Messaging Agents in Messaging Apps — The Next App Store for AI

There’s a tectonic shift underway in how people will interact with artificial intelligence. For decades, the dream has been to put powerful AI into everyone’s hands, but until now, the path has mostly meant downloading specialized apps, opening new browser tabs, or wrestling with clunky interfaces. But what if the real revolution isn’t in building the next killer app, but in meeting people exactly where they already are—inside their messaging apps?

In just the past year, conversational AI has gone from novelty to necessity for millions. ChatGPT reportedly reached 100 million weekly active users in less than twelve months, according to Sam Altman, OpenAI’s CEO. Meanwhile, tech giants are racing to weave AI more deeply into the fabric of everyday communication. Meta has rolled out “Meta AI,” a conversational assistant available natively inside WhatsApp, Messenger, and Instagram, instantly exposing their AI to a user base in the billions. Snap’s My AI, introduced to Snapchatters worldwide, saw more than 150 million users send over ten billion messages to the bot in just its first two months. These numbers are staggering, but they also signal something deeper: messaging is becoming the new gateway for how people will experience, use, and even pay for AI.

If the last decade belonged to the smartphone app stores, the next will belong to messaging platforms. The analogy isn’t a stretch. Just as Apple’s App Store and Google Play centralized access to millions of mobile apps and created an ecosystem that shaped a generation of digital experiences, messaging apps are now poised to become the launchpads—and, crucially, the distribution engines—for the coming wave of AI-powered services. OpenAI’s GPT Store is taking the first step, letting users discover, share, and even sell their own custom chatbots, while Meta’s new “AI Studio” is opening up WhatsApp and Messenger to third-party developers to create specialized AI agents. The stage is set for a new “app store moment”—but this time, the entry point is your favorite chat window, and the “apps” are AI agents that can do just about anything you ask, in plain language.

Why Messaging Agents Matter

To understand why this shift is so powerful, you need to grasp what messaging agents actually are—and, more importantly, why they’re poised to upend how we use technology. A messaging agent is not just a chatbot; it’s an AI-powered entity that exists natively within a messaging platform, capable of holding a rich, multi-turn conversation, responding to context, and performing tasks for the user. It is, in effect, a digital concierge living in your chat list, ready to help at a moment’s notice.

The real magic, though, is not in the technology, but in the frictionlessness of the experience. Bill Gates, reflecting on the future of personal computing, recently predicted that “you won’t have to use different apps for different tasks. You’ll simply tell your device, in everyday language, what you want to do.” This vision is already being realized, but it’s happening not on a desktop or a web page, but in the humble chat window—where people spend the majority of their digital lives.

Why does this matter? Because messaging is universal, immediate, and intimately personal. People trust their messaging apps in a way they don’t trust many other forms of software. There’s no learning curve; there’s no need to hunt for an app, remember a password, or update your software. You simply message, as you always have, and the AI is there, ready to help, to answer, or to execute a command. For the vast majority of users—those who never bother with app stores or rarely download new software—this is the missing piece for true AI accessibility.

Consider the impact: With agents embedded in WhatsApp or Telegram, users can book flights, get tech support, shop online, or even schedule appointments, all without ever leaving their chat interface. A concrete example of this trend is Notis, an AI-powered voice assistant that lives inside WhatsApp and integrates directly with Notion. Users simply send a voice note to Notis, and it transcribes, organizes, and stores the information in the right place in their Notion workspace—all within the familiar chat interface, with no extra apps to install or learn. This turns WhatsApp into a frictionless AI productivity platform for busy professionals, students, and teams who want to capture thoughts and meetings on the go.

Snapchat’s My AI has likewise been embraced by users looking for advice, creative inspiration, or just a friendly nudge in their day. The chat context means that these interactions are naturally more conversational and more personalized than the transactional, one-size-fits-all experiences of traditional apps. The agent can remember your preferences, understand your habits, and deliver truly individualized service.

This is not just more convenient—it’s transformative. As Gates points out, “agents are not only going to change how everyone interacts with computers. They’re also going to upend the software industry.” For most people, the first AI they use daily will not be a standalone product, but a presence inside the messaging app they already open a dozen times a day.

The Next ‘App Store’ for AI

Why are messaging platforms set to become the app stores of the AI era? First, it’s about scale. Messaging apps are, without exaggeration, among the most widely used software on the planet. WhatsApp just crossed three billion monthly users. WeChat boasts over 1.3 billion. Messenger, Telegram, and Snapchat each have hundreds of millions. These aren’t just casual users, either. The frequency and intensity of engagement dwarf almost every other category of app. People check messaging apps dozens of times a day; they’re woven into the rhythms of work, family, and social life.

