When ChatGPT Stops Being a Tool and Starts Becoming a Platform

OpenAI’s app ecosystem changes how digital capability is assembled, governed, and delegated

OpenAI’s decision to allow developers to submit applications directly into the ChatGPT ecosystem has been widely described as an “app store” moment. That label is understandable, but it undersells what is actually changing.

We sense that this move is not primarily about distribution or monetisation. It is about where capability now lives, who controls it, and how judgement is increasingly mediated through orchestration layers rather than standalone tools.

This is not a cosmetic expansion of features. It is a structural shift in how digital work is packaged and delivered.

What Has Actually Changed

OpenAI has opened submissions for apps that run inside ChatGPT itself, extending conversations into real, task-oriented functionality. These apps can order groceries, generate slide decks, book accommodation, or execute specialised workflows directly from within the chat interface, using the Model Context Protocol and custom UI elements embedded in chat. 

This is not an informal experiment; it represents a formalised platform expansion rather than a loosely curated marketplace. Apps must meet strict submission guidelines, cannot sell digital products yet, and will be surfaced gradually through an official directory hosted by OpenAI — a curated infrastructure, not an open bazaar.  OpenAI+1

That distinction matters because it signals a broader shift in how AI capabilities are integrated.

Michelle Hawley, Editorial Director, VKTR observed, “OpenAI is betting that the next frontier for ChatGPT lies in becoming a platform, not just a product,” highlighting that this move transforms the chatbot into a hub for executing real services and workflows rather than merely responding to prompts. VKTR.com

By defining the conditions under which capability is embedded, surfaced, and governed, OpenAI is signalling that task execution — and the constraints, quality standards, and review processes that come with it — are becoming foundational to its vision for conversational AI. This is curated functionality at scale, with implications for how organisations build, distribute, and control AI-mediated workflows within their own systems.

From Software Products to Embedded Capability

For decades, enterprise software has been delivered as discrete products. Teams selected tools, integrated them, trained users, and adapted workflows around them. Even cloud platforms largely followed this model.

The ChatGPT app ecosystem alters that dynamic. Capability no longer sits outside the work and gets pulled in. It sits inside the interaction layer itself.

This marks a substantive shift in how capability is being deployed. Specialist workflows, domain logic, and decision support can now operate much closer to practice. The translation gap between tool and usage narrows. Teams interact with outcomes rather than interfaces.

This lowers friction substantially. For project managers, it suggests faster access to embedded intelligence rather than generic software layers. Capability becomes modular, composable, and increasingly agent-led.

But this convenience comes with new dependencies.

The Quiet Centralisation of Control

While this move is often framed as democratisation, there is an equally important consolidation underway.

As value concentrates inside a single orchestration layer owned by OpenAI, organisations risk outsourcing not just execution, but elements of judgement, workflow design, and even assurance. Decisions about how work is structured, how context is preserved, and how outputs are prioritised increasingly sit with the platform.

We feel the critical tension. What looks like openness at the developer level can translate into lock-in at the delivery level.

The platform controls discovery, interaction patterns, guardrails, and ultimately the framing of decisions. That does not mean misuse is inevitable. It does mean incentives are not neutral.

This is where delivery leaders need to slow down and read the architecture, not just the feature set.

Accountability in an Agent-Mediated World

There is a quieter but more consequential shift happening alongside this ecosystem expansion. Accountability is becoming harder to localise.

If a delivery decision is informed or executed by a third-party agent running inside ChatGPT, responsibility blurs. The developer wrote the logic. The platform mediated the interaction. The project team relied on the output.

Traditional governance models assume clearer lines. Tool vendor, system integrator, delivery owner. Those assumptions strain when agents operate across contexts and evolve independently of the programmes that depend on them.

This is not a hypothetical concern. It mirrors patterns already visible in automated decision systems across finance, logistics, and operations.

As OpenAI itself notes through its submission framework, control is being exercised deliberately.

“Apps must follow strict submission guidelines and are reviewed before appearing in ChatGPT’s app directory.” Source: eWeek

Review is necessary, but it is not the same as accountability. Delivery leaders remain responsible for outcomes, even when the logic behind them is increasingly abstracted.

A Contrarian Opportunity Hidden in Plain Sight

There is, however, a counter-narrative worth taking seriously.

This shift may not advantage large incumbents or broad-scope consultancies in the way many assume. Instead, it could reward small, deeply contextual teams that encode lived delivery experience into narrow, high-impact agents.

In a world where distribution is handled by the platform, differentiation moves upstream. Understanding of context, constraints, and decision nuance becomes the asset.

We believe this is where the most interesting innovation may occur. Not in general-purpose tooling, but in agents that embody specific delivery wisdom, built by those who understand the work intimately.

The platform may centralise access, but expertise does not automatically commoditise.

What Senior Leaders Should Be Asking Now

For senior leaders, the strategic question is not which apps to approve or which vendors to back. It is more fundamental.

Which decisions are we prepared to delegate. Under whose control. With what visibility. And with what ability to intervene when context shifts.

The temptation will be to focus on productivity gains. Faster execution. Lower cognitive load. Reduced coordination cost. Those benefits are real.

The risk is treating delegation as a technical choice rather than a governance one.

The most resilient organisations will be those that make delegation explicit, bounded, and reviewable. They will decide deliberately where human judgement must remain central and where automation can safely operate.

From Tools to Decision Infrastructure

Seen clearly, OpenAI’s app ecosystem is not just a new distribution channel. It is a move toward decision infrastructure.

When applications live inside the interaction layer, they shape how problems are framed, how options are presented, and how trade-offs are surfaced. Over time, that influences how organisations think, not just how they work.

This is not inherently negative. But it is consequential.

Delivery leaders who treat this as “just another platform feature” will miss the deeper shift.

Call to Action

The question is no longer whether AI will sit inside your delivery environment. That is already happening.

The question is whether you are consciously designing how it does so.

Take stock of where decisions are being mediated by agents rather than people. Examine which assumptions are being encoded into tools you do not control. Decide explicitly where accountability must remain human, visible, and interruptible.

AI embedded at the interaction layer changes how decisions are framed long before they are made. Leaders who recognise that early retain control over delivery logic rather than retrofitting it later. 

At Project Flux, we focus on these moments where capability shifts faster than governance and where delivery intent needs to be made explicit. Subscribe for more such in-depth discussions.