Smart homes have always been advertised as being able to make life easier, but the reality was that homes that were supposed to be “smart” had homeowners struggling to find ways to control all of their devices and apps. Many people were met with frustrations when automating tasks daily; many of their smart devices rarely worked with other devices together, and they just seemed as though everything wasn’t functioning as intended. This would not be the case anymore!

By 2026, the situation is improving by leveraging advances in artificial intelligence; homes that are “smart” are now providing real value by learning homeowners’ routines, reducing energy use, improving security, and making decisions without needing assistive touch from the homeowner. Homeowners are experiencing this with AI-enabled features finally providing the “smartness” that the industry has been promising them for over a decade.

Smart Homes Are Moving Beyond Commands

In the past, smart homes required command inputs from users to accomplish tasks. For instance, users could say commands such as “Turn on living room lights” or “Set thermostat to 22°C”. With the advancement of artificial intelligence, smart home systems can now use prediction models as an alternative to commands when determining the actions needed to complete tasks.

A smart home system can use predictive behaviour models based on factors such as occupancy trends, device usage, environmental variables, and household routines to suggest the next expected action prior to your request to perform that action.

A homeowner who leaves for work each weekday at 8:15 AM does not have to have his/her timer programmed to do the entire schedule, as an AI knows the typical schedule and optimises all relevant smart home settings (lighting, heating, security and energy use). Research into Matter-enabled homes shows that AI systems can provide extremely accurate demand forecasts and adaptive energy optimisation as they continuously learn about the behaviour of occupants and the patterns of usage within the residence.

This is an indication of how smart homes have shifted from being remote-controlled to adaptable systems.

The Smartest Feature Isn’t Voice Control

Voice assistants were instrumental in the rise of smart homes but were not the ultimate goal. The ironic part, according to many who have a lot of experience using smart homes, is that voice control is now considered one of the least beneficial features.

In a Reddit thread about upgrading your smart home, many homeowners stated that the best automation for them is when no interaction is needed at all. Examples of this are automated pathways that light up at night; rooms that automatically turn off; and context-based notifications, which provide homeowners with a much greater feeling of satisfaction than using their voice to control them.

This change is happening industry-wide. Aided by large language models, voice assistants are transforming into conversational systems that understand your intent rather than just responding to specific commands. Users will no longer have to build complicated automation rules manually; they will be able to describe to the system what they want in simple language.

Google’s Home automation systems come in the form of Gemini-powered tools that let users use natural-language prompts to create sophisticated automation scenarios instead of programming using menus. This is a significant advancement over simply talking to your home; it’s teaching your home to comprehend what you’re trying to say.

For example, if you were to request something like, “Please prepare my home for movie night,” an AI system could complete multiple tasks, such as dimming lights, closing all of the blinds, changing the temperature, turning on the surround-sound system, and muting non-critical notifications without needing to give several different commands. This is how home automation will develop in the future.

Presence Detection Is Quietly Becoming a Killer Feature

Among the many exciting new things being developed for AI-enhanced homes are incredibly helpful yet simple applications. These applications can create presence awareness.

Most standard motion sensors provide information regarding whether motion has happened or not. However, when AI-enhanced presence systems combine radar and camera sensors, as well as environmental information and behavioural learning of an individual in a room, they can determine if someone is actually in that room. That is a significant distinction.

For instance, if a traditional motion sensor detects the presence of a person sitting quietly reading a book, the lights will turn off; however, an AI-enhanced presence system would recognise that the room is still being occupied.

The Reddit users frequently indicate their occupancy-based automations are among their first smart home implementations that provide a more convenient day-to-day living experience, such as the act of turning on air conditioning when a person is detected in bed or the use of arrival scene automations that will turn on the garage door, turn on outside lights, etc., without needing to manually perform those functions.

Today’s modern devices are being built to reflect this. For example, Amazon’s newest smart displays, like the Echo Show, are using radar perception, motion detection, temperature sensors, and AI analysis to automate based on context provided by actual behaviour exhibited in a household.

As a homeowner does not have to think about presence-based automation, the added value is much higher.

AI Is Finally Making Energy Savings Practical

The potential for energy management automation is possibly the biggest success story of the smart home. Traditionally, in order to take advantage of energy-efficient features, users had to actively monitor their energy use or set up complex schedules to optimise when they would run their appliances.

With AI, this is now changing.

Machine learning algorithms can predict how much energy will be needed at a home and detect wasteful use of energy, as well as create guidelines for when electricity is most likely to be used in a household and schedule devices accordingly.

Researchers studying an AI-powered home energy management system that uses the Matter protocol found that predictive algorithms were able to achieve a greater than 90% accuracy rate in forecasting energy use and optimally managing energy usage at the home.

The applications for AI energy management go beyond just smart thermostats.

AI can:

• Delay using appliances until electricity is at a cheap rate.

• Coordinate the charging of electric vehicles.

• Balance the solar generation and battery storage at the home.

• Change the heating and cooling of the home based on anticipated occupancy.

• To manage the use of energy based on utility pricing.

Further to this, the smart home industry is increasingly aligning its energy management protocols with electric utility infrastructure. Matter and OpenADR are working together to connect smart homes more directly to energy management systems and to directly connect smart homes to the electric grid.

For those people who are struggling with the rising cost of electricity in their homes, this may be more appealing than any voice assistant.

Computer Vision Is Replacing Basic Security Cameras

Conventional security cameras are constantly capturing video footage, whereas AI-based security cameras can analyse that data to understand what they’re seeing. This is dramatically changing the way we use security in our homes. Instead of receiving notifications every time a branch moves or a car goes by, these cameras now only notify homeowners for things like someone entering their home, a package being delivered, or any suspicious activity.

