We were promised an AI wearable revolution in 2025 – will 2026 finally deliver?

Two years ago, “AI” was positioned as the next great leap for wearables. Smarter coaching. Conversational assistants on your wrist. Personalised health insights that felt closer to a doctor than a dashboard. Fast-forward to 2025, and the picture looks a lot more complicated.

AI is everywhere in smartwatches and smart rings, but not always where brands said it would be, or in ways users actually asked for. Some implementations have quietly improved how we understand our health. Others have sparked backlash, confusion, or a sense that “AI” became a business model before it became a benefit.

So, two years on, has AI in wearables proven itself useful, or are we still waiting for the point where it genuinely earns its place?

The promise vs the reality

The original pitch was simple. Wearables already collect vast amounts of data, so – we were told – AI would be the missing layer that finally makes sense of it all. Instead of charts and scores, we’d get explanations, predictions, and guidance tailored to our bodies and habits.

What actually emerged was a split. On one side, AI as presentation, with summaries, explanations, coaching prompts, and chat-style interfaces that sit on top of existing data.

On the other hand, AI as physiology with new derived metrics and models that deepen what wearables can tell us about stress, recovery, and long-term health.

The brands that leaned too hard into the first camp have struggled to convince users. The ones focused on the second have made the strongest case for AI actually belonging in wearables.

Garmin: AI as a pricing strategy

Garmin’s biggest AI moment didn’t arrive as a breakthrough feature, but as a controversy. The launch of Connect+, a paid tier that bundled advanced insights and AI-style summaries, immediately ran into resistance from a user base that had long trusted the company for its no-nonsense, no-subscription positioning.

The features themselves weren’t inherently bad. The problem was perception. AI felt like something that had been put behind a paywall simply because it could be, not framed as a leap forward in understanding your training or health.

In that sense, Garmin tested how much goodwill it had built up over the years. The backlash suggests that, for core users, AI needs to feel additive and essential, not optional and monetised.

Apple: AI lives on the iPhone, not the Watch

Apple’s approach has been more restrained and arguably more honest. Apple Intelligence never truly arrived on the Apple Watch. Instead, the Watch became a surface for AI-powered experiences driven by the iPhone.

Features like smarter notifications, contextual messaging help, and more recently, Workout Buddy-style coaching lean on Apple Intelligence in the background. The Watch delivers the moment, but not the intelligence itself.

That explains why Apple’s AI efforts feel less dramatic on the wrist than on the phone. The Watch is an interface, deliberately limited, not an AI computer.

That restraint has kept expectations in check, but it’s also left the Watch feeling like a secondary beneficiary of Apple’s AI strategy rather than a platform where AI is being fully explored.

Samsung: health modelling beats chatbot energy

Samsung entered this phase with a head start. Its health features were already deeper than most, and recent additions, like vascular load, which estimates cardiovascular strain during sleep, reinforce that strength.

What’s notable is that Samsung’s most compelling “AI” features don’t look like AI at all. They’re advanced physiological models, built quietly into Samsung Health, without a big language-model-shaped spotlight.

Yes, Samsung has talked up Gemini and voice-based experiences on the Watch, but they feel like add-ons. The real progress is happening where AI helps reinterpret sensor data into something more meaningful for long-term health.

Google and Fitbit: AI as coaching, not hardware

If you’re looking for AI in the Pixel Watch, you won’t find a dramatic “assistant on your wrist” story. Instead, Google’s AI influence shows up through the Fitbit app via personalised run recommendations, adaptive coaching, and increasingly conversational health guidance inside the app.

Fitbit’s lack of new hardware over the past couple of years has made the brand feel quieter, but the signals point to software doing the heavy lifting. AI becomes a way to justify Premium, deepen engagement, and turn historical data into forward-looking guidance.

Oura: the strongest argument for AI done right

If there’s one category where AI feels genuinely at home, it’s smart rings, and Oura has been the clearest example.

The ring itself does very little beyond sensing. Well, that may be an oversimplification, but the ring itself is just that: a sensor array and a battery in a circular shell.

All the intelligence lives in the app. Features like Oura Advisor don’t try to replace doctors or coaches; they explain trends, connect dots between sleep, stress, and activity, and help users understand why something changed.

This is AI as interpreter, not oracle, and it works because it respects the limits of both the hardware and the user’s attention. It also hints at where wearables may be headed more broadly.

Where AI in wearables is actually going in 2026

Speaking of the future, the signs are clearer than the hype ever was. Instead of becoming the headline feature of wearables, AI is becoming invisible infrastructure.

In 2026, expect less talk of assistants and more focus on prediction. Instead of telling you what happened, wearables will increasingly tell you what’s likely to happen next: fatigue accumulation, injury risk, sleep debt, cardiovascular strain trends.

We’ll also see AI lean more toward coaching than conversation, which is something I begged companies to do since they started floating the idea AI as a feature. Adaptive plans, subtle nudges, and better-timed recommendations will matter far more than chat interfaces on tiny screens.

Crucially, more intelligence will shift on-device, not to run large language models, but to enable faster pattern recognition, better privacy, and real-time feedback without a constant cloud connection. At least, that's what I hope.

And form factors will diversify. Earbuds with built-in cameras, smart earrings, and AI-powered glasses are better suited to ambient, context-aware AI than smartwatches ever were. The wrist may remain the hub, but not the whole story.

So, useful or not?

Two years in, AI in wearables hasn’t transformed the category, but it has certainly improved it. When AI tries to be the product, it struggles. However, when it acts as the translator between raw data and real-world decisions, it earns its place.

The biggest shift at the end of 2025 is that AI became the user manual for the data they’ve been collecting all along. And in 2026, that – not hype – is likely what finally makes it indispensable.