Picture this: You're scrolling through your phone's app store, and suddenly it feels like you've entered an AI wonderland. Every other app is trumpeting its "revolutionary AI features" and "groundbreaking AI technology." Your weather app now claims to use AI to predict rain (wasn't it already doing that?), your photo editor boasts "AI-powered enhancement" (what happened to good old filters?), and even your calendar swears it has AI scheduling capabilities (because apparently, we can't be trusted to manage our own time anymore).
If you're feeling a bit overwhelmed or skeptical about all this AI chat, trust us – you're not alone. We've spent the last eight years at Glance building mobile apps for everyone from fresh-faced startups to household names, and we've watched this AI gold rush unfold from the front row.
Here's the thing: artificial intelligence in mobile apps isn't inherently good or bad – it's a tool, like a hammer. And just like you wouldn't use a hammer to brush your teeth, not every app needs AI to be brilliant. Sometimes it genuinely makes things better, and sometimes... well, it's about as useful as a chocolate teapot.
In this article, we're going to cut through the noise and marketing speak to explore what AI in mobile apps really means for you. No fancy jargon, no overselling – just honest insights from folks who've been elbow-deep in app development since before AI became the buzzword du jour.
We'll look at real examples where AI genuinely makes apps better (and they do exist!), point out where it's just window dressing, and give you the knowledge to spot the difference. Think of this as your friendly guide to navigating the increasingly AI-filled app landscape.
By the time you finish reading, you'll understand:
- What AI in mobile apps can and can't actually do (right now)
- How to spot genuinely useful AI features versus marketing fluff
- What to expect from AI-powered apps in the real world
- How to decide whether an AI feature is worth your time (and battery life)
So, grab a cuppa, get comfortable, and let's demystify this whole AI in apps business together. After all, your phone should work for you, not baffle you with buzzwords.
The Current State of AI in Mobile Apps
Let's take a moment to look at what's actually happening with AI in mobile apps right now. Think of it as opening the bonnet of your car – we're going to see what's really powering all these AI features that companies keep talking about.
First off, let's address the elephant in the room: not everything labelled "AI" in today's apps actually involves artificial intelligence. Sometimes it's more like a very clever calculator with good marketing. But that doesn't mean there aren't some genuinely impressive implementations out there.
The Good: Where AI Actually Shines
Some of the most useful AI features we're seeing in mobile apps today are quietly working behind the scenes to make your life easier. Take photo enhancement apps, for instance. When you use an app like Google Photos to restore an old, damaged family photo, you're seeing AI at its best. It's learned from millions of photos what a clear, undamaged picture should look like, and it applies that knowledge to fix your treasured memories.
Language translation apps have made incredible strides too. Remember the days when translation apps would give you completely bonkers results that made you sound like a confused tourist? Now, apps like DeepL can handle context and nuance in a way that actually helps you have proper conversations in different languages.
The Not-So-Good: AI for AI's Sake
On the flip side, we've seen plenty of apps jumping on the AI bandwagon without adding any real value. We recently came across a to-do list app that proudly advertised its "AI-powered task prioritisation." In reality, it was just sorting tasks by deadline and user-assigned importance – something apps have been doing since before the iPhone existed.
Or consider the fitness apps that claim to use "advanced AI" to count your steps. In most cases, they're simply using your phone's built-in pedometer with some basic calculations. It's like putting racing stripes on a bicycle – it might look flashy, but it's not making you go any faster.
The Surprising: Unexpected Uses of AI
Some of the most interesting AI implementations we've seen are in areas where you might not expect them. Mental health apps are using natural language processing to detect changes in user's writing patterns that might indicate they're struggling and need support. Shopping apps are using AI to help colourblind users by describing product colours in more meaningful ways than just their names.
These examples show how AI can be truly valuable when it solves real problems rather than just adding another feature to the marketing list.
What's Actually Working?
