Generative AI
Building for intent: What it takes to become an intent-ready organization
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This article is the fourth in our Age of Intent series, examining how value and revenue models will evolve as AI intermediaries reshape discovery and engagement.
What happens when the interface disappears — and so does the business model?
As we discussed in earlier pieces: When interactions happen through large AI systems like ChatGPT, Gemini or Claude, the interface between organizations and customers dissolves. The familiar feedback loops — clicks, sessions, conversions — vanish with it.
We can already build conversational experiences, but we don’t yet know how the value and revenue exchange will work in this new ecosystem. Who captures the demand? Who owns the transaction? Who gets paid — and how?
That uncertainty isn’t a reason to wait. It’s a reason to lead.
Because in every major technological shift — from the web to mobile to platform ecosystems — those who began exploring before the economic model was clear were the ones who shaped it.
Why this matters now
In the interface era, the economics were straightforward: you built the platform, you owned the customer relationship and that meant you monetized attention, transactions or subscriptions.
In the intent era, the interface might belong to someone else. Your customer might start their journey not on your app, but in a conversation with ChatGPT or through an enterprise assistant that brokers multiple services on their behalf.
The challenge is structural: you could be fulfilling demand you never directly see, through an intermediary you don’t control.
Right now, there is no clear model for how value is created, shared or monetized in this chain — and that’s exactly why it’s time to act. Once ecosystems mature, the revenue model will be defined for you.
What happens when value moves upstream?
We’ve seen this before. When search engines emerged, visibility became the new currency. When social platforms scaled, attention became the currency.
Now, as AI intermediaries rise, intent is becoming the currency — and the value exchange is shifting upstream, to whoever interprets and orchestrates that intent best.
That means value will flow:
From interfaces to intermediaries. Assistants will decide who’s included in the conversation.
From attention to outcomes. Instead of paying for impressions, organizations may pay for verified fulfillment.
From ownership to participation. Brands that make their data, APIs, and capabilities accessible will earn inclusion.
The old playbook — control the interface, then monetize attention — won’t work in a world where the interface is ambient and the transaction invisible.
The disappearing interface, the invisible transaction
When a customer says, “Find me a travel insurance policy that covers skiing,” or “Book me a hotel near the conference venue,” an assistant interprets that intent and selects options on their behalf. No website visited. No app downloaded. No direct engagement logged.
So where does the value exchange happen?
Does the insurer or hotel pay for inclusion?
Does the assistant take a transaction fee?
Does the brand even know the request occurred?
These are not hypothetical questions — they’re open design challenges that will define the next decade of digital business.
Embracing uncertainty: leading before the value model is clear
Right now, we simply don’t know how this value exchange will ultimately work — and that’s precisely why leaders need to start shaping it. History tells us the same story every time a new marketplace emerges: early movers who experiment before the model stabilizes help define it. They gain advantage not because they predict perfectly, but because they learn faster than everyone else.
The question is not: What’s the revenue model? It’s: How do we prepare to thrive in any model that emerges? That begins with a few principles.
Principles for an unknown value exchange
While the economics evolve, focus on the foundations that will hold in any version of the future:
Be legible to machines. Make your offerings and data machine-readable. If assistants can’t interpret your services, you can’t be chosen.
Build trust as infrastructure. Treat trust as a product feature. Transparency, reliability, and explainability will determine inclusion.
Design for composability. Assume your products will be part of a larger ecosystem. Closed systems will be left behind.
Experiment early. Prototype different participation models — from verified data APIs to outcome-based partnerships. Learn before the rules are written.
Govern for participation. Prepare your governance, data-sharing and consent frameworks now. When the value flow matures, you’ll be ready to transact responsibly.
These are not revenue strategies yet — they’re readiness strategies for an ecosystem still under construction.
New metrics for the age of intent
Even if we can’t measure revenue precisely, we can start tracking signals of future advantage:
Inclusion rate. How often your brand appears in agentic responses.
Selection rate. How often you’re chosen once included.
Outcome yield. The measurable result per inclusion — verified conversions, resolved intents, completed actions.
Trust score. Your visible reliability and compliance to external evaluators and platforms.
These metrics will become as fundamental as clicks and impressions once were. They’re early indicators of whether your brand is being seen, trusted and preferred — even when the interface is gone.
The leadership opportunity
This is a defining leadership moment — not a technical one. You don’t need to know the final value model to start leading in it. You need to cultivate a culture that’s comfortable experimenting before the economics are settled.
Ask your teams:
Where could we safely test participation in emerging ecosystems?
What data or APIs would make us easy for AI intermediaries to include?
How can we measure inclusion and trust today, even without direct revenue attribution?
The leaders who start asking these questions now will have a voice in shaping how the value exchange actually works — rather than being price-takers once it’s defined.
Closing thought
We’re in a moment of economic ambiguity and strategic opportunity. We don’t yet know how value will move through intent-driven ecosystems — but we can already see that it will reward clarity, trust, and adaptability. The question isn’t whether the model will emerge. It’s who will be ready when it does.
In the final article, “Building for Intent: What We Learned from the ChatGPT App SDK,” we take a hands-on look at the technology itself — sharing lessons from our own experiments with the SDK, Model Context Protocol and what it takes to build for intent in practice.
Disclaimer: The statements and opinions expressed in this article are those of the author(s) and do not necessarily reflect the positions of Thoughtworks.
