Not a single wellness brand has launched a ChatGPT app. Spotify, Zillow, Canva – they're there. Fitness and health? Absent. Peloton and AllTrails are announced as "coming soon" partners. No one has actually done it.
The hesitation makes sense specifically for healthcare. You're dealing with sensitive health data, potential Food and Drug Administration (FDA) oversight, liability concerns, and users who need trust before they'll share biometric information. Entertainment apps don't face these barriers. Health apps do.
Yet the opportunity is massive. In October 2025, OpenAI announced the ChatGPT Apps SDK (software development kit) – a platform that lets brands live in the flow of conversation rather than requiring users to download separate software. For the 800 million people who use ChatGPT weekly, this changes everything.
Imagine typing "Help me train for a half-marathon" and having your fitness app appear right there in the conversation thread – no download, no login reminder, no separate interface. Just immediate coaching that understands your history, your data, and your goals.
This matters because friction kills health apps. Industry data shows that 66% of health apps and 69% of fitness apps are abandoned within 90 days, worse than the 52% average across all app categories. Every download screen, every login reminder, every notification that gets swiped away represents a moment where intention evaporates. Conversational interfaces collapse that barrier. They meet people mid-thought, when motivation is highest.
A conversational front door
ChatGPT isn't a chatbot anymore. It's becoming a conversational operating layer. The Apps SDK, built on the Model Context Protocol, lets developers embed logic, UI elements, and API calls directly into chat threads. Users summon apps by name or let ChatGPT suggest them contextually.This won't replace your native app. Think of it as a new front door. You'll still need your mobile, web, and wearable presence for sensor complexity, offline functionality, and full features. What you gain is an alternative interface with no download friction and built-in contextual awareness.
The catch? You can't just port your existing experience. This demands rearchitecture for conversation. Your backend must expose secure endpoints for retrieving user data, performing calculations, and updating state. You must design for permissions and consent upfront – ChatGPT gates access to user data, and connection transparency isn't optional.
But once you’ve built this integration, ChatGPT can fetch someone's workout history, display it conversationally, generate a training plan, and save that plan back to their account – all while the user stays in the chat. The data synchronisation is bidirectional. Your app maintains the source of truth. ChatGPT becomes an interface layer.
This fundamentally changes discovery for health apps. The traditional battleground – fighting for App Store visibility, search ranking, featured placement – gets partially bypassed. Now you're competing on two fronts: conversational relevance and brand recognition. When someone says, "Help me manage my diabetes," will ChatGPT suggest your brand? That depends on integration quality, user satisfaction signals, and how well your conversational design maps to natural language patterns.
But users can also invoke apps directly by name – "Peloton, plan my week" or "MyFitnessPal, log this meal" – which means traditional brand awareness still matters. Strong brand recognition ensures users think of you first when they need health coaching, even in a conversational interface.
Success here shifts your brand from an app users must launch to a companion they speak to.
When conversation meets your health data
The real opportunity sits where user data intersects with a conversational interface. When you combine historical fitness metrics, wearable sensor streams, and self-reported information with natural language, you unlock something between app and coach.
Consider the half-marathon example. Your ChatGPT-embedded app fetches their previous runs, pace trends, heart rate variability, sleep records, and injury history. It proposes a plan that adapts dynamically as real data arrives. Sensors detect elevated fatigue? The plan adjusts. It can benchmark them against population norms or personal bests.
The conversational setting invites new user behaviours, asking questions they wouldn't bother typing into a traditional interface: "If I skip this week, how much would that affect my finish time?" "Is my resting heart rate trend normal for someone my age?" "Should I be worried about this soreness?"
Your app answers with charts, insights, and recommendations. Because it lives inside ChatGPT, it can lean on conversational memory. Someone who previously discussed poor sleep doesn't need to re-establish that context when talking about training fatigue. The threads weave together.
Research validates this approach. A systematic review published in April 2025 found that conversational AI coaching improved adherence rates by up to 32.7% compared with traditional app-based interventions. Meanwhile, Google Research's 2025 study on Wayfinding AI, powered by Gemini, demonstrates that users interacting with conversational health tools ask many more clarifying questions than those using traditional form-based interfaces.
Little wonder the AI fitness market is projected to grow to $138.5 billion by 2029, with a 17% compound annual growth rate from 2024 to that date. That's capital following user behaviour.
The strategic benefits compound. Conversational coaching is inherently sticky – users return to talk rather than stare at dashboards. You can monetise advanced features: detailed benchmarking, predictive analytics, premium coaching tiers. Over time, your brand perception shifts from "fitness app" to "coach I depend on."
Here's where it gets complicated for health brands. When you're making recommendations that influence training load or injury risk, you're operating in territory that attracts FDA attention. In January 2025, the FDA released draft guidance on AI-enabled device software that specifically addressed adaptive coaching algorithms. Most wellness apps don't currently fall under Software as a Medical Device classification. That boundary is blurring.