Most current computer vision systems summarise video events instead of just recording raw footage. These cameras can alert you if a package has just been left at your front door, if a person you know has just visited your house, and if there is any suspicious activity occurring.

Numerous studies using computer vision and language-processing models indicate that homeowners are primarily interested in “smart home” devices that will identify household events automatically, without constant human programming of each event.

For example, a homeowner could receive an alert that states, “A package was delivered at your front door”, instead of just “Motion detected”. This small change reduces the fatigue caused by constant notifications.

The Matter Standard Is Finally Solving the Smart Home’s Biggest Problem

The greatest complaint homeowners had regarding their smart home was not functionality but compatibility. A lightbulb would work on one platform, a lock would work on a different platform, and a thermostat would require yet another app to function properly.

Many homeowners were using 4 or more different apps from different manufacturers in order to operate all of their smart home devices. One Reddit user was very direct in describing their experience using multiple ecosystems to manage their smart home devices: “If you mix different ecosystems, it results in the need to have multiple apps, multiple hubs, and unreliable routines.” They learned a very simple lesson—choose one ecosystem and stick to it.

The emergence of matter is changing that equation.

With backing from leading technology companies, Matter is emerging as a worldwide communication protocol for smart devices to communicate with one another across networks. Recent iterations of this protocol are expanding to include support for a wider variety of device categories, including cameras, appliances, energy-management systems, electric vehicle chargers and many other device types.

AI derives significant value from interoperability. The more devices that can exchange data, the more contextual data AI systems will receive.

An intelligent thermostat, for example, becomes far more valuable when it can obtain data from motion sensors to identify occupancy, from air-quality monitoring devices to gather environmental data, and from security systems to predict when people will be home.

Matter provides a means to connect multiple devices that do not operate independently of one another.

Why Edge AI May Matter More Than Generative AI

Although generative AI usually receives most attention as the leading technological advancement, edge-based AI could arguably have a bigger impact within our smart homes. Edge-based AI allows information to be processed and analysed at the location of the edge device itself, instead of sending all information collected to the cloud for processing.

There are three key benefits to using edge-based AI within smart homes:

1. Reduced latency (speed of response).

2. Continued functionality of devices, even during internet disruptions.

3. Retention of sensitive household information within the household.

The importance of retaining sensitive information is becoming a greater consideration for homeowners using AI-powered smart home devices. As AI-powered devices gain access to cameras, microphones, occupancy data and behavioural tracking of occupants, privacy concerns have also increased.

Researchers studying AI-powered smart homes have warned that as AI capabilities expand, so does the extent of new forms of surveillance and data collection risks. However, in most cases, the homeowner is not aware of this.

Homeowners interested in AI-powered smart homes are increasingly favouring home automation systems that are more focused on local processing than the processing of data in the cloud.

When discussing AI-powered virtual assistants, homeowners frequently say that they prefer virtual assistants that function primarily on local computing rather than relying on the cloud because of their feedback on improving privacy and system reliability.

The smartest home will likely not be the one that has the most AI present; rather, it will be the home that retains the most intelligence within the home itself.

The industry still has a long way to go.

Smart homes powered by artificial intelligence continue to make improvements, but they’re still far from perfect. Some of the biggest complainers about smart homes are the people who use them. Many conversations about how AI-powered assistants can make our lives easier show that users are frustrated when they can’t get their AI assistants to perform even basic tasks like turning lights on/off, running routines, or managing devices in a consistent manner. Users also say that sometimes the newer AI assistants don’t seem as reliable as the older non-AI assistants.

This leads us to today’s reality: the consumer doesn’t care if his/her home sounds smart; what they want is for their home to work consistently.

How the future of smart homes gets shaped will not be from which assistant can have the most human-like conversation but from which smart home systems are able to work behind the scenes and eliminate the most amount of everyday friction.

Final Thoughts: Smart Homes Are Finally Growing Up

For years, smart homes were defined by connected gadgets and flashy demonstrations that often delivered limited real-world value. Today, artificial intelligence is changing that equation. Features such as predictive automation, presence detection, intelligent energy management, computer vision, and context-aware assistants are transforming smart homes from reactive systems into environments that actively adapt to the people living in them.

What makes this shift significant is that homeowners are beginning to notice the difference. Across online communities, users consistently praise automations that quietly solve everyday problems—whether it’s reducing energy bills, improving home security, automatically adjusting comfort settings, or eliminating the need to constantly interact with apps and devices. The most successful smart-home technologies are no longer the most futuristic; they are the ones that seamlessly fade into the background.

Looking ahead, advances in edge AI, natural language interfaces, and interoperability standards such as Matter will make smart homes even more intuitive and personalised. While challenges surrounding privacy, security, and reliability remain, the industry appears to be moving beyond novelty and toward genuine utility.

For consumers considering smart-home technology, the question is no longer whether a home can be made smarter. The more important question is how AI can make everyday living simpler, safer, and more efficient. After more than a decade of promises, smart homes are finally beginning to deliver on their original vision.

Frequently asked questions

How are smart homes improving with AI?

Smart homes are leveraging advances in artificial intelligence to learn homeowners' routines, reduce energy use, improve security, and make decisions autonomously.

What is the role of presence detection in smart homes?

Presence detection allows smart home systems to recognize if someone is actually in a room, enhancing automation and convenience.

How does AI contribute to energy management in smart homes?

AI can predict energy needs, detect wasteful energy use, and create guidelines for optimizing appliance usage based on electricity pricing.