If there’s one phone camera feature we leave in 2025, it should be this

The relentless pursuit of higher zoom capabilities in smartphone cameras has reached a critical juncture. While 100x zoom sounds impressive, the quality often falls short of expectations, relying heavily on artificial intelligence (AI) to fill in the gaps. This trend raises questions about the future of smartphone photography and whether we’re prioritizing quantity over quality.

The core issue isn’t the zoom itself, but how it’s achieved. Early iterations of high-zoom features, like Samsung’s 100x Space Zoom, were a novelty. However, as manufacturers push beyond optical limits, AI becomes increasingly crucial. This isn’t inherently bad; computational photography has revolutionized smartphone imaging. But over-reliance on AI can lead to images that look artificially enhanced, lacking the natural detail and texture we expect.

Recent tests on devices like the OnePlus 15 and Google Pixel 10 Pro demonstrate this. While both phones offer impressive zoom ranges, the results can be inconsistent. OnePlus, in an attempt to maintain zoom levels despite a smaller telephoto sensor, leans heavily on its DetailMax Engine. Google’s Pro Res Zoom, while excellent for static subjects, struggles with organic elements like people and foliage, often resulting in an unnatural appearance. DxOMark consistently highlights this trade-off in their camera reviews, noting the benefits and drawbacks of AI-powered zoom.

The solution isn’t simply more AI, but a renewed focus on hardware. As OnePlus’s experience shows, downgrading sensor size to compensate for AI processing is a flawed strategy. AI needs data – and that data comes from a quality sensor. Larger sensors with higher megapixel counts provide a richer source of information for AI algorithms to work with, resulting in more natural and detailed images.

We’re likely to see a resurgence in sensor technology. Sony, the leading manufacturer of smartphone image sensors, is already developing sensors with improved dynamic range and low-light performance. Sony’s latest innovations, like stacked CMOS sensors, promise to deliver significant improvements in image quality, even at high zoom levels. This will allow manufacturers to reduce their reliance on aggressive AI processing.

The future of AI in smartphone cameras lies in specialization. Instead of applying a blanket AI filter to every image, manufacturers will leverage semantic segmentation – the ability to identify and categorize different elements within a scene. This allows for targeted processing, applying AI enhancements only where they’re needed.

For example, AI could be used to sharpen architectural details while preserving the natural texture of skin tones. Google’s current approach, which prioritizes scenery over people, hints at this direction. Expect to see AI algorithms specifically trained to enhance different types of subjects – landscapes, portraits, macro shots, and more. This nuanced approach will deliver more realistic and visually appealing results.

Another emerging trend is “Computational Raw.” This combines the benefits of RAW image capture – maximum dynamic range and editing flexibility – with the power of computational photography. Instead of applying processing at the point of capture, Computational Raw captures a wealth of data and allows users to apply AI-powered enhancements during post-processing.

Apple’s ProRAW format is a prime example. It provides photographers with the control they need while still leveraging Apple’s computational photography engine. This approach caters to a growing segment of users who want more creative control over their images. PetaPixel’s coverage of Computational Raw highlights its potential to bridge the gap between smartphone photography and professional workflows.

Looking further ahead, the rise of the metaverse and spatial computing will drive new demands for smartphone cameras. Capturing 3D models and creating immersive experiences requires more than just high-resolution images; it demands depth information and accurate spatial mapping.

We’re already seeing smartphones equipped with LiDAR sensors, which measure distance using laser light. These sensors, combined with advanced AI algorithms, will enable the creation of realistic 3D models of objects and environments. This technology will be crucial for augmented reality (AR) applications and the development of the metaverse. The Verge’s coverage of Apple’s Vision Pro demonstrates the potential of spatial computing and the role of advanced camera technology.

The future of smartphone cameras isn’t just about more megapixels or higher zoom levels. It’s about intelligent hardware, specialized AI, and a focus on delivering natural, high-quality images that capture the world as we see it. The next generation of smartphone cameras will be less about trickery and more about truly enhancing our ability to see and share the world around us.