a distribution model in which customers can use a service without starting on its website.
Why it matters
An interactive experience can resolve a customer’s task inside the conversation instead of handing them another link. That makes utility, data permissions and response quality more important than a conventional landing-page pitch. The brand experience depends on what the app actually helps the user accomplish.
Conversational apps put brand services inside the assistant's environment. The attraction is access to a customer who already has a question and may be ready to act. The challenge is earning that place with something useful. An app that simply repeats public marketing copy adds another interface without resolving the customer's problem. A stronger enterprise case is a bounded service, such as helping a user interpret options or complete a supported request using accurate business information. That requires ownership of the underlying data, permissions and outcome, not just a conversational presentation. As a preview ecosystem, the launch should be treated as an opportunity to learn about a new distribution surface. It does not guarantee discovery, user adoption or a durable commercial return for every submitted experience.
How your brand can benefit / be affected
Choose one bounded customer task: finding a compatible product, assembling a shortlist or retrieving an approved account answer. Define the permitted inputs, outputs and actions, then connect the minimum data needed to complete that task accurately.
Agree ownership for content updates, API reliability and review requirements. Evaluate completion, qualified hand-offs and customer understanding, rather than app invocations alone. Build a small experience with a clear purpose before committing to a broad conversational storefront.
Define one task in terms the customer would recognise. Specify what information is required, what the service can answer and what a successful outcome looks like. If the app helps compare options, ensure it explains the differences that affect the decision rather than merely ranking products. If it accesses an account, decide what requires authentication and what permission the user is granting. Keep the scope narrow enough that the brand can support it properly. A clear boundary also makes it easier to explain when the assistant should send the customer to a person or to the existing website for the next step.
Work backwards from support and maintenance. Name the team responsible for incorrect answers, unavailable services and changes to the underlying product catalogue or policy. Plan how to withdraw or revise a capability if it stops being reliable. Measure whether users finish the chosen task and whether the resulting handoff contains enough context to be useful. Directory exposure and interaction counts can show interest, but they cannot establish service quality. Compare the app with the existing way customers complete the same task, including abandonment and support effort. Expand only when the evidence shows that the assistant interface improves an outcome the enterprise is prepared to own.
News date: 6 October 2025. Editorial review: 16 September 2026. Analysis includes subsequent developments where stated.