AI in Smartphones 2026: How Artificial Intelligence is Changing Your Phone

Every phone manufacturer is selling you AI. Most of it is nonsense. Some of it is genuinely useful. The trick is knowing which is which.

I've been testing smartphones for over a decade now, and I've seen plenty of marketing trends come and go. 3D displays. Modular phones. "Military-grade" durability. Curved screens. Each one arrived with breathless press releases and departed quietly when nobody cared. In 2026, the buzzword is AI, and it's everywhere — stamped on packaging, splashed across launch event stages, whispered reverently by product managers in rehearsed keynotes. Every single phone brand, from Apple to Xiaomi to Realme, wants you to believe that artificial intelligence has fundamentally changed what your phone can do.

Some of that is true. A lot of it isn't. Let me sort through the noise.

The Stuff That Actually Works

I want to start with the honest wins, because dismissing everything would be just as dishonest as the marketing itself. There are AI features on phones today that I use daily, that solve real problems, and that I would genuinely miss if they disappeared tomorrow.

Photo Erasers and Object Removal

This is the one AI feature that has crossed the line from gimmick to necessity. Google started it with Magic Eraser on the Pixel, Samsung followed with Object Eraser in One UI, and Apple eventually joined with Clean Up in iOS 18. In 2026, every phone above Rs 20,000 has some version of this. You tap on an unwanted person in the background, a stray auto-rickshaw photobombing your Taj Mahal shot, a plastic bag ruining your beach photo — and the phone removes it. Fills in the space. Makes it look like it was never there.

Does it work perfectly every time? No. Complex backgrounds with repeating patterns still confuse it. Try removing a person standing in front of a crowded market in Chandni Chowk and you'll get smudged chaos. But for straightforward removals — a stranger walking through your family photo at Cubbon Park, an electricity wire cutting across a sunset, a signboard you don't want in the frame — it works remarkably well. I'd estimate a success rate of about 80% in my day-to-day use, which is high enough to be genuinely useful rather than just a party trick.

This is what real AI utility looks like. It solves a problem that existed before, solves it well enough to rely on, and doesn't require you to understand anything about how it works.

Live Translation During Calls

Here's one that matters enormously in India, a country with 22 official languages and hundreds of dialects, where a customer service call might require switching between Hindi, English, Tamil, and back again mid-sentence. Samsung's Live Translate and Google's call translation on Pixel phones now support real-time translation during voice calls. You speak in Hindi, the other person hears English. They reply in English, you hear Hindi. It happens with a slight delay — maybe a second or two — and the translations are imperfect, especially with colloquial expressions and slang. But it works.

I tested this extensively with a friend in Chennai who speaks primarily Tamil, while I'm more comfortable in Hindi. We had a fifteen-minute phone conversation where the AI translated between us in near real-time. Was it flawless? Absolutely not. It mangled a few idioms and struggled with the speed at which my friend speaks. But we understood each other, we completed the conversation, and neither of us had to awkwardly switch to English as a bridge language. For a country where language barriers are a daily reality — where a migrant worker from Bihar calling a government helpline in Karnataka faces a genuine communication wall — this is meaningful technology.

The Indian use case for this feature alone justifies the "AI phone" label more than anything else these companies are marketing.

Smart Text Suggestions and Writing Assistance

This one is quieter but no less useful. The AI-powered text prediction on modern phones has gotten genuinely good. I'm not talking about the basic autocorrect that's existed for fifteen years. I'm talking about the system that reads the context of your conversation and suggests entire reply sentences. Someone sends you "What time are you reaching?" and your phone offers "I'll be there by 7" or "Running 10 minutes late" based on your calendar, your location, and your past patterns.

Samsung and Google have pushed this further with AI-composed replies for emails, AI tone adjustments (make this message more formal, more friendly, more concise), and summarisation tools. The tone adjustment is particularly handy for professional communication — I've used it to soften blunt messages to clients and to make casual messages to colleagues sound more appropriate when I accidentally started typing as if I were messaging a friend.

None of this is magic. It's pattern recognition applied to language, and it's been improving incrementally for years. But the 2026 versions are noticeably better than what we had even eighteen months ago, and they've reached a point where they save me real time on a daily basis.

Promising but Half-Baked

Then there's the middle tier: features that show genuine potential but aren't ready for prime time. They work sometimes. They impress in demos. They frustrate in daily use.

AI Summaries

Every phone maker now wants to summarise things for you. Samsung will summarise your web articles. Apple will summarise your notifications. Google will summarise your emails. The pitch is compelling: you're drowning in information, and AI will distil it down to what matters.