From our experience building apps at Glance, we've noticed a pattern: the most successful AI features tend to share three characteristics:
- They solve a specific, well-defined problem rather than trying to be a magical do-everything solution.
- They work seamlessly in the background without constant user input or attention.
- They provide clear value that users can actually experience, not just technical achievements that look good on paper.
For example, we recently worked with a small business app that used AI to automatically categorise expenses by analysing receipt photos. The AI wasn't the star of the show – it was just quietly making life easier for busy business owners. That's the sweet spot we should be aiming for.
The Real-World Impact
It's worth noting that even the best AI features come with trade-offs. That brilliant photo enhancement feature might drain your battery faster. The smart language translation might need an internet connection to work. These aren't necessarily deal-breakers, but they're part of the reality that often gets glossed over in the marketing materials.
The current state of AI in mobile apps is a bit like British weather – mixed, with occasional bright spots. While there's certainly some drizzle (unnecessary AI features that add complexity without value), there are also some lovely sunny days (genuinely helpful implementations that make our lives better).
As we move forward, the key isn't to have more AI in apps – it's to have better AI in apps. And that starts with understanding what's actually possible and valuable, rather than what makes for good marketing copy.
Behind the Curtain: How AI Actually Works in Mobile Apps
Remember when you were little and thought there was a tiny person living inside the television? Well, when most people think about AI in their mobile apps, they imagine something similar – a clever little brain living inside their phone, thinking deep thoughts about their photos or messages. The reality is both more mundane and more fascinating.
The Magic Behind the Scenes
Let's imagine you're using an app that can recognise what's in your photos. When you point your camera at your cat (who, let's be honest, is probably ignoring you), the app instantly tells you "That's a cat!" It seems like magic, but what's really happening?
Your phone isn't actually thinking or understanding what a cat is. Instead, it's following a set of incredibly detailed instructions – think of it like a massive recipe book. This recipe book was created by showing millions of pictures to a computer system (that's the 'training' part of AI), and the system learned to spot patterns. When you take a photo, your app compares what it sees to all these patterns it learned about.
Where's All This Happening?
Here's where it gets interesting. When an app tells you it's using AI, the clever bits usually aren't happening on your phone at all. Most of the heavy lifting happens in massive data centres – imagine rows upon rows of powerful computers, all working together. Your phone is more like a messenger, sending your photo to these computers and waiting for an answer.
This is why many AI features need an internet connection to work. It's also why some apps seem to work better when you're on WiFi than when you're using mobile data in the middle of nowhere (sorry, Cornwall).
On-Device vs Cloud AI: The Trade-offs
Some AI features do work directly on your phone – we call this "on-device AI." It's like having a mini version of those massive data centres, optimised to run on your phone. The advantage? It works anywhere, even without internet, and it's usually better for privacy since your data stays on your phone.
The downside? On-device AI is usually less powerful than its cloud-based cousin. It's like comparing a homemade pizza to one from a professional pizza oven – both can be good, but they have different capabilities.
The Real Costs (That Nobody Talks About)
When we're building apps at Glance, one of the biggest conversations we have with clients is about the hidden costs of AI features. Here's what usually surprises them:
Processing Power: AI features can be proper power-hungry beasts. That clever photo enhancement feature might be why your phone feels warm and your battery drains faster than a bathtub with the plug out.
Storage Space: On-device AI models need to store their "recipe books" somewhere on your phone. A good speech recognition system might need hundreds of megabytes – that's quite a few episodes of your favourite podcast you won't be able to download.
Development Costs: Training AI models isn't cheap. When an app offers AI features, someone's paying for all those expensive computers and the electricity they use. This often means either higher app prices or more ads.
What This Means for You
Understanding how AI works in apps helps you make better decisions about which apps to use and when. That brilliant AI feature might not be worth it if it means your phone dies by lunchtime. Similarly, if privacy is important to you, you might prefer apps that use on-device AI, even if they're not quite as powerful.
