Artificial intelligence (AI) has the potential to become the operating system of a consumer’s life (not to mention the comms industry), running quietly in the background and helping to make a user’s life more convenient, personalized and enriched—but according to new research, AI fragmentation causes inconsistent user experiences. The problem is that not all features and functions are the same across all AI devices and platforms, and not all AI devices and platforms have the ability to “speak” to each other.
This is the key takeaway from a recent study by the User Experience Strategies (UXS) service at Strategy Analytics, UXS Technology Planning Report: Artificial Intelligence, which investigates the needs, behaviors and expectations of future AI consumers. To ensure seamless integration, all systems within one ecosystem must be able to communicate with each other, regardless of brand.
“Fragmentation results in users having to devote extensive time to manage different devices and profiles,” said Christopher Dodge, associate director and report author, in a news release. “Consumers are frustrated by trying to remember which tasks a phone assistant can do versus an in-home assistant, versus voice recognition capabilities in a car; and all require different command language.”
Key findings of the research include:
- Command language and scope of supported features differs widely across AI platforms. If one of the most compelling features of AI is to minimize user input, learning the differing abilities and command languages of many AI devices is at the very least time consuming, and mostly inefficient.
- If left to choose which app, service or device the user thinks is most appropriate to complete a task, AI is not being used in the most effective way or to its full potential.
- Based on a request, a system must be able to distinguish which source will best complete the task; and this means that all devices within an ecosystem must be able to talk to each other.
“Consumers want the same level of intelligence to be imbedded in all the devices they are using. This way, AI could function much faster; and if the internet is down or slows, usage is not impacted,” added Chris Schreiner, director of syndicated research for UXIP, in the release.
