Would AI super agents mean goodbye to apps as we know them?
In the Western world, we now have an app for everything. Shopping, banking, gaming, and even controlling the temperature in your home - you name it, there’s an app for it. The iOS app store began in 2008 with 500 apps, yet, now there are over four million apps available across iOS and Android platforms. Each of these apps serve individual needs and consumers have learnt to ignore the digital clutter in favor of app loyalty.
Asia went the opposite way. Instead of narrow-purpose-built apps, they built the 'everything app' long before Elon started dreaming about it with platforms like Paytm, Grab and WeChat. But what would it take for the West to catch up? AI super agents might be the answer to that one.
Why the West resisted the super app
Super apps struggled to gain traction in the West because user behavior and technology there evolved along a very different path than in Asia. The West started with desktop internet, which got users accustomed to various apps catering to individual needs instead of offering a unified experience. Countries in Southeast Asia, meanwhile, led the mobile-first consumer economy, prioritizing ease and integration, skipping the desktop internet phase altogether.
This means the West has fostered far stronger app (or ‘brand’) loyalty -- some users will never stray from Deliveroo for their Friday night takeaway, while others rely on JustEat. For a super app to succeed in the West, it would need to combine the best features of well-loved apps into one cohesive interface, which is challenging to say the least. Some western giants have certainly tried, whether it's Uber adding flights, trains, and food delivery, or Meta introducing gaming, marketplace, and even dating into Facebook. Still, these haven't come close to the mega-app status of something like WeChat.
Enter AI super agents
As much as super apps may have struggled to coalesce in the West, AI super agents could be their second chance. Unlike traditional apps designed for specific tasks, these agents can adapt to a wide range of user needs. We’re not a million miles from it now, as AI language models like DeepSeek, Llama 3, Claude 3.5, Gemini and GPT-4o are already designed to support many use cases, with Agentic AI taking that even further.
The real strength of these AI super agents will be their ability to personalize experiences. They won’t just aggregate service but analyze preferences and habits to provide tailored recommendations, such as an AI that can help you find a good restaurant based on your dietary preferences, your favorite cuisine and where you went last week. It could also go a step further to suggest dishes based on past orders and make reservations for you -- all while checking traffic conditions to ensure you arrive on time.
There’s a strong argument for integrating our favorite apps into these intelligent systems. Historically, apps have been built for narrow purposes -- often just one at a time. With millions of apps competing for our attention, this model may not be sustainable in the long run. Instead of creating larger apps that attempt to do everything, we could see networks of specialized AI agents collaborating seamlessly.
This integration would also change what it means to be a developer. Instead of building separate apps for iOS, Android, and web platforms, they could focus on creating robust APIs that AI agents can interact with. Many startups come up with fantastic ideas every day but often hit roadblocks due to a shortage of skilled developers. AI super agents could democratize app development by letting people without extensive coding skills bring their ideas to life using natural language -- turning everyday conversation into programming.
The UX Challenge
But making AI super agents successful hinges on user experience. The digital assistant needs to sit at the OS level, on devices with powerful GPUs and lightning-fast connectivity. The interface must be intuitive and responsive across different input methods -- whether it’s voice commands or touch gestures. Human-machine interaction relies on effective information presentation, and tactile feedback is important because ultimately people want to see, hear, and feel their technological interactions.
Another major challenge to overcome will be making sure these agents comply with stringent data protection and privacy laws that otherwise make it unappealing for developers to process large datasets through an AI. Wouldn’t it be much easier if managing online privacy resembled a graphic equalizer? It would be a lot more user-friendly, while still giving the user control over personal data.
Where super apps failed in Western markets, AI super agents may well be the key to delivering on their promise of streamlining daily life. At the end of the day, the point of technology is to address real issues, not to keep you within any particular app or ecosystem.
Miao Luo is Director of Technology Strategy, Qt Group.