Like many people, I’ve been having fun playing with cool new AI applications on my phone. I love how my photos can be transformed into 3D images and short videos. I marvel at the speed with which notetakers produce nearly perfect transcripts of my conference calls. And thanks to my writing assistant, my emails have never been clearer.
What I don’t love is the toll this all takes on my battery. As someone who travels a lot, I find the need to frequently stop and plug in to be as annoying as driving an electric vehicle with a 90-mile range.
AI will soon be embedded into the devices we use every day. Deloitte predicts that over 30% of new smartphones will be AI-enabled this year, and Gartner expects AI PCs to account for 43% of all PC shipments.
But here’s the thing: all that AI power takes a lot of energy. Think about it – processing images, understanding our voices, and transcribing calls involves tons of calculations every second, and it pushes our devices to their limits. Lots of people have noticed this.
The current limitations of battery technology will throttle the potential of mobile AI, restricting innovation and usability. While many tasks are currently offloaded to the cloud, local processing will be required to deliver the responsiveness people will expect as the way we interact with our devices is reshaped.
AI is shifting the mobile user interface from taps and clicks to voice commands and gestures. The value of these efficiencies will be undercut by battery constraints, forcing users to remain tethered to power outlets or lug around external battery packs.
This is a problem that not enough people are talking about. We will soon face a tradeoff that no one wants: whether to harness AI’s full capabilities or preserve battery life.
The consequences are even more severe for professionals and businesses that rely on AI-driven tools. Mobile workers who depend on AI assistance for tasks such as real-time translation, automated data analysis and virtual meetings will be inconvenienced by devices that can’t sustain a full day’s work on a single charge. In industries such as healthcare, logistics and emergency response — where real-time AI-powered decision-making is already crucial — battery limitations could have serious operational consequences.
The primary power source for smartphones, tablets and laptops remains lithium-ion batteries. While they have made gradual improvements in energy density of about 5% per year over the last decade, the pace of progress is insufficient to match the rapidly increasing power demands of graphic processing units that are leaping ahead 30-fold in performance every 18 months.
Lithium-ion cells are reaching their physical limits. Their chemical constraints make it difficult to achieve significant leaps in energy density without compromising safety. Alternatives like solid-state batteries and lithium-sulfur batteries hold the greatest promise for significant short-term gains in energy density and better scaling in the future.
To fully realize AI’s potential in mobile computing, the technology industry must accelerate breakthroughs in three critical areas:
Higher Energy Density Batteries. The most immediate solution is increasing the energy density of batteries, allowing them to store more power without increasing size or weight. Advances in solid-state and silicon-anode battery technology show promise in achieving higher energy density levels.
Faster Charging Capabilities. Ultra-fast charging technology, which enables devices to reach 80 percent capacity in under 15 minutes, could mitigate the impact of rapid battery drain. Improvements in wireless charging efficiency can ensure seamless power replenishment for users on the go.
More Efficient AI Processing. AI software and hardware must become more power efficient. Neural processing units, which can execute AI tasks with lower power consumption, are promising. AI can also be applied to learn user behavior and usage patterns to dynamically adjust power consumption.
If battery innovation fails to keep pace with AI’s rapid evolution, users will face increasing limitations. The promise of AI-powered mobile devices — effortless automation, enhanced creativity, and greater productivity — will be constrained by the power sources that enable them. Without bold advancements in energy storage, mobile AI could fall well short of its potential, tethering users to power sources rather than empowering them to work, create and explore freely.
The tech industry must treat energy storage as a critical frontier of innovation on par with advances in processor speed. Only through a concerted effort to advance energy technology can we ensure that AI-enhanced experiences remain practical, seamless, and truly transformative.
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