Most tech firms seem to follow a path that starts with mobile phones and leads to smart homes. For example, the genesis of Xiaomi’s AIoT revolution is to transform homes into intelligent spaces with devices that can be personalized and customized to the individual’s preferences while offering an unparalleled level of convenience and comfort.

One key advantage to moving into the smart home market is that brands can take advantage of existing smartphone and mobile services customers by offering them additional opportunities to move deeper into an ecosystem they’re already using, while also leveraging data they already have to provide consumers with a better experience than a competitor might.

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Google CEO Sundar Pichai said in October 2017 that Google believes the tech world is shifting from a “mobile-first to AI-first” focus. Based on this, it is obvious to see why Google Home matters: It’s the first step in Google’s transition to life as an AI company.

We’re moving into an AI-driven world and AIoT devices are the cornerstone of this future.

The goal of AIoT products ecosystem

As people consume more and more content, each moment of attention creates data that businesses can use. So far, the only problem is that data is typically siloed and scattered across numerous departments and companies. This is what we call the “consumer attention ecosystem.”

However, imagine being able to connect these data points across this ecosystem. With the help of smart devices equipped with AI, a company could have a far more comprehensive knowledge of its customers. Brands want to apply this knowledge to provide a personalized experience for each consumer across disparate moments and channels.

AI acts as data gathering, analysis, and decision-making system to act automatically in some instances, and work under the hood of an interface operated by humans via mobile devices to obtain critical instructions. AI can be applied to data from any of these home automation devices or systems to anticipate and predict user behavior, provide maintenance data, etc.

Without AI, the data that circulates in the IoT would fail to reach its full potential and, without the IoT, AI systems would be without rich data. Out of the data, brands will reinforce the lock-in effect through personalized services.

In my opinion, purchasing decisions consumers make today will lock them into entire ecosystems for years.

The race is very important because the millions of homes where voice control has gained a foothold for smart home adoption will be fertile ground for the wider adoption of a growing range of additional smart home devices, control systems, integrated applications, and vendors. Moreover, If companies do not get the market share as soon as possible, it will be harder for them to get it when the users have adopted other systems already.

Brands that have managed to secure a consequent customer base will soon pivot to deliver new offerings that can be integrated into existing smart homes thanks to AI.

This use of data to drive additional revenue can be seen with Amazon. Indeed, by Echo, Alexa, and initiatives such as Dash. Amazon managed to architect dynamic avenues into the devices that will surround and interact with us every day. Devices able to influence our spending habits and that will automate our household purchases. Purchases that will go directly through the marketplace of Amazon.

I predict that people will be highly reluctant to the idea of switching from one system to another one since that would cause starting over on the learning process. Furthermore, if companies cannot take advantage of the smart home part, they will lose the market share in the other parts of the technology device market.

Technology

To put it simply, conventional IoT devices integrate sensors that gather data. Built-in communications hardware relay this data either to nearby or cloud-based systems for analysis. Those systems may subsequently transmit instructions back to the IoT devices for further action.

By equipping those IoT devices with built-in intelligence, analysis, filtering, actionable outcomes, and even user interaction can all be handled from the device itself. This capability frees many solutions from the latencies and delays inherent in cloud communications, which can be particularly critical in applications where multi-source data must be acted on in real-time.

Put simply, the difference between a “connected” device and an AIoT device is that the latter can take over decisions and tasks for humans.

The issue that we have with current IoT devices is that general processors are too slow for AI functions. Moreover, many AI services are cloud-based, and the Internet can slow down… By building AI networks directly into devices, we could minimize that concern.

As we have seen, AIoT will boost smart devices capabilities. By leveraging AI, brands intend to propose better services and strengthen their lock-in effect on customers thanks to the data acquired through these devices.