OpenAI's introduction of apps inside ChatGPT in October 2025 marks a fundamental transformation in how businesses reach customers. With over 800 million weekly users, the comparison to the 2008 App Store launch is inevitable.
But for most businesses, that comparison is dangerous.
In 2008, the goal was to get a user to download your app and live in your ecosystem. In this new shift, the goal is to keep the user inside ChatGPT.
This creates a "Zero-Click Reality": users might utilize your product without ever visiting your website.
So, is building a ChatGPT App a win for your business, a win for OpenAI, or a potential trap? Here is the full breakdown of the opportunity, the risks, and the actual engineering required based on our internal investigation.
ChatGPT Apps are interactive applications that run natively inside ChatGPT conversations, invoked by natural language commands and surfaced contextually when relevant. Instead of users jumping between tabs—opening ChatGPT, then your app, then back—they accomplish tasks in a single, continuous conversation.
The experience is deceptively simple. A user types "Spotify, make a playlist for my dinner party on Friday," and the Spotify interface materializes within the chat. They can browse songs, create playlists, and share them—all without leaving the conversation. Similarly, someone asking "Zillow, find apartments in Seattle under $2,500" sees interactive property listings rendered inline, complete with maps and filtering options.
Early launch partners include Booking.com, Canva, Coursera, Expedia, Figma, Spotify, and Zillow, representing a diverse spectrum from creative tools to commerce platforms to educational services. Each demonstrates how apps can deliver specialized functionality at the exact moment users need it.
Building a ChatGPT App isn't like building a traditional web or mobile application. The architecture is fundamentally different, and understanding these differences is essential before committing resources.
At the core of every ChatGPT App lies an MCP server—the bridge between your backend logic and ChatGPT's conversational interface. The MCP server exposes tools that the model can call, enforces authentication, and packages both structured data and component HTML that ChatGPT renders inline.
Developers can choose between two official SDKs: Python (ideal for rapid prototyping with FastMCP) or TypeScript (suitable for Node/React stacks). Both support standard frameworks like FastAPI and Express.
Tools define what your app can do and how ChatGPT should invoke it. A well-structured tool includes:
These descriptors determine how naturally ChatGPT can recommend your app. Poor tool design leads to apps that are never surfaced, even when relevant.
While ChatGPT handles the conversation, your app controls its visual interface. Components are typically React-based, run inside an iframe, communicate with the host via the window.openai API, and render inline with the conversation. They should be lightweight, responsive, and focused on a single task.
Users connect their accounts through OAuth 2.1 flows with explicit consent dialogs that enumerate requested data access. First-time use triggers a permissions prompt with clear disclosures, and subsequent tool calls honor granted scopes. This creates transparency but also adds friction—users must trust your app with their data before experiencing its value.
Production-ready ChatGPT Apps require HTTPS endpoints for secure communication, properly bundled UI components with correct MIME types, and secure management of API keys and environment variables through secret managers. During development, tools like ngrok enable local testing.
Let's start with the most sobering statistic. A major study of 973 e-commerce sites analyzing $20 billion in revenue found that ChatGPT referral traffic accounted for only 0.2% of total sessions—roughly 200 times smaller than Google Organic traffic.
A separate analysis of 13,770 domains across 10 industries found that AI referrals overall represent about 1% of website traffic, with ChatGPT driving 87.4% of those AI referrals.
This creates an immediate strategic question: if users aren't clicking through to your website, how do you measure success?
While volume is low, traffic referred by ChatGPT had a conversion rate of 11.4%, compared to just 5.3% for organic search. Users who do transact show significantly higher intent.
Conversion rates are improving month over month, but average order value is shrinking: LLMs are learning to close snack-sized purchases like $19 accessories, not $900 sofas. This pattern suggests ChatGPT excels at low-friction, impulse purchases rather than considered, high-ticket transactions.
But these metrics only tell half the story. The reason referral traffic remains low is often because the user's journey no longer requires a destination. This creates the 'Stay-in-Chat' dynamic.
