Do native AI devices have a future, or will smartphones absorb the shift?

After early native AI gadgets failed to take off, big players are exploring AI-first hardware while analysts and founders debate whether real change will happen through new devices or evolving phones

Native AI devices have moved from a niche experiment to a topic of wider industry debate. Early products such as the Rabbit R1 and the Humane AI Pin made headlines in 2024 by promising an AI-first way to interact with technology, but neither managed to build a sustainable consumer market. Now, with companies like OpenAI and Apple reportedly exploring their own AI-focused hardware, analysts and industry insiders are split on whether the category is ready for a second attempt, or whether the future of “native AI” will play out inside smartphones instead of through entirely new gadgets.

 

Native AI devices are products designed around continuous, AI-driven interaction rather than traditional app-based software. Instead of relying on a screen full of apps, these devices are meant to work primarily through vision, voice, context, and sensors, with AI acting as the main interface for everyday tasks.

 

 

That shift away from the app-centric model is also where some of the challenges begin, said Navkender Singh, Associate Vice President of Data & Analytics: Devices & Ecosystem for India and South Asia at IDC. He said that smartphones, along with their rich application ecosystems, have been the “window to the world” for over a decade, and asking people to completely switch to a new category of hardware is difficult. He added that this ecosystem expands the role of smartphones beyond AI, bringing in social media, streaming, and a wide range of other services that native AI devices currently do not replace.

 

Singh also said, “the timing of these launches also played a role, as consumer-facing AI technology was still in the early stages.”

 

Mohammad Faisal Ali Kawoosa, Chief Analyst at Techarc, echoed that view and said AI itself still needs to mature further before native AI devices can see wider adoption. In his view, such products need more than generative AI and require more “agentic” systems that can take actions and adapt to users in a more personalised way, something the first wave largely lacked.

The analysts' view aligned with those of Dhananjay Yadav, founder of Indian AI hardware startup NeoSapien. He said the early devices tried to do too much at once. He said many users could not clearly explain what those products were meant to do in a single sentence, and that hardware which feels vague or gimmicky quickly loses relevance.

 

On the relevance point, Singh pointed out that some of the early AI devices did not offer strong enough use cases to convince users to make the transition.

Hype around early native AI devices

The category first gained wider attention in 2024 with products such as the Rabbit R1 and the Humane AI Pin. These devices were positioned either as alternatives to smartphones or as companions that could handle AI tasks in a more direct way.

 

The Rabbit R1 focused on voice-based interactions and task automation, while the Humane AI Pin was designed as a wearable that could respond to voice commands and project information when needed. Both products received significant attention ahead of launch and were widely discussed as early signs of a possible shift away from app-driven computing.

 

However, despite the initial interest, neither device managed to create a broader consumer market. Reviews and early user feedback pointed to gaps in functionality, reliability, and everyday usefulness, and the products struggled to justify themselves as replacements or even strong companions to existing smartphones.

Can big players turn things around

The category may now see renewed attention as larger companies begin to explore it seriously. OpenAI is reportedly working on its first consumer hardware product in collaboration with former Apple design chief Jony Ive, with reports suggesting a small, screen-free device focused on audio-based interaction and continuous assistance. The company has indicated this will be part of a broader push into AI-first hardware rather than a single experimental product.

 

Apple, meanwhile, is reportedly exploring an AirTag-sized wearable AI device that would rely on cameras, microphones, and on-device processing to understand a user’s surroundings and respond through voice. According to The Information, the project is separate from the Apple Watch and AirPods and is still in early development, but it suggests Apple is at least testing the idea of a standalone AI-first product.

Singh said the entry of larger players could change the picture, especially since they already have AI capabilities, platforms, and ecosystems in place. He also said, “specific form factors such as TWS earbuds and smart glasses, which already complement smartphones, could be better suited as native AI devices.”

 

At the same time, it remains unclear whether these products are intended to replace smartphones, sit alongside them, or simply explore new interaction models.

Can smartphones evolve into native AI devices

Another possibility is that native AI experiences may not arrive through entirely new gadgets at all. Instead, existing devices, especially smartphones, could gradually take on many of the same characteristics.