In practice, the summaries are often either too vague to be useful or too inaccurate to be trusted. I tested Apple's notification summary feature over two weeks and found that it regularly merged unrelated WhatsApp messages into a single nonsensical summary. One memorable example combined a message from my mother about dinner plans with a group chat argument about cricket into a summary that read: "Your mother wants to discuss the team selection for dinner." Hilarious, but not helpful.

The WhatsApp group summarisation feature, which Samsung and Google both offer in their own ways, is the one I most want to work properly. Anyone who's part of an Indian WhatsApp family group knows the pain — you leave your phone for two hours and come back to 347 messages, of which 340 are good morning images, forwarded videos, and arguments about politics. An AI that could tell me "Uncle Rajesh shared a wedding invitation for March 22nd, your cousin asked about train tickets to Delhi, and the rest is noise" would be worth its weight in gold. We're not there yet. The summaries miss important details, include irrelevant ones, and occasionally hallucinate information that nobody actually said. But the direction is right, and I suspect this will be genuinely useful within a year or two.

Generative Wallpapers and Image Creation

Samsung, Google, and Apple all now let you create custom wallpapers using AI image generation. Type a prompt — "mountain lake at sunset with cherry blossoms" — and the phone generates a unique wallpaper. It's neat the first three times you do it. Then the novelty wears off, and you realise you've spent fifteen minutes generating wallpapers when you could have just picked one from the pre-loaded options that look better anyway.

The generated images have a telltale AI quality — slightly too smooth, slightly too perfect, with that uncanny-valley sheen that makes everything look like a stock photo from a parallel universe. Samsung's implementation on One UI 7 is the most polished, Apple's is the most conservative, and Google's is the most creative but also the most likely to produce something that looks like a fever dream.

Fun? Sure. Useful? Debatable. Worth marketing as a headline AI feature? Absolutely not.

Pure Marketing Nonsense

And now we arrive at the bottom of the barrel — the features that use the word "AI" the way food companies use "natural" or "artisanal." Technically not a lie. Practically meaningless.

"AI-Enhanced" Camera Modes

This is the one that irritates me most. Nearly every phone brand has renamed its existing camera processing pipeline as "AI photography." The scene detection that identifies whether you're shooting a sunset, a plate of food, or a face, and adjusts colour and exposure accordingly? That's existed since 2018. The HDR processing that combines multiple exposures into a single well-lit image? That's been standard for half a decade. The night mode that takes long exposures and merges them? Old news.

But in 2026, these same features have been rebadged. What was "Scene Optimizer" is now "AI Scene Optimizer." What was "Night Mode" is now "AI Night Photography." What was "Portrait Mode" is now "AI Portrait Enhancement." The algorithms have improved incrementally, as they do every year, but the "AI" prefix is doing almost no extra work. It's the same computational photography process, given a fresh coat of marketing paint.

I asked a product manager at a major phone brand, off the record, whether their "AI camera" was meaningfully different from what they shipped two years ago. The honest answer: "The neural networks are updated, the models are bigger, the results are slightly better. But the approach is the same. We call it AI now because consumers expect AI." At least they were honest about it.

"AI Battery Management"

Another favourite. Your phone learns your usage patterns and optimises battery allocation accordingly. It knows you check Instagram at lunch, play games in the evening, and barely touch your phone after midnight, so it adjusts background processes to match.

This is just... battery management. Android has been doing adaptive battery optimisation since Android 9 Pie in 2018. iOS has had optimised battery charging since iOS 13. Calling it "AI battery management" in 2026 is like calling your car's cruise control "AI speed management." It's pattern-based automation, and while it's gotten better over the years, slapping "AI" on it doesn't make it new.

The Privacy Question Nobody Wants to Answer

Here's where my fascination with phone AI turns to genuine concern.

When your phone's AI removes an object from a photo, where does the processing happen? When it translates your phone call in real time, is that conversation being sent to a server somewhere? When it summarises your WhatsApp messages, who else might have access to that summary?

The answers vary by brand and by feature, and most companies are deliberately vague about it.

Apple has been the most transparent, pushing its "Apple Intelligence" processing through what it calls Private Cloud Compute — a system where data sent to Apple's servers is processed in encrypted enclaves and, Apple claims, never stored or accessible to Apple employees. Google processes some AI tasks on-device and some in the cloud, with varying levels of clarity about which is which. Samsung uses a mix of on-device processing and partnerships with Google and its own cloud services, and the privacy documentation is a maze of corporate language that would take a law degree to parse.

For Indian consumers, this matters more than most people realise. India's Digital Personal Data Protection Act, which came into force in 2023, establishes rules about data processing and consent. But the enforcement mechanisms are still being built, and the nuances of AI processing — where your voice data goes during a translated call, whether your photos are used to train future AI models, whether your message summaries are stored temporarily or permanently — exist in a grey area that the law hasn't fully addressed.

