Important points
- AI research and development can divert a company’s attention from new hardware innovation efforts.
- Prioritizing advances in AI will delay addressing the key issues users face with existing models.
- Companies that rely on AI may focus on novelty over functionality and ignore providing value to cost-conscious buyers.
Smartphone makers are rushing to integrate artificial intelligence into their devices, betting that it will be the next big thing. While AI can certainly help in many ways, fixating on it can cause problems and inhibit other innovations that could have a bigger impact.
1 Companies are overlooking hardware innovation
Regardless of the iOS or Android platform, smartphone users unanimously agree that innovation in this space is slowing down. I’m not trying to blame this on AI capabilities, but it certainly doesn’t make the situation any better.
why? Because companies have limited R&D budgets, every dollar spent on advancing AI models devises new hardware innovations that could turn out to be much more groundbreaking. Because it is not spent on.
For example, flip phones are still far from their final form and still require years of refinement. However, the companies creating them may not be able to afford to do so if they are already spending a large portion of their R&D budgets on training large in-house language models.
2 Prioritizing AI leaves important questions unanswered
While no one is denying the utility that AI can provide, it may not be the best idea to prioritize adding new AI capabilities to devices that already have issues that need fixing. But that’s exactly what some smartphone companies seem to be doing.
For example, while Samsung’s Galaxy AI features are certainly new and exciting, most users prefer the company to fix shutter lag when taking high-resolution photos and reduce the amount of bloatware on Galaxy devices. There is no doubt that you are thinking about getting it.
Similarly, many Pixel users would like to see Google improve charging speed, video quality, and battery life, fix unstable lens transitions in the camera app, and make it the default for flagship devices rather than flooding them with more AI smart features. I’d like to work on offering 256 GB. .
The important thing here is that for most people, a smartphone is first a tool and then an integral part of their lifestyle. Therefore, it makes more sense to fix the problems you are currently facing than to simply add new features that are nice to have but not necessarily necessary.
3 AI features complicate the UI for non-technical users
There’s only so much you can add to a user interface before it becomes cluttered and confusing. While you may be able to navigate all the new icons, labels, and UI elements, most people aren’t tech-savvy enough to keep up with all the changes.
The learning curve for AI features can be steep, and results aren’t always visible immediately. Understanding and processing user input takes time, especially on low-end mobile phones. This can deter users from using the feature after trying it for a few days.
4 Companies prioritize novelty over value delivery
Since we are not in the midst of major hardware advances in smartphone technology, companies are using AI as a way to differentiate and provide novelty to their smartphones.
So what’s the problem? Well, it’s one thing to offer existing features at a lower price, it’s another to offer new features at a higher price. And the tech giant seems to be favoring the latter approach, which is bad news for value-conscious buyers looking for an affordable phone that does all the basics.
But as companies start integrating AI into everything, they’re forced to pay for those new features even if they don’t actually need them. I wish companies had focused on providing value rather than novelty.
To be clear, I’m not saying that everyone should prevent the integration of AI into smartphones. We argue that companies should not become so obsessed with AI that they overlook other important aspects of smartphones. AI capabilities should not be the reason why companies don’t solve existing problems or forget other avenues of innovation.