 

In 2024, Nothing CEO Carl Pei said he expects smartphones to remain the primary consumer form factor, but argued that the way people use them will change. According to him, smartphones are likely to move toward a “post-app” model, where the operating system becomes more personalised and dynamic, and where AI plays a central role in how users interact with services and information.

 

Kawoosa echoed a similar view. He said, “future native AI devices could be drastically different from smartphones or could even be an evolution of smartphones, similar to how smartphones evolved from feature phones.”

 

In his view, future AI-first devices could look very different from today’s phones, or could simply represent a new phase of what a phone is.

Can native AI devices find a market in India

The question of adoption looks different in India, where price sensitivity, language diversity, and usage patterns shape how new device categories succeed or fail.

 

Yadav said India could become one of the more important markets for native AI devices, but for different reasons than in the US. In his view, many high-value conversations in India still happen offline — in meetings, clinics, factories, sales visits, and family-run businesses. If native AI devices succeed in India, he said, it will not be because they replace phones, but because they quietly assist real-world conversations and workflows that phones were not designed to handle.

 

He added that Indian users tend to be more outcome-oriented and less tolerant of vague promises around “AI magic”. Devices, in his view, will need to prove that they save time, reduce follow-ups, or prevent mistakes. The bigger challenges in India, he said, will be achieving high reliability, managing battery constraints, dealing with background execution limits on Android, and handling linguistic diversity. “Indian users need the Activa of AI, not the Tesla of AI,” he said, arguing that dependability will matter more than novelty.

Can sovereign AI models help native AI devices in India

One open question is whether the development of an Indian “sovereign” AI model could improve the prospects of native AI devices in the local market, particularly when it comes to language support, accent handling, and understanding local context.

 

Yadav said a strong domestic model with better performance on Indic languages and on-device efficiency would be useful, but he argued that models alone will not determine the success of AI-native hardware.

 

In his view, the bigger problem is “orchestrating multiple models, handling real-world audio quality, managing latency, and delivering consistent results.”

 

He said his startup NeoSapien has designed its first AI device, the Neo 1, which tracks real life conversations for summaries and transcripts, to be model-agnostic, evaluating both Indian and global models and adopting whichever performs better on accuracy, cost, latency, or privacy.

 

If a sovereign Indian model proves stronger in specific areas such as language support, he said the company would consider integrating it. However, he added that NeoSapien is not planning to build its own foundation model and is instead focused on building AI-native devices and systems on top of existing models.

 

“We also have no plans to build a foundation model ourselves. Our focus is on building reliable AI-native devices and systems on top of the best available models,” said Yadav.

Will privacy and data protection affect AI device adoption in India

As native AI devices move closer to everyday conversations and personal routines, questions around data security and privacy are likely to follow. However, there is disagreement over how much these concerns will shape consumer behaviour in India.

 

Navkender Singh said privacy has not historically been a decisive factor for most consumers in the Indian market. He stated that users generally do not differentiate between whether AI processing happens on-device or in the cloud, and pointed out that many already accept personalised advertising and data collection as part of using smartphones and online services.

 

“So let's say any device which has AI, consumers right now don't care if it's on device or off device, and anyway most of the consumers leave personalised ads enabled when they switch on the smartphone,” Singh added.

 

In his view, even companies that have tried to position privacy as a key selling point have seen limited impact on mass consumer behaviour in India. Singh added that while people may be more curious or cautious about a standalone device that is “always listening”, everyday usage patterns suggest that this concern does not necessarily translate into rejection, citing the widespread adoption of always-on smart speakers as an example. He said privacy tends to become a larger issue from a regulatory or government perspective, or after major data breaches, rather than as a primary factor in day-to-day purchasing decisions.

 

Yadav said that he broadly agrees that, in India, privacy expectations are still evolving, but added that trust is not optional for native AI devices. He argued that these products raise a different set of concerns because they sit much closer to real human conversations than most software. If handled casually, he said, they can quickly feel invasive, and users will expect “transparency, selectivity, and clear boundaries around what is captured, stored, and processed.”

 

He said NeoSapien’s approach is to avoid storing raw audio, instead processing conversations in encrypted memory, extracting the required information, and then deleting the recordings. According to him, users should be able to pause capture, delete specific conversations, or remove their data entirely. Yadav argued that trust is likely to become a key differentiator in this category, and that devices which overreach on data collection may gain short-term capabilities but risk losing users over time.