OpenAI just quietly launched something that could change everything: apps inside ChatGPT. If you missed it, the new release lets third-party developers build interactive tools that live right inside ChatGPT, things like browsing Zillow listings, designing in Canva, taking a Coursera course, or even booking travel with Expedia. That’s a pretty wild shift for what started as just a chatbox.

Under the hood, an app today is still pretty simple: it’s auth, an MCP server, and a UI layer. (As Gadget’s technical write-up explains, ChatGPT apps require an MCP implementation, a UI-rendering extension, and OAuth 2.1 / OIDC support to authenticate with your backend.) But the fact that OpenAI added real UI components, and is hand-picking early APIs to invest in, feels like a signal: this is the start of a true app ecosystem, not just a plugin marketplace.

So let’s talk about what that means, and where the real opportunities might be.

Why the ChatGPT app ecosystem matters

ChatGPT is already used by a lot of people, around 800 million weekly users, according to OpenAI. It’s one of the few products that’s equally at home in both your workday and your personal life. People use it to brainstorm marketing copy, debug code, help their kids with homework, or write their wedding vows.

That makes it fundamentally different from almost every platform that came before. It’s not just business software or entertainment software, it’s everything software. Which means both B2B and B2C apps have room to thrive here.

The obvious early winners: Big SaaS

The first wave of apps will almost certainly come from big SaaS players like Shopify, Notion, Google Workspace, QuickBooks, and HubSpot.

Their playbook is straightforward: take parts of their existing product and surface them inside ChatGPT so users don’t have to context-switch. Imagine:

• Shopify letting merchants check orders, edit product listings, or even complete a purchase right in chat.
• Google Docs showing your recent documents inline, letting you summarize or edit them conversationally.
• QuickBooks or Wave enabling small business owners to query cash flow, send invoices, or file receipts with natural language.

That kind of convenience alone will win users. These companies already have massive audiences, and ChatGPT simply brings those experiences closer together.

Some things won’t make sense yet though. For domains where latency, privacy, or compute cost matter, like high-frequency trading or real-time gaming, running inside ChatGPT isn’t practical because ChatGPT sits in the cloud and messages flow through OpenAI’s infrastructure. That introduces delays, extra routing overhead, and makes it harder to guarantee data control. Apps that rely on millisecond-level response times or on fully private on-prem data just can’t live comfortably inside that architecture, at least for now.

The murky frontier: New consumer apps

For indie devs and new startups, things are a lot less clear. How people will actually spend time inside ChatGPT is still evolving.

Right now, it’s more transactional. You pop in, ask a question, get an answer, and leave. It’s not yet the kind of “always-on” platform that your phone or social feeds are. That makes it tricky to predict what kinds of consumer apps will stick.

Will we see social media or games pop up here? Maybe, but it’s a tough sell when those categories already thrive on mobile. Unless someone figures out a uniquely AI-native experience, something that feels better inside ChatGPT than on your phone, it’ll be hard to compete.

That said, there’s a bold, speculative bet available: be early. If OpenAI really does ship hardware (which feels more likely by the month) and that hardware starts to challenge the smartphone’s dominance, the app landscape could reset overnight. Whoever built the “first wave” of great ChatGPT apps will already be in position.

The B2B side: Where it gets interesting

If you’re thinking in enterprise terms, the big SaaS companies will again move fastest. Salesforce, HubSpot, Asana, and others will all build official apps.

So where’s the space for everyone else?

One clear opportunity is connectors and integration layers. There are thousands of SaaS tools that will be slow to build ChatGPT apps on their own. If you can make it easy for them, through a hosted connector, a no-code adapter, or a white-label app generator, you can carve out a nice business without competing directly with OpenAI or the big players.

Another lane is domain-specific vertical apps.

These are tools deeply tuned to a particular field, places where ChatGPT alone isn’t enough because you need rules, context, or domain data. For example:

• A legal assistant that drafts contracts using your firm’s clause library and jurisdiction rules.
• A medical summarizer that reads patient notes and prepares SOAP summaries while respecting clinical terminology.
• An insurance underwriting helper that compares quotes and compliance docs.
  A construction project estimator that pulls from local materials databases and building codes.
• A clinical trial protocol generator that enforces regulatory constraints in biomedical research.
• A tax prep advisor that structures returns while adhering to jurisdictional tax law logic.

These kinds of apps are perfect for ChatGPT. They combine language understanding with structured, rule-based reasoning. And since they require domain data, the barrier to entry is higher, meaning less competition.

Finally, there’s an opportunity in data and augmentation services. This isn’t just about connecting APIs, it’s about making the data smarter before it ever reaches ChatGPT. Think of tools that:

• Clean, normalize, or enrich customer data before sending it into ChatGPT.
• Securely blend internal databases like CRM, analytics, and ticketing systems with conversation context.
• Manage which data ChatGPT can “see,” keeping sensitive info behind permission layers.
• Provide smart caching or indexing of domain datasets so that repeated queries don’t re-ingest the same data.
• Offer precomputed embeddings or vector indexes for domain corpora so the app can respond fast without hitting remote APIs every time.

That’s more than integration. It’s about shaping the data so AI can use it effectively and safely.

Building for real pain points

The best way to find opportunity in this ecosystem might simply be to solve your own problem. Because ChatGPT apps are built for tasks people already do in ChatGPT every day, the strongest ideas often come from noticing where the current experience breaks down for you.

For example, my personal pain point is that I love writing blog posts with ChatGPT, but I hate that it doesn’t have proper change tracking or collaboration. I want a ChatGPT app, not a Google Doc, where my team and I can co-edit drafts, see revisions, leave comments, and keep the chat context right alongside the text.

That’s the kind of small but high-impact use case that feels native to ChatGPT: it builds on what’s already working while patching a gap that millions of people might share. If you use ChatGPT daily, you’re sitting on a front-row seat to these unmet needs. The trick is to notice the friction, and then build the simplest possible app that removes it.

Where it all might go

We’re early. Really early. But if ChatGPT keeps growing at this pace, this new app layer could become the next big computing platform.

For now, the safe money is on SaaS extensions. The exciting money is on indie devs who take weird bets on what AI-native consumer experiences look like. And somewhere in between sits a huge B2B opportunity for anyone who helps data, software, and domain logic connect more fluidly to this new world.

The real frontier might belong to the builders who notice what annoys them and fix it. The apps that win won’t just be the cleverest, they’ll be the ones that make people say, “I can’t believe ChatGPT didn’t already do that.”

If you’ve ever wanted to be early to a platform shift, this might be the one.