This means users accomplish what they need without leaving ChatGPT, and has profound implications depending on your business model.
For transaction-based businesses (retail, booking platforms, tools with consumption pricing), this can be a win. While specific conversion lift data for the Agentic Commerce Protocol is still emerging, the reduction of friction by enabling instant checkout within ChatGPT has the potential to dramatically increase conversion rates. By removing friction (no clicking out, no logging in, no entering payment details) drop-off points are eliminated.
For interface-based businesses (SaaS dashboards, ad-supported content), the dynamic is concerning. Industry analysts identify a "cannibalization" risk where users accomplish 80% of their work inside ChatGPT, questioning why they need to log into the dashboard at all.
Real estate agents noted that Zillow's integration keeps users in the chat for discovery and comparison, traditionally the stickiest part of their app, reducing time spent on the broker's actual site.
Before authorizing a budget, you must determine if your business model survives the "Stay-in-Chat" dynamic.
If you decide ChatGPT Apps make sense for your business, implementation strategy determines whether you capture value or give it away.
Be intentional about what functionality lives in ChatGPT versus what requires your platform. The Canva model is instructive: allow creation and preview in ChatGPT, but require users to enter Canva for editing, customization, and exporting. The app becomes a bridge to deeper engagement, not a replacement.
Structure your app to complement rather than replace your core product. Use ChatGPT for discovery, configuration, and initial interaction—then provide clear pathways to your platform for advanced features, collaboration, or premium capabilities.
Traditional last-click attribution models systematically undervalue discovery and mid-funnel assistance. Build attribution systems that recognize ChatGPT's role in the customer journey, even when the final conversion happens elsewhere. Track assisted conversions, influence metrics, and cross-platform user journeys.
Structure your ChatGPT offerings to encourage bundles and upsells—let the AI act as a skilled salesperson. Consider how the Agentic Commerce Protocol enables merchants to maintain control as the merchant of record while ChatGPT acts as the user's agent.
Before launching, define policies about what data your app can access, who approves new features, how you monitor usage and outputs, and when humans need to be involved. Build safeguards against hallucinations and ensure you're comfortable being legally liable for what your integration does.
Don't integrate your entire product suite at launch. Choose one high-value use case, implement it rigorously, measure actual business impact, and iterate based on real data. The temptation to be "AI-first" can lead to premature commitments that undermine your core business.
At NineTwoThree, we've built AI systems for over 150 clients across industries. We understand both the technical complexity of building production-ready integrations and the strategic nuance of avoiding cannibalization traps.
Our approach starts with discovery, not code. We assess whether ChatGPT Apps make strategic sense for your business model, identify the specific use cases that drive value without undermining your core product, and design integration architectures that complement rather than replace your platform.
Then we build. Our Ph.D-level AI engineers have deep expertise in MCP protocols, conversational interfaces, and production AI systems. We implement with the rigor required for business-critical integrations: robust error handling, comprehensive monitoring, and proper security.
If you're considering a ChatGPT App and want a partner who will tell you the truth about whether it makes sense, and how to do it right if it does, let's talk.
Because in platform shifts, the difference between winners and losers isn't just speed. It's a strategy.
Yes, through proper authentication and API integration. Your MCP server can connect to internal databases, CRMs, or other systems. However, you maintain full control over what data is exposed through your tool definitions. Implement proper access controls and only expose data necessary for the app's functionality.
Currently, users can discover apps in three ways: (1) explicitly calling them by name ("Spotify, make a playlist"), (2) ChatGPT suggesting them contextually when relevant to the conversation, or (3) browsing the upcoming app directory that OpenAI plans to launch. Apps that meet higher design and functionality standards may be featured more prominently.
ChatGPT Plugins were the previous generation of integrations, focused primarily on data retrieval and simple actions. ChatGPT Apps, built on the Apps SDK, offer richer interactive UI components, better authentication flows, and more sophisticated conversational capabilities. Apps represent a complete re-architecture of the integration model.
