AI is one of the hottest new technologies in mobile. Evaluate the AI market and determine how your organization can take advantage of the latest advances in mobile tech.
Self-aware technologies aren't reserved for science fiction movies anymore; they're real and coming soon to your mobile device.
In the past, mobile assistants such as Apple's Siri, Google Assistant and Samsung's Bixby used voice interactions to retrieve data from the web and ease navigation. The next generation of mobile assistants, however, will focus on learning about end users and adapting the device and its apps to the users' specific needs. AI for mobile will become more like a concierge that knows what end users need and want rather than just a list of search possibilities.
The advent of artificial intelligence (AI) promises to make mobile devices easier to use. This adaptation can increase personal productivity and overall corporate productivity and decrease user frustration when navigating multiple functions or apps. As the next phase of mobile computing delves into the world of AI for mobile, determine how to adjust your organization's strategy.
The road to AI for mobile
This transition will not be quick or easy, however. Many phones today have some rudimentary AI hardware, but for compute- and memory-intensive AI powered by machine learning (ML), back-end services will need to run in the cloud.
AI for mobile will become more like a concierge that knows what end users need and want rather than just a list of search possibilities.
Also, the algorithms that will be incorporated into the devices to run on AI subprocessors still need work, particularly if they are to enable the extension of existing programs and processes, such as ERP systems or personal productivity apps.
Many hope to move ML to the device itself, but I expect that it will be impractical to acquire the necessary resources to accomplish that other than for very simple processes. Instead, organizations should partner with a cloud service, particularly over a fast and low latency network, such as 5G.
It will be easier for companies that use SaaS applications to deploy smart apps than organizations that exclusively use on-premises apps that need to identify and deploy the proper APIs to the new ML services.
The benefits of AI for mobile
AI should improve security for mobile devices. Truly smart mobile devices will know the appropriate use of data and will understand whether the user is the designated user/owner of the device or just one that happened to gain access to it. These security capabilities extend beyond biometric authentication and focus on knowledge about the end user and an ability to detect errant behavior. This should nearly eliminate the significant security threats posed by current mobile devices and users and supplement current enterprise mobility management suites or other management products.
AI will also provide mixed reality capabilities that can enhance user interactions. For some applications, these features will create a completely new experience.
Mixed reality should provide detailed and useful data to the user -- otherwise, it's a wasted opportunity. Truly assisted intelligence will enable mixed reality with the device -- often without the need to wear a cumbersome headset -- to improve many systems in retail, manufacturing, healthcare, financial services and transportation.
Employees with a relationship with their vendors' representatives should ask which functions will be available as extensions of the hardware -- the smartphone -- and the software -- the running apps.
Further, IT teams should closely follow all of the capabilities that the major cloud vendors, such as Google, Microsoft and Amazon, announce. These should become available as standard extensions to existing and future SaaS offerings.
Finally, companies that deploy on-premises applications should evaluate which new features/upgrades will become available as part of their ongoing maintenance agreements with their software providers.
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