The interface is dead. Time for the age of intent

OpenAI’s latest Dev Day gave tantalizing glimpses into the next phase of generative AI — not merely new features, but the arrival of a new kind of digital experience. The BuyIt paired with Apps in ChatGPT, signals the emergence of a unified ecosystem where conversation, commerce, and creativity coexist.

The fundamental ideas hint at the next era of digital products — where interfaces disappear, intent replaces navigation and personalized interaction becomes the default. These innovations aren’t just about increasing the utility of an LLM; they redefine what a digital channel can be.

From interfaces to intent

Each new wave of interface has redrawn the digital map: the web browser, the smartphone, the voice assistant. You can chart the progression of easier, richer interactions — and how that made business models more fluid. Apps in ChatGPT represent a new opportunity — where conversation replaces navigation and intent displaces clicks.

Apps in ChatGPT are third-party or specialized tools that live inside the ChatGPT environment, extending what the model can do. In this new world, your users won’t launch an app or tap in a search, they’ll just ask ChatGPT to plan and book their flights to Ibiza or curate a Spotify playlist. 

The initial launch partners (Booking.com, Expedia, Zillow, Canva and Spotify) illustrate both the creative breadth of this ecosystem and its potential to solve some of the most frequently requested use cases in generative AI, such as planning and booking trips or generating personalised content.

But the real kicker is how this marks the emergence of AI-native interfaces: it creates an opportunity to meet customers where they already are, in natural language conversations, rather than expecting them to navigate to websites or apps. This marks a profound shift in how discovery, intent, and purchase come together. For enterprise architects, that raises both opportunities and challenges. Traditional UI flows give way to dialogue-based orchestration, where the model interprets context, invokes the right app, and executes a task seamlessly.

Building an AI-native platform

For enterprises, this is more than an integration opportunity. It’s a fundamental shift in how you interact with your customers.

This isn’t just a new interface: it’s a new business channel. Embedding commerce inside AI assistants opens the door to experiences that are proactive, personalized, and context-aware. The moment feels reminiscent of the early shift to Web 2.0 or the second generation of iOS apps, when digital products evolved from static experiences into platforms for deeper connection and ongoing engagement.

In this way enterprises can embed services directly within conversational flows — from HR queries to IT automation or customer support. The result is a platform that unifies marketing, product and service touchpoints into a single intelligent interface. Those who learn to design for this channel early will shape the playbooks for AI-driven customer experience in the next decade.

The question of money

The seamless combination of conversational AI (OpenAI) and payment infrastructure — in this case Stripe — fundamentally redefines people’s shopping experience while addressing a key friction point for consumers: trusting services with their money. Instead of multiple clicks and checkout forms, transactions happen through dialogue “I like that one, find it at the best price and buy it.” The model moves from navigation-driven to intent-driven, lowering friction and making digital experiences more natural.

But for retailers, it raises other questions: How do we ensure ChatGPT assesses our offerings? How can we guarantee that we deliver the right products at the right price?

And so far, the biggest unknown is how monetization will work. We know OpenAI plans to introduce the Agentic Commerce Protocol (ACP) as the foundation for payments and revenue sharing, but the specifics haven’t been disclosed. Drawing from how other marketplaces have matured, we can speculate that early incentives may entice brands to build on the platform, with the economics shifting once a critical mass of apps is established.

This raises familiar strategic questions:

• Where does value accrue: to the platform or to the participant?

• How will fees, commissions and token usage costs be structured?

• Will the platform evolve toward a “closed garden” or an open ecosystem model?

There’s also uncertainty around who bears the ongoing costs of usage, particularly token consumption. Right now, Apps in ChatGPT are only available to premium-tier subscribers; if that continues, it could limit audience reach or create new segmentation challenges for brands.

What your teams should be thinking about

It’s still early days to be thinking about how this shift conversational UI might play out, but there are several obvious areas to start thinking about:

Customer experience and data access

• There’s a huge opportunity for more personalized and contextual user experiences within an LLM-based interface.

• But it’s unclear how much customer data will be shared with developers — will OpenAI keep most insights?

• What about the privacy/analytics trade-off? That could be key to define the platform’s real business value.

• Enterprises must plan for data governance and understand limitations around user visibility and behavioral insights.
  
  

Developer experience and governance

• The developer approval and review process isn’t yet defined — we might think it will likely mirror Apple’s App Store–style models.

• Should I extend my APIs to be compatible with ACP i.e. product inventory, checkout, delegated payment?

• It’s not yet clear how open or scalable the ecosystem will be for enterprise-grade deployments.

• Key technical areas to evaluate:

  • Ease of SDK use and integration experience.

  • Testing and CI/CD pipeline compatibility.

  • Security boundaries and required system access.

• Until clear tooling, governance and QA patterns emerge, large-scale enterprise adoption remains uncertain.
  
  

Security and responsible use

• New integration surfaces mean new threat vectors — from data leaks to malicious app behavior.

• Past incidents highlight how human error and weak governance can expose sensitive data.

• Organizations must prepare proactive safeguards and monitor vetting processes once OpenAI defines its app approval model.

• Ongoing security assessment and compliance reviews will be essential to maintain trust.
  
  

So there’s some kicking of the tires to be done. But if you’re curious about how your business can take advantage of these shifts to embed AI into your products, reimagine your digital channels and build responsibly for the future, you’re already ahead of the game. This moment belongs to those ready to reimagine how technology meets human intent turning conversation into connection and interaction into impact.