While composing an email, you see autocomplete suggestions that match your writing style. When you insert an image into a presentation, the software makes cropping and layout suggestions. If you forget to respond to an important message, it reappears at the top of your inbox with a reminder.
Google’s G Suite, Microsoft Office and other productivity suites are increasingly adding machine learning and artificial intelligence features to automate and personalize repetitive tasks, like replying to email or scheduling meetings. More broadly, AI-fueled office software can help users collaborate on projects across different platforms and glean insights for making better business decisions.
The adoption of AI into office suites is part of a larger trend that’s expected to drive significant productivity gains in the near future, according to a 2017 study from PwC. “According to our analysis, global GDP will be up to 14% higher in 2030 as a result of the accelerating development and take-up of AI — the equivalent of an additional $15.7 trillion,” the report found.
As more AI-enhanced products appear, the research suggests, consumer demand for the technology will grow as people begin to depend on automation and personalization. Naturally, office suite makers like Microsoft, Google and others are inserting AI and machine learning capabilities into their products in an effort to be part of these overall gains.
But are these additions actually useful? “When you first start using it, the AI has little data to use to know what your preferences are,” says Jeffrey Mann, a research vice president at Gartner. “If there’s a small set of data to analyze, the recommendations won’t be very good.” Over time, though, the data set grows and recommendations improve, Mann says, and “we get used to it and feel lost when they’re not there. Like when my car automatically locks when I walk away from it. I’m lost in a rental car that doesn’t do that now.”
Meanwhile, some industry watchers wonder if AI-driven features will come with unexpected costs, as with previous technologies that traded privacy and security for expediency. Saving your personal data in the cloud is convenient, for example, but also exposes your email, photos and financial identity to anyone who can figure out your username and password. Analysts and technology execs say AI’s convenience needs to be paired with data security, as we’re just scratching the surface of what AI can do in everyday business software.