Think about what your phone's AI needs access to in order to work: your photos, your messages, your call audio, your location patterns, your app usage, your typing habits. This is the most intimate dataset any technology has ever assembled about an individual. The question isn't whether AI features are useful. It's whether the trade-off is worth it, and whether you're making that trade-off with informed consent or marketing-induced obliviousness.

I don't have an answer to that. But I think it's a question that deserves more attention than it's getting, especially in a country of 1.4 billion people where digital literacy varies enormously and where the phrase "I agree to the terms and conditions" is clicked through without reading by roughly 100% of the population.

NPU Chips: The Engine Behind the Hype

If you've read any phone review in the past year, you've encountered the term "NPU" — Neural Processing Unit. Qualcomm's Snapdragon 8 Elite has one. MediaTek's Dimensity 9400 has one. Apple's A18 and A18 Pro have one. Samsung's Exynos chips have one. Everyone has one. But what does it actually do?

Let me explain this simply, because the tech press has done a poor job of it.

A regular processor (CPU) is a generalist. It can handle any task — calculations, app logic, system management — but it does everything one step at a time, in sequence. It's like a very smart person solving problems with pen and paper. A GPU (graphics processor) is optimised for doing many simple calculations simultaneously — great for rendering images and games, like having a thousand people each solve one simple sum at the same time.

An NPU is different from both. It's specifically designed to handle the kind of mathematics that AI and machine learning require: matrix multiplications, tensor operations, pattern recognition across massive datasets. It's not smarter than a CPU or faster than a GPU in general tasks. It's specialised. Think of it as a dedicated translator at the United Nations — they can't do the ambassador's job, but they can translate languages faster than anyone else in the room.

What this means in practice: when your phone identifies objects in a photo, processes natural language, generates an image, or runs any AI model, the NPU handles it. Without an NPU, these tasks would run on the CPU or GPU, draining battery faster and taking longer. With a dedicated NPU, AI features run more efficiently and, importantly, can run on-device rather than needing to send data to the cloud.

Snapdragon 8 Elite vs Dimensity 9400: The NPU Battle

Qualcomm's Hexagon NPU in the Snapdragon 8 Elite delivers around 75 TOPS (Tera Operations Per Second). MediaTek's APU in the Dimensity 9400 claims 80 TOPS. These numbers are measured differently by each company, so direct comparison is misleading, but both are capable of running large language models on-device — something that was impossible on phones just two years ago.

The practical difference between these two for most users? Almost nothing. Both can run the same AI features at comparable speeds. Qualcomm has a broader developer ecosystem, which means more third-party apps are optimised for its NPU. MediaTek is catching up, and for the built-in AI features that come with the phone's software, both chips perform equally well. If you're choosing a phone in 2026, the NPU brand should be near the bottom of your decision criteria.

The Rs 15,000 Question: Will AI Trickle Down?

This is the question that matters most for India, a market where the vast majority of phones sold cost less than Rs 20,000 and the sweet spot for most buyers sits between Rs 10,000 and Rs 15,000.

Right now, meaningful AI features are concentrated in flagships and upper mid-range phones. You need a reasonably powerful NPU to run on-device AI, and those chips live in Snapdragon 7-series and above, or Dimensity 8000-series and above. Below that, phones either lack the hardware to run AI models locally or rely entirely on cloud processing, which requires a stable internet connection — something that's not guaranteed in rural and semi-urban India where much of the country's phone market exists.

The optimistic view: chip efficiency improves every year. What required a flagship NPU in 2024 can run on a mid-range chip in 2026. Qualcomm's Snapdragon 6 Gen 4, expected later this year, is rumoured to include AI capabilities that match what the Snapdragon 8 Gen 2 offered in 2023. MediaTek's Dimensity 6300, already available in phones around Rs 12,000, includes a basic NPU that can handle photo enhancement and simple text tasks. The trickle-down is happening, just slowly.

The pessimistic view: the most useful AI features — real-time translation, on-device language models, generative image tools — require substantial processing power and memory. Budget phones with 4GB or 6GB of RAM simply can't run a billion-parameter language model alongside the operating system and your open apps. Cloud-based processing could bridge this gap, but that depends on data connectivity and raises the privacy concerns I mentioned earlier. And phone companies have less incentive to optimise AI for budget devices when they can use it as a selling point to push consumers toward more expensive models.

My honest assessment: by late 2027, phones in the Rs 12,000 to Rs 15,000 range will have basic AI features — photo cleanup, smart replies, simple summarisation. But the headline features that phone makers are using to sell their flagships today will remain flagship-exclusive for at least another two to three years. If you're buying a phone under Rs 15,000 in 2026 expecting the AI experience you see in Samsung's or Apple's advertisements, you'll be disappointed.

What the Brands Won't Tell You

There's an uncomfortable truth lurking beneath all the AI enthusiasm: most people don't use most AI features.

