by Chris Paggioli | 05/26/2021
Google recently held its I/O event to unveil updates, partnerships, and new features for several different products. Across these announcements there are a few that standout as having practical applications within enterprise environments either at present or in the future: the company is updating the Android OS with better password protection and auto-deletion of activity after 18 months to protect user data; Google has also begun to build a closer partnership with Samsung, the biggest maker of Android phones. Additionally, Google discussed upgrades to its AI that don’t seem to have much currently targeted enterprise use, but that can be leveraged in the future to enhance operational efficiencies. The most eye-catching pieces of news to come out of this event were related to Google’s LaMDA (Language Model for Dialogue Applications) AI.
Google’s Android OS updates leverage end users’ preferences to create a customized look and feel to all of a given user’s applications. There are now over 3 billion Android devices active across the globe, and organizations increasingly shift to Android devices for workforce computing needs. In VDC Research’s recent Buyer Behavior Guide survey, 45.3% of enterprise respondents chose ‘ease of use’ as a primary selection criterion for the frontline mobile devices purchased by their organizations – with an optimized OS that facilitates an improved, smoother and more customizable UI, Google’s latest updates will prove beneficial to employee productivity and reduced training costs/time and also make Android devices even more appealing from an enterprise perspective.
Samsung and Google will begin to work closer to better combine Google’s Wear OS and Samsung’s Tizen wearable device platform. With Samsung being the biggest producer of Android phones, a greater coordination across each team’s engineers and goals will result in a better product. VDC Research found that the overall enterprise wearables market is expected to grow at a CAGR of 8.6% from 2020 to 2025 – as these two mobile computing powerhouses come together to create a better wearable device experience, each company will be able to more effectively compete for market share in this growing segment. The partnership will also likely mean better products for enterprise use and result in improved frontline productivity and streamlined workflows.
Google’s LaMDA uses AI to have conversations with users. It is an example of AI becoming increasingly “humanlike” to ensure more natural conversations. This AI can even pretend to be ‘things’ – for example, a user can ask the AI “what is it like to be a paper airplane?” and the AI will answer as if it were a paper airplane. The AI can use information from Google Search to enhance conversations. While this does not have any practical or test-driven applications for enterprise use currently, it is an impressive demonstration of advancing AI capabilities. As AI-driven interactions become more natural and easy to use, the technology will increasingly be leveraged by and benefit organizations in the near future. The enhanced fluency of AI-human interactions displayed by Google’s latest updates may help reduce employee training times with new technology tools; for example, for enterprises that use smart glasses and voice-directed applications, a more humanlike and intuitive AI experience will be hugely beneficial to the introduction of these technologies into their employees’ hands and frontline workflows.
Ultimately, the Google I/O event had some interesting developments. While these developments might not currently have any game-changing applications within enterprise environments, they do help reveal the current state of several advanced technologies. Upgrades to wearable devices and their operating systems and user interfaces are also always necessary, especially as the category’s enterprise footprint quickly expands. Looking ahead, Android devices will be better equipped to leverage Google’s advances in AI to have nuanced conversations with end users; these devices will then be better equipped to pull from internal data to improve and assist with a number of workflows such as giving instructions to workers conducting field maintenance or repairing machinery.
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