A Peek at Our Process
At Glance, when we're considering adding AI features to an app, we ask ourselves questions like:
- Does this actually need AI, or could we achieve the same result with simpler technology?
- Will this feature work well enough on most phones, not just the latest models?
- Is the trade-off between functionality and battery life acceptable?
- How can we make this work offline when possible?
Sometimes, the honest answer is that traditional non-AI approaches might work better. For instance, we once replaced a complex AI-based content recommendation system with a simpler algorithm based on user preferences and behaviour. Not only did it work better, but it also used less battery and data.
The Future of Mobile AI
The exciting bit is that this technology is improving rapidly. Phones are getting more powerful, AI models are getting more efficient, and developers are finding clever ways to balance performance and resource use. We're gradually moving towards a future where more AI features can run directly on your phone, making them faster and more private.
Think of it like the early days of mobile games. Remember when phones could barely handle Snake? Now we're running console-quality games on our phones. AI is on a similar journey – what requires massive data centres today might run smoothly on your phone tomorrow.
Understanding how AI works in mobile apps isn't just about satisfying curiosity – it helps you become a more informed user. Next time an app boasts about its AI features, you'll know what questions to ask and what trade-offs to consider.
Wrapping Up
We've taken quite a journey through the world of AI in mobile apps, haven't we? From peeking behind the curtain to separating genuine innovation from clever marketing, we've covered a lot of ground. Now, let's bring it all together and look at what this means for you.
The truth about AI in mobile apps isn't as flashy as the headlines might suggest, but in many ways, it's more interesting. It's not about magical thinking machines in our pockets – it's about thoughtful applications of technology that can genuinely make our daily lives a bit easier, a touch more efficient, or occasionally even a little more delightful.
Think of AI like salt in cooking. Used carefully and purposefully, it can enhance everything else and create something wonderful. But too much, or using it just because you can, ruins the whole dish. As we've seen through various examples, the best AI implementations often aren't the ones shouting about themselves from the rooftops – they're the ones quietly making things work better behind the scenes.
At Glance, our eight years of experience building apps has taught us that the most successful mobile experiences aren't about chasing the latest buzzwords or cramming in trendy features. They're about understanding what users genuinely need and finding the best way to deliver it. Sometimes that means using cutting-edge AI, and sometimes it means sticking with simpler, proven solutions that just work better.
Looking ahead, we're genuinely excited about the future of AI in mobile apps. Not because of the potential for more flashy features, but because we're seeing the technology mature in ways that create real value. The focus is shifting from "What can AI do?" to "What should AI do?" – and that's a far more interesting question.
For you, as someone who uses apps every day, here's what we hope you'll take away:
Trust your instincts. If an app's AI features seem to make your life genuinely easier or better, brilliant. If they feel more like a gimmick or a drain on your battery, it's perfectly fine to look for alternatives. You're the best judge of what works for you.
Don't feel pressured to embrace AI features just because they're there. Sometimes the simple approach is the best approach. After all, you don't need AI to tell you it's raining when you can look out the window.
Most importantly, remember that technology should serve you, not the other way around. The best apps, AI-powered or not, are the ones that fit seamlessly into your life and help you do what you want to do with minimum fuss and maximum reliability.
As we wrap up, we'd love to hear your thoughts and experiences with AI in mobile apps. What features have you found genuinely useful? Which ones seemed more like marketing fluff? Your experiences and insights help us and other developers create better, more meaningful mobile experiences for everyone.
The future of mobile apps isn't about AI taking over – it's about AI fitting in, helping out, and knowing when to get out of the way. And that's something worth looking forward to, don't you think?
After all, at the end of the day, the best technology is the kind that makes you forget it's there at all. Like a good cup of tea, it should just work, bringing a bit of comfort and efficiency to your day without any fuss or bother.
Want to learn more about how we approach AI and app development at Glance? We're always happy to chat about creating mobile experiences that actually make a difference. Drop us a line!