OpenAI has announced plans for monetization through the Agentic Commerce Protocol, which enables instant checkout within ChatGPT. Merchants pay a small fee on completed purchases. Additional monetization details, including support for subscriptions and in-app purchases, will be shared as the platform matures. Currently, most apps use ChatGPT as a top-of-funnel acquisition channel, driving users to their platform for paid features.
Security depends on your implementation. All communication must use HTTPS, OAuth 2.1 handles authentication, and payment data (if using Agentic Commerce Protocol) is encrypted via Stripe or other compliant payment processors. You're responsible for securing your backend, managing API keys properly, and following OpenAI's security guidelines. The Apps SDK documentation provides detailed security requirements.
Yes, ChatGPT Apps are now available to Business, Enterprise, and Edu customers. Enterprise use cases might include internal tools, workflow automation, or customer-facing applications. However, consider whether your enterprise customers want data flowing through ChatGPT's infrastructure versus on-premise solutions.
OpenAI hasn't published specific approval timelines yet, as the submission process is still being refined. Based on early partner experiences, expect a review process similar to app stores, likely 1-2 weeks for initial review, with potential back-and-forth for revisions. Apps must meet OpenAI's usage policies, be appropriate for all audiences, and follow developer guidelines.
This is why tool descriptors and error handling are critical. Design your tools with clear, unambiguous descriptions. Implement validation in your backend to reject invalid inputs gracefully. Provide helpful error messages that ChatGPT can relay to users. During testing, identify common misunderstandings and refine your tool descriptions. Remember: ChatGPT is probabilistic, not deterministic.
The Model Context Protocol (MCP) is designed to be platform-agnostic. While the Apps SDK is specific to ChatGPT, the underlying MCP server architecture can potentially work with other AI platforms that adopt the same protocol. OpenAI and Anthropic are collaborating on MCP standards, suggesting broader compatibility in the future.
OpenAI's introduction of apps inside ChatGPT in October 2025 marks a fundamental transformation in how businesses reach customers. With over 800 million weekly users, the comparison to the 2008 App Store launch is inevitable.
But for most businesses, that comparison is dangerous.
In 2008, the goal was to get a user to download your app and live in your ecosystem. In this new shift, the goal is to keep the user inside ChatGPT.
This creates a "Zero-Click Reality": users might utilize your product without ever visiting your website.
So, is building a ChatGPT App a win for your business, a win for OpenAI, or a potential trap? Here is the full breakdown of the opportunity, the risks, and the actual engineering required based on our internal investigation.
ChatGPT Apps are interactive applications that run natively inside ChatGPT conversations, invoked by natural language commands and surfaced contextually when relevant. Instead of users jumping between tabs—opening ChatGPT, then your app, then back—they accomplish tasks in a single, continuous conversation.
The experience is deceptively simple. A user types "Spotify, make a playlist for my dinner party on Friday," and the Spotify interface materializes within the chat. They can browse songs, create playlists, and share them—all without leaving the conversation. Similarly, someone asking "Zillow, find apartments in Seattle under $2,500" sees interactive property listings rendered inline, complete with maps and filtering options.
Early launch partners include Booking.com, Canva, Coursera, Expedia, Figma, Spotify, and Zillow, representing a diverse spectrum from creative tools to commerce platforms to educational services. Each demonstrates how apps can deliver specialized functionality at the exact moment users need it.
Building a ChatGPT App isn't like building a traditional web or mobile application. The architecture is fundamentally different, and understanding these differences is essential before committing resources.
At the core of every ChatGPT App lies an MCP server—the bridge between your backend logic and ChatGPT's conversational interface. The MCP server exposes tools that the model can call, enforces authentication, and packages both structured data and component HTML that ChatGPT renders inline.
Developers can choose between two official SDKs: Python (ideal for rapid prototyping with FastMCP) or TypeScript (suitable for Node/React stacks). Both support standard frameworks like FastAPI and Express.