For AI developers and startups, this presents an irresistible opportunity. Getting people to download a new app or visit a website is hard. Plugging an AI agent into WhatsApp or Messenger puts you in front of hundreds of millions—if not billions—of potential users instantly. Meta’s leadership has called WhatsApp “one of its biggest distribution platforms for AI services,” and the data backs this up. In Q1 2025, Meta’s CFO Susan Li stated that “WhatsApp continues to see the strongest Meta AI usage across our family of apps,” with the vast majority of users engaging the assistant in direct, one-on-one chat.

But it’s not just about reach. Messaging platforms offer something that traditional app stores never could: context, community, and virality. When an AI agent delights a user with a clever response or a genuinely useful recommendation, that moment can be shared instantly in a group chat, amplifying discovery through social trust. This is a fundamentally new form of app distribution, built not on banners or search algorithms, but on the natural dynamics of human conversation.

Discovery is also being formalized. Telegram and Slack already have bot directories; WeChat’s Mini Programs are miniature apps inside the messaging experience, allowing users to summon services for everything from shopping to banking. Meta has introduced entire “galleries” of AI personas, including celebrity-inspired bots, each with its own skills and personality, ready to be added to any chat. The line between app and contact is blurring; the future “store” isn’t a marketplace you visit—it’s a living list of agents, instantly accessible from your conversations.

This shift will transform monetization as well. Messaging platforms can enable everything from subscriptions (as with Replika’s paid tiers) to transaction fees and revenue sharing on in-chat commerce, mirroring the playbook of traditional app stores. OpenAI’s GPT Store is pioneering this with paid bots and anticipated revenue-sharing models. Messaging giants are likely to follow suit, layering business models atop these new AI-powered experiences.

Key Drivers Behind the Trend

So why is all this happening now? The convergence of several powerful trends has made messaging agents the right idea at exactly the right time.

First, there’s the ubiquity of messaging apps themselves. Messaging is as fundamental to modern life as email once was. Billions already use these apps across every demographic and geography. When Meta launches an AI in WhatsApp, it’s immediately accessible to a population greater than the United States, Europe, and India combined. The friction to try something new is almost nonexistent—you’re already in the app, you just tap a contact or type a question.

Second, the underlying technology has made a quantum leap. Advances in large language models (LLMs) like GPT-4 and Google’s Gemini mean that today’s AI agents can handle nuanced, multi-turn conversations, remember context, and perform tasks that were science fiction just a few years ago. The quality leap is so dramatic that Gartner’s 2025 tech trends placed “Agentic AI”—autonomous, goal-driven assistants—at the top of its strategic priorities. As Bill Gates put it, “they’ll be dramatically better… [You’ll] have nuanced conversations with them… not limited to simple tasks.”

Third, developer ecosystems have blossomed. Most major messaging platforms now offer robust APIs and frameworks, making it straightforward for startups and established companies alike to build and deploy bots. OpenAI’s and Google’s APIs have brought state-of-the-art conversational intelligence to any developer with a credit card. The result is a wave of innovation: AI-powered agents for support, coaching, scheduling, shopping, and more, all integrated into the workflows and conversations people already have.

Fourth, user trust and familiarity play an outsized role. People have deep, personal relationships with their messaging apps; these are spaces of trust and intimacy, often protected by encryption and governed by strong social norms. When an AI is introduced here—especially if it carries the brand of a familiar platform—it benefits from this trust by association. A user might hesitate to chat with a faceless bot on a random website, but they’ll give “Meta AI” or “Snapchat My AI” a try, especially if friends are already using them.

Finally, the network effects and social dynamics unique to messaging apps can turbocharge adoption. AI agents can be invited into group chats, shared in stories, or referenced in conversations, spreading organically through social graphs in a way that standalone apps can only dream of. When one person uses an AI agent to plan a party or generate a funny meme, everyone else in the group sees the value firsthand—and the loop continues. This social virality is a powerful accelerant for any new technology, and messaging agents are uniquely positioned to benefit from it.

Challenges & Considerations

Of course, no technological revolution arrives without challenges. If messaging agents are to fulfill their promise as the next app store for AI, several thorny issues must be addressed.

First and foremost is privacy and data security. Messaging platforms are the homes of our most sensitive conversations, and introducing AI agents into this space raises serious questions about data handling, consent, and oversight. End-to-end encryption, while standard for one-on-one messaging, may not always extend to messages processed by cloud-based AI, as they often need to decrypt content for analysis and response. The onus is on platform providers to set clear boundaries, inform users about what data is shared, and offer robust controls. Recent regulatory actions—such as Italy’s temporary ban on the Replika AI companion over concerns about data protection and minors—show that missteps can have swift consequences.

Then there’s the issue of platform control and gatekeeping. When messaging apps become de facto app stores, their owners become powerful gatekeepers, able to dictate who can build what and how. This introduces risks around monopoly power, unfair competition, and innovation stifling. Developers may be forced to comply with onerous approval processes, pay steep revenue shares, or risk being locked out entirely. The history of mobile app stores offers cautionary tales here, and similar battles are already brewing in the AI agent ecosystem.