Your conversational experience is your brand
Your brand lives in the words you choose when someone asks for help. How you phrase advice, handle uncertainty, and manage expectations becomes your identity.
Consider three responses to "I'm exhausted, but my training plan says I should run today":
Option A: "Your training plan shows a five-mile run scheduled. Would you like to proceed with today's workout?"
Option B: "I can see you're feeling tired. Your recent sleep data shows 5.2 hours last night – well below your average. Consider a gentle walk or rest day instead."
Option C: "My algorithm says you should rest today."
Option A ignores the user's stated fatigue, treating them like a data point rather than a human. Option C sounds robotic and lacks empathy, leaving no sense of agency in the decision. Option B acknowledges their feeling, provides relevant context, and offers options. It feels empathetic while remaining data-driven.
These micro-interactions accumulate into brand perception. Users remember brands that listen to their concerns and offer nuanced guidance. They abandon ones that feel mechanical or dismissive.
Brand differentiation in conversational wellness
In a conversational interface, your brand differentiates through four key dimensions:
Domain expertise: Depth of knowledge in specific health verticals – diabetes management, injury prevention, sports nutrition – matters more than broad surface coverage. Users trust specialists.
Data integration quality: Brands that weave multiple data streams intelligently – wearables, manual logs, environmental factors, training history – provide insights competitors can't match.
Conversational personality: Some users want a supportive coach. Others want data-driven analysis. Others want tough-love accountability. Your brand voice determines who you attract and retain.
Regulatory positioning: Brands that invest in clinical validation, FDA clearance, and transparent methodology signal a different level of credibility than consumer wellness apps. This particularly matters for chronic condition management.
Platform dependency trap
Platform dependencies cut both ways. You're exposed to OpenAI's pricing changes, policy updates, and quota limits. Your brand could become invisible if OpenAI's algorithm doesn't surface you. The platform hasn't disclosed its monetisation model for developers yet.
Here's the bigger risk: What happens if ChatGPT loses its conversational dominance? The AI landscape moves fast. Google's Gemini, Anthropic's Claude, Apple Intelligence, Meta's Llama – multiple players are investing billions in conversational AI. If you've built everything for ChatGPT's specific platform and users migrate elsewhere, your investment becomes stranded.
This suggests a multi-platform strategy from the start. Design your conversational interface layer to be platform-agnostic. Build on standards like the Model Context Protocol that work across multiple AI platforms. Maintain your native apps as the source of truth. Treat conversational platforms as distribution channels, not your primary product.
Guidance for wellness brands crossing the conversational threshold
The path forward demands specific action:
Build hybrid architecture. Keep your native applications for sensor complexity, offline functionality, immersive visualisation, and full feature depth. Position your ChatGPT integration as the conversational companion: always-on, low-friction, contextually aware.
Design conversation-first for health use cases. Design specifically for how people actually discuss health: vague symptoms, emotional language, uncertainty about terminology. "My knee hurts" means different things to different people. Your conversational design needs to handle ambiguity gracefully.
Build data moats through integration depth. Invest in longitudinal learning, sensor fusion, and analytical depth that competitors can't easily replicate. Consider tiered monetisation: foundational coaching free or ad-supported, premium insights behind subscription walls.
Make transparency and control core to your brand. Users should understand exactly what data you're using, how recommendations get generated, and where your confidence is high versus speculative. Provide granular permissions and clear opt-outs.
Treat compliance as a strategy, not a constraint. Building SaMD-grade infrastructure, establishing clinical validation protocols, and implementing audit systems – these create defensive positioning that attracts healthcare partnerships and insurance collaborations.
Design for multi-platform conversational AI. Don't build exclusively for ChatGPT. The conversational AI landscape will evolve. Design your backend to support multiple conversational platforms.
What makes users stick
Ultimately, we're witnessing the emergence of an AI-mediated computing paradigm in which conversational interfaces increasingly sit between users and functionality. The organisations that master conversational design, data fusion, regulatory compliance, and trust infrastructure now will be positioned to adapt as the ecosystem evolves.
Here's what matters most: If users come to trust your brand as genuinely helpful – if your recommendations prove accurate, your tone feels supportive, your privacy protections hold, and your guidance produces real results – then your brand transcends the platform. The key is designing engagement that serves genuine health outcomes rather than empty metrics.
Wellness brands that embrace this shift early, invest in conversational design, build proper data and compliance infrastructure, and maintain the humility to admit uncertainty will establish defensive positions that late movers struggle to challenge.
Those who treat ChatGPT Apps as just another distribution channel will miss what's actually happening: the conversation is becoming the product. And, specifically, in health, that conversation needs to be worth having.