Artificial intelligence (AI)
features will become a critical product differentiator for smartphone
vendors that will help them to acquire new customers while
retaining current users, according to Gartner, Inc. As the smartphone market
shifts from selling technology products to delivering compelling and
personalized experiences, AI solutions running on the smartphone will become an
essential part of vendor roadmaps over the next two years.
Gartner predicts that
by 2022, 80 percent of smartphones shipped will have on-device AI capabilities,
up from 10 percent in 2017. On-device AI is currently limited to premium
devices and provides better data protection and power management than full
cloud-based AI, since data is processed and stored locally.
"With smartphones
increasingly becoming a commodity device, vendors are looking for ways to
differentiate their products," said CK Lu, research director at Gartner.
"Future AI capabilities will allow smartphones to learn, plan and solve
problems for users. This isn't just about making the smartphone smarter, but
augmenting people by reducing their cognitive load. However, AI capabilities on
smartphones are still in very early stages."
10 Uses for AI-Powered
Smartphones
“Over the next two
years, most use cases will still exploit a single AI capability and
technology,” said Roberta Cozza, research director at Gartner.
“Going forward, smartphones will combine two or more AI capabilities and
technologies to provide more advanced user experiences.”
Gartner has identified
10 high-impact uses for AI-powered smartphones to enable vendors to provide
more value to their customers.
1) "Digital Me" Sitting on the
Device
Smartphones will be an
extension of the user, capable of recognizing them and predicting their next
move. They will understand who you are, what you want, when you want it, how
you want it done and execute tasks upon your authority.
“Your smartphone will
track you throughout the day to learn, plan and solve problems for you,” said Angie Wang, principle research analyst at
Gartner. “It will leverage its sensors, cameras and data to accomplish these
tasks automatically. For example, in the connected home, it could order a vacuum bot to
clean when the house is empty, or turn a rice cooker on 20 minutes before you
arrive.”
2) User Authentication
Password-based, simple
authentication is becoming too complex and less effective, resulting in weak
security, poor user experience, and a high cost of ownership. Security
technology combined with machine learning, biometrics and user behavior will improve
usability and self-service capabilities. For example, smartphones can capture
and learn a user's behavior, such as patterns when they walk, swipe, apply
pressure to the phone, scroll and type, without the need for passwords or
active authentications.
3) Emotion Recognition
Emotion sensing
systems and affective computing allow smartphones to
detect, analyze, process and respond to people's emotional states and moods.
The proliferation of virtual personal assistants and
other AI-based technology for conversational systems is
driving the need to add emotional intelligence for better context and an
enhanced service experience. Car manufacturers, for example, can use a
smartphone's front camera to understand a driver's physical condition or gauge
fatigue levels to increase safety.
4) Natural-Language Understanding
Continuous training and deep learning on smartphones will
improve the accuracy of speech recognition, while better understanding the
user's specific intentions. For instance, when a user says "the weather is
cold," depending on the context, his or her real intention could be
"please order a jacket online" or "please turn up the
heat." As an example, natural-language
understanding could be used as a near
real-time voice translator on smartphones when traveling abroad.
5) Augmented Reality (AR) and AI Vision
With the release of
iOS 11, Apple included an ARKit feature that provides new tools to developers
to make adding AR to apps easier. Similarly, Google
announced its ARCore AR developer tool for Android and plans to enable AR on
about 100 million Android devices by the end of next year. Google expects
almost every new Android phone will be AR-ready out of the box next year. One
example of how AR can be used is
in apps that help to collect user data and detect illnesses such as skin cancer
or pancreatic cancer.
6) Device Management
Machine learning will improve device
performance and standby time. For example, with many sensors, smartphones can
better understand and learn user's behavior, such as when to use which app. The
smartphone will be able to keep frequently used apps running in the background
for quick re-launch, or to shut down unused apps to save memory and battery.
7) Personal Profiling
Smartphones are able
to collect data for behavioral and personal profiling. Users can receive
protection and assistance dynamically, depending on the activity that is being
carried out and the environments they are in (e.g., home, vehicle, office, or
leisure activities). Service providers such as insurance companies can now focus
on users, rather than the assets. For example, they will be able to adjust the
car insurance rate based on driving behavior.
8) Content Censorship/Detection
Restricted content can
be automatically detected. Objectionable images, videos or text can be flagged
and various notification alarms can be enabled. Computer recognition software
can detect any content that violates any laws or policies. For example, taking
photos in high security facilities or storing highly classified data on
company-paid smartphones will notify IT.
9) Personal Photographing
Personal photographing
includes smartphones that are able to automatically produce beautified photos
based on a user's individual aesthetic preferences. For example, there are
different aesthetic preferences between the East and West — most Chinese people
prefer a pale complexion, whereas consumers in the West tend to prefer tan skin
tones.
10) Audio Analytic
The smartphone's
microphone is able to continuously listen to real-world sounds. AI capability
on device is able to tell those sounds, and instruct users or trigger events.
For example, a smartphone hears a user snoring, then triggers the user's
wristband to encourage a change in sleeping positions.