Internal data from phone companies — shared with me off the record by people at two major brands — suggests that fewer than 15% of users regularly engage with AI features beyond the basics (autocorrect, photo enhancement, voice assistants). The flashy demo features — generative wallpapers, AI image editing, circle-to-search style visual lookups — see a spike of usage in the first week after purchase and then drop off sharply. People try them, find them interesting, and go back to using their phones the way they always have.

This doesn't mean the features are worthless. It means the industry is ahead of user habits, which is normal for any technology shift. Touchscreens seemed gimmicky when the first iPhone launched. App stores seemed unnecessary when most people just wanted to make calls and send texts. These things take time to become natural parts of how people use their devices.

But there's a difference between a technology that's ahead of its time and a technology that's being force-fed to consumers who don't need it. Right now, AI on phones feels like a bit of both.

The Indian Context

India is a unique market for phone AI, and not just because of language diversity. Consider the infrastructure realities.

• Roughly 65% of India's mobile data connections are on 4G, with 5G still concentrated in major cities. Cloud-dependent AI features work poorly on congested 4G networks in tier-2 and tier-3 cities.
• Power cuts remain a reality in much of the country. AI features that drain battery faster are a harder sell when you can't guarantee your phone will be charged by evening.
• Data costs, while among the lowest in the world, still matter to price-sensitive consumers. AI features that require constant cloud communication eat into data plans.
• Digital literacy varies enormously. Features that require understanding prompts, editing AI outputs, or managing AI-generated content assume a level of tech comfort that doesn't exist universally.
• Language support remains patchy. Hindi and English AI features are reasonably mature. Try using AI summarisation in Kannada, Odia, or Assamese, and you'll find the experience ranges from mediocre to non-existent.

The brands that win in India won't be the ones with the most AI features. They'll be the ones whose AI features work reliably in Indian conditions — on patchy networks, in regional languages, on devices that cost what most Indians can actually afford.

A Brief Note on Voice Assistants

Google Assistant, Siri, and Samsung's Bixby have all been "enhanced with AI" in 2026. The improvements are real but uneven. Google Assistant is noticeably better at understanding context and follow-up questions. Siri is less noticeably better, though Apple's integration of large language models into Siri has made it marginally more conversational. Bixby remains Bixby — functional for device control, forgettable for everything else.

The most interesting development is on-device voice processing. Both the Snapdragon 8 Elite and the A18 Pro can process voice commands locally, without sending audio to the cloud. This means faster responses and better privacy. It also means your voice assistant works in airplane mode, in areas with no signal, and in situations where you'd rather not broadcast your queries to a server farm.

Is it enough to make voice assistants actually useful? For basic tasks — setting timers, making calls, sending messages, controlling smart home devices — yes, they've been useful for years. For complex tasks — "find me the cheapest flight to Goa next weekend and compare it with train options" — they're still clumsy. The gap between what voice assistants promise and what they deliver has narrowed, but it hasn't closed.

So Where Does This Leave Us?

I've spent the past three months deliberately testing every AI feature on five different flagship phones. I've used AI to edit photos, translate calls, summarise articles, generate images, compose emails, and manage my daily schedule. Some of these features have become part of my routine. Most haven't. A few actively annoyed me enough that I turned them off.

The phone industry wants you to believe that 2026 is the year AI changed everything about how you use your phone. That's an exaggeration. What's actually happening is more gradual and more interesting: AI is becoming another layer of computational power that makes certain tasks faster and easier, the way GPS made navigation easier and touchscreens made interaction easier. It's not a revolution. It's an evolution, and a slow one at that.

The useful stuff — photo cleanup, translation, smart suggestions — will keep getting better and will eventually feel as natural as autocorrect does today. The marketing fluff — "AI-enhanced" everything, generative gimmicks, rebranded old features — will fade away when the next buzzword arrives. And the privacy questions will only grow louder as AI gets more capable and more deeply embedded in how our phones operate.

The real test of any technology isn't whether it impresses you in a demo. It's whether you notice when it's gone. If Samsung or Apple removed AI photo erasing from their next update, I'd genuinely miss it. If they removed generative wallpapers, I wouldn't notice for months. That's the dividing line between substance and spectacle, and most of what's being sold as AI in 2026 falls on the spectacle side.

Which brings me to the question I keep coming back to, the one I deliberately won't answer because I think the honesty is in the uncertainty: is AI in smartphones the next great technological shift — the thing we'll look back on in ten years the way we look back on the App Store or 4G — or is it the next 3D TV, a technology that generated enormous hype, sold a few units on the strength of that hype, and then quietly disappeared when people realised they didn't actually need it?

I genuinely don't know. And I'm not sure anyone does, no matter how confidently they say otherwise.