Tools define what your app can do and how ChatGPT should invoke it. A well-structured tool includes:
These descriptors determine how naturally ChatGPT can recommend your app. Poor tool design leads to apps that are never surfaced, even when relevant.
While ChatGPT handles the conversation, your app controls its visual interface. Components are typically React-based, run inside an iframe, communicate with the host via the window.openai API, and render inline with the conversation. They should be lightweight, responsive, and focused on a single task.
Users connect their accounts through OAuth 2.1 flows with explicit consent dialogs that enumerate requested data access. First-time use triggers a permissions prompt with clear disclosures, and subsequent tool calls honor granted scopes. This creates transparency but also adds friction—users must trust your app with their data before experiencing its value.
Production-ready ChatGPT Apps require HTTPS endpoints for secure communication, properly bundled UI components with correct MIME types, and secure management of API keys and environment variables through secret managers. During development, tools like ngrok enable local testing.
Let's start with the most sobering statistic. A major study of 973 e-commerce sites analyzing $20 billion in revenue found that ChatGPT referral traffic accounted for only 0.2% of total sessions—roughly 200 times smaller than Google Organic traffic.
A separate analysis of 13,770 domains across 10 industries found that AI referrals overall represent about 1% of website traffic, with ChatGPT driving 87.4% of those AI referrals.
This creates an immediate strategic question: if users aren't clicking through to your website, how do you measure success?
While volume is low, traffic referred by ChatGPT had a conversion rate of 11.4%, compared to just 5.3% for organic search. Users who do transact show significantly higher intent.
Conversion rates are improving month over month, but average order value is shrinking: LLMs are learning to close snack-sized purchases like $19 accessories, not $900 sofas. This pattern suggests ChatGPT excels at low-friction, impulse purchases rather than considered, high-ticket transactions.
But these metrics only tell half the story. The reason referral traffic remains low is often because the user's journey no longer requires a destination. This creates the 'Stay-in-Chat' dynamic.
This means users accomplish what they need without leaving ChatGPT, and has profound implications depending on your business model.
For transaction-based businesses (retail, booking platforms, tools with consumption pricing), this can be a win. While specific conversion lift data for the Agentic Commerce Protocol is still emerging, the reduction of friction by enabling instant checkout within ChatGPT has the potential to dramatically increase conversion rates. By removing friction (no clicking out, no logging in, no entering payment details) drop-off points are eliminated.
For interface-based businesses (SaaS dashboards, ad-supported content), the dynamic is concerning. Industry analysts identify a "cannibalization" risk where users accomplish 80% of their work inside ChatGPT, questioning why they need to log into the dashboard at all.
Real estate agents noted that Zillow's integration keeps users in the chat for discovery and comparison, traditionally the stickiest part of their app, reducing time spent on the broker's actual site.
Before authorizing a budget, you must determine if your business model survives the "Stay-in-Chat" dynamic.
If you decide ChatGPT Apps make sense for your business, implementation strategy determines whether you capture value or give it away.
Be intentional about what functionality lives in ChatGPT versus what requires your platform. The Canva model is instructive: allow creation and preview in ChatGPT, but require users to enter Canva for editing, customization, and exporting. The app becomes a bridge to deeper engagement, not a replacement.
Structure your app to complement rather than replace your core product. Use ChatGPT for discovery, configuration, and initial interaction—then provide clear pathways to your platform for advanced features, collaboration, or premium capabilities.
Traditional last-click attribution models systematically undervalue discovery and mid-funnel assistance. Build attribution systems that recognize ChatGPT's role in the customer journey, even when the final conversion happens elsewhere. Track assisted conversions, influence metrics, and cross-platform user journeys.
Structure your ChatGPT offerings to encourage bundles and upsells—let the AI act as a skilled salesperson. Consider how the Agentic Commerce Protocol enables merchants to maintain control as the merchant of record while ChatGPT acts as the user's agent.
