Gartner: AI Is a Game Changer for Personal Devices

Gartner: AI Is a Game Changer for Personal Devices

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Emotion artificial intelligence (AI) systems are becoming so sophisticated that Gartner predicts that by 2022, personal devices will know more about an individual's emotional state than his or her own family. AI is generating multiple disruptive forces that are reshaping the way we interact with personal technologies.

"Emotion AI systems and affective computing are allowing everyday objects to detect, analyze, process and respond to people's emotional states and moods to provide better context and a more personalized experience," said Roberta Cozza, research director at Gartner. "To remain relevant, technology vendors must integrate AI into every aspect of their devices, or face marginalization."

The current wave of emotion AI systems is being driven by the proliferation of virtual personal assistants (VPAs) and other AI-based technology for conversational systems. As a second wave emerges, AI technology will add value to more and more customer experience scenarios, including educational software, video games, diagnostic software, athletic and health performance, and the autonomous car.

"Prototypes and commercial products already exist and adding emotional context by analyzing data points from facial expressions, voice intonation and behavioral patterns will significantly enhance the user experience," said Cozza. "Beyond smartphones and connected home devices, wearables and connected vehicles will collect, analyze and process users' emotional data via computer vision, audio or sensors capturing behavioral data to adapt or respond to a user's wants and needs."

Gartner also found that by 2021, 10 percent of wearables users will have changed lifestyles, and thereby extend their life spans by an average of six months. By 2020, 60 percent of personal technology device vendors will use third-party AI cloud services to enhance functionality and services. Through 2022, claims Gartner, security technology combining machine learning, biometrics and user behavior will reduce passwords to account for less than 10 percent of all digital authentications.

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