Quality and discovery also present real hurdles. As the number of available messaging agents multiplies, how will users find the best, safest, and most useful ones? The early app stores were plagued by “app spam” and low-quality submissions. Messaging agent platforms will need strong curation, perhaps with ratings, editorial picks, or even certifications for trustworthy bots. OpenAI has openly acknowledged the risk of saturation—where millions of bots can crowd out innovation—and platforms will need to learn from the lessons of the app store era.

There are also major concerns around safety, misinformation, and ethical risks. AI agents in chat can easily be mistaken for human interlocutors, potentially leading to overtrust or misuse, especially among vulnerable populations. There have already been incidents where users formed deep emotional bonds with AI agents, or received misleading or inappropriate advice. Developers need to embed ethical guardrails, clear disclosures, and escalation paths to human help when needed. Regulators, particularly in the EU, are rapidly moving to impose transparency, age restrictions, and liability rules for conversational AI.

Lastly, regulatory and compliance complexities loom large. Data protection, consumer rights, speech regulation, and even competition law will all shape what’s possible in the messaging agent space. Europe’s AI Act and China’s censorship requirements both signal that the path to global deployment will be neither simple nor uniform. Companies will need to invest heavily in compliance and adapt quickly to local laws, or risk being shut out of key markets.

Where This Goes Next

Despite these challenges, the rise of messaging agents is just getting started, and the future is rich with possibilities. If you want to know where things are heading, look no further than the early case studies and emerging trends.

China offers a compelling example with Xiaoice, Microsoft’s empathetic chatbot, which has amassed over 660 million users and more than 30 billion conversations on platforms like WeChat and Weibo. Xiaoice’s popularity as a virtual friend demonstrates how AI can become a deeply integrated, everyday presence. In the West, Replika has built a community of more than 25 million users, many seeking companionship, advice, or just a safe space to talk. These examples highlight both the demand for conversational AI and the importance of clear boundaries and ethical design.

Consumer-focused assistants like Snapchat’s My AI and Meta’s roster of AI characters are also breaking new ground. My AI, for instance, has seen tens of millions of queries on everything from homework help to planning trips. Meta’s experiment with themed AI personas, including those modeled on celebrities, hints at a future where users can choose from a cast of AI assistants, each with unique skills and personalities, directly within their messaging app.

Monetization models are already evolving. Some agents are supported by freemium subscriptions—Replika, for example, offers advanced features to paying users. Others monetize via transaction fees, enterprise SaaS models, or even advertising. As commerce and payments become more tightly integrated with messaging, expect to see more AI agents handling everything from shopping to banking directly inside chat threads. This also opens up new opportunities for businesses to connect with customers in more personal, conversational ways.

Perhaps most intriguingly, we are seeing the beginnings of cross-platform and ubiquitous AI agents. Inflection’s Pi assistant lets users switch seamlessly between WhatsApp, web, SMS, and Instagram, with the AI maintaining context across channels. Microsoft and Google are embedding AI into every layer of their ecosystems, from operating systems to productivity suites. The future personal agent will likely follow you from chat to voice to email, orchestrating tasks and information wherever you are, whenever you need.

User experience is also set to leap forward. Messaging agents will soon be multimodal—able to generate and interpret images, voice, and video, not just text. Meta AI already drops photorealistic images into chat; Snapchat is moving toward AI-generated Snaps. Group collaboration features will let agents help coordinate plans or answer questions for entire chat groups. Customization and discovery will improve, with users able to personalize their AI’s persona and skills, or browse curated menus of specialized bots. The vision is a conversational interface so rich, intuitive, and helpful that you rarely need to leave it for anything else.

Finally, expect global diversity and regulation to shape the landscape. In China, AI agents will be more tightly controlled, but deeply integrated into commerce and daily life. In the West, regulatory pressure will lead to transparency, user protections, and (eventually) a more level playing field for startups. Over time, as standards emerge and APIs improve, the dream of a cross-platform, interoperable AI agent may come true—giving every user a true digital companion that travels with them across apps, devices, and languages.

The Conversational Interface Era

A decade ago, the smartphone app store defined how we accessed software and services. Today, as AI breaks out of its silos and into our everyday conversations, messaging apps are poised to become the new operating system for life—and messaging agents the new apps. The implications are profound: For most users, the “AI app store” of the future won’t be a marketplace they browse or an app they install. It will be a chat window they already trust, open, and use every day, with agents ready to help, inform, and entertain at a moment’s notice.

Product leaders, developers, and brands should pay close attention. The winners in this new era will be those who build for the chat-first world, designing agents that are genuinely helpful, safe, and delightful inside the world’s favorite messaging apps. The opportunity is massive, but so are the responsibilities: privacy, ethics, quality, and user trust will determine who thrives as messaging becomes the primary interface for AI.

As William Gibson once put it, “The future is already here—it’s just not evenly distributed.” Messaging agents are arriving fast. The only question is, are you ready to build and compete where the world is already talking?