Before launching, define policies about what data your app can access, who approves new features, how you monitor usage and outputs, and when humans need to be involved. Build safeguards against hallucinations and ensure you're comfortable being legally liable for what your integration does.
Don't integrate your entire product suite at launch. Choose one high-value use case, implement it rigorously, measure actual business impact, and iterate based on real data. The temptation to be "AI-first" can lead to premature commitments that undermine your core business.
At NineTwoThree, we've built AI systems for over 150 clients across industries. We understand both the technical complexity of building production-ready integrations and the strategic nuance of avoiding cannibalization traps.
Our approach starts with discovery, not code. We assess whether ChatGPT Apps make strategic sense for your business model, identify the specific use cases that drive value without undermining your core product, and design integration architectures that complement rather than replace your platform.
Then we build. Our Ph.D-level AI engineers have deep expertise in MCP protocols, conversational interfaces, and production AI systems. We implement with the rigor required for business-critical integrations: robust error handling, comprehensive monitoring, and proper security.
If you're considering a ChatGPT App and want a partner who will tell you the truth about whether it makes sense, and how to do it right if it does, let's talk.
Because in platform shifts, the difference between winners and losers isn't just speed. It's a strategy.
Yes, through proper authentication and API integration. Your MCP server can connect to internal databases, CRMs, or other systems. However, you maintain full control over what data is exposed through your tool definitions. Implement proper access controls and only expose data necessary for the app's functionality.
Currently, users can discover apps in three ways: (1) explicitly calling them by name ("Spotify, make a playlist"), (2) ChatGPT suggesting them contextually when relevant to the conversation, or (3) browsing the upcoming app directory that OpenAI plans to launch. Apps that meet higher design and functionality standards may be featured more prominently.
ChatGPT Plugins were the previous generation of integrations, focused primarily on data retrieval and simple actions. ChatGPT Apps, built on the Apps SDK, offer richer interactive UI components, better authentication flows, and more sophisticated conversational capabilities. Apps represent a complete re-architecture of the integration model.
OpenAI has announced plans for monetization through the Agentic Commerce Protocol, which enables instant checkout within ChatGPT. Merchants pay a small fee on completed purchases. Additional monetization details, including support for subscriptions and in-app purchases, will be shared as the platform matures. Currently, most apps use ChatGPT as a top-of-funnel acquisition channel, driving users to their platform for paid features.
Security depends on your implementation. All communication must use HTTPS, OAuth 2.1 handles authentication, and payment data (if using Agentic Commerce Protocol) is encrypted via Stripe or other compliant payment processors. You're responsible for securing your backend, managing API keys properly, and following OpenAI's security guidelines. The Apps SDK documentation provides detailed security requirements.
Yes, ChatGPT Apps are now available to Business, Enterprise, and Edu customers. Enterprise use cases might include internal tools, workflow automation, or customer-facing applications. However, consider whether your enterprise customers want data flowing through ChatGPT's infrastructure versus on-premise solutions.
OpenAI hasn't published specific approval timelines yet, as the submission process is still being refined. Based on early partner experiences, expect a review process similar to app stores, likely 1-2 weeks for initial review, with potential back-and-forth for revisions. Apps must meet OpenAI's usage policies, be appropriate for all audiences, and follow developer guidelines.
This is why tool descriptors and error handling are critical. Design your tools with clear, unambiguous descriptions. Implement validation in your backend to reject invalid inputs gracefully. Provide helpful error messages that ChatGPT can relay to users. During testing, identify common misunderstandings and refine your tool descriptions. Remember: ChatGPT is probabilistic, not deterministic.
The Model Context Protocol (MCP) is designed to be platform-agnostic. While the Apps SDK is specific to ChatGPT, the underlying MCP server architecture can potentially work with other AI platforms that adopt the same protocol. OpenAI and Anthropic are collaborating on MCP standards, suggesting broader compatibility in the future.
