Robots aren’t taking over the media (yet) but Artificial Intelligence and automation are lending a helping hand.

The challenges of running a profitable media company have resulted in a “streamlining” of these organizations, often requiring staff reductions that create holes in coverage, particularly in areas that require domain expertise or a nuanced interpretation. What if there was a way to free up the increasingly valuable reporters from some of their tedious or time-consuming tasks to focus on telling complex stories or digging into subjects deeply? Enter Artificial Intelligence (AI) for journalism. An increasing number of media companies are employing robot journalists—or, more accurately, artificially intelligent algorithms adept at analyzing data and writing serviceable prose – to do just that. (Fusion’s Kevin Roose does a terrific job explaining how it works.)

Here are some of the ways AI is making its mark on journalism:

The Associated Press, working with Automated Insights and Zacks Investment Research, automatically generates almost 4,000 stories about U.S. corporate earnings each quarter—about twelve times what AP reporters and editors previously created. For a small fraction of these stories, editors add “the human touch” to provide more nuanced interpretations.

More recently, the AP added sports reporting to its automated journalistic endeavors. The move allowed the company to expand its coverage of Minor League Baseball (and could offer similar possibilities for other sports coverage). AP baseball editors and reporters worked with Automated Insights to configure the Wordsmith platform to ensure that it would follow AP standards for baseball coverage.

The Washington Post is also taking a crack at automated journalism, developing its own proprietary artificial intelligence tool, “Heliograf,” which automatically generates brief, multi-sentence updates. The Washington Post will roll it out to report key information from the 2016 Rio Olympics, including results of medal events. Heliograf, which will continue to be developed by Post engineers to enhance storytelling for large-scale projects, will also be leveraged for data-driven coverage of major news events, including the U.S. election. This technology can process a combination of different data sources, such as crime and real estate numbers, customize stories depending on individual user actions, and help look for anomalies in data to alert journalists to a potential story—all of which The Washington Post plans to leverage as it further develops Heliograf’s utility.

Algorithmic journalism is not limited to sports and finance, however. One of the longest-running robo-journalists in the game is Quakebot, which was written by Los Angeles Times Writer Ken Scwenkie. According to Business Insider, Quakebot is an automated system that resides on the Los Angeles Times’s servers, which receives emails from the US Geological Survey, runs that data through an information checklist, and then determines if it’s newsworthy based on the magnitude. It then parses out content from the email and inputs it into the Los Angeles Times’s content management system. Posts are structured using a formula based on previous posts.

It is interesting to note the LA Times also uses its own brand of automated journalism for The Homicide Report, which tracks every homicide victim in LA County. This sort of approach (visualized data journalism) is particularly suited to the algorithmic approach in that analyzing huge (and possibly constantly growing or changing) data sets is a massive undertaking. With solid structure and oversight, these can be reliably created, updated and presented in a dynamic visual way by leveraging AI.

The momentum for automated journalism has been building for years now and is definitely picking up steam. The New York Times reports that Tronc, Hearst, Bonnier, Gannett and the Weather Channel use automation to do everything from streamlining video production to analyzing and summarizing text and finding photographs and video clips to go with it. And, in an April memo to Bloomberg’s staff, Editor-in-Chief John Micklethwait announced that the news organization is creating a 10-person team to determine how automation can be used throughout the company’s portfolio of editorial products.

As Dr. Andreas Graefe, author of the Tow Center for Journalism report “Guide to Automated Journalism” noted, automated journalism is particularly useful in generating routine news stories for repetitive topics for which clean, accurate, and structured data are available. He also outlines the potential for algorithms to generate large volumes of news quickly, potentially in multiple angles and personalized for reader preference.

But, as the report points out, there are limitations to automation that must be carefully considered as more organizations use artificial intelligence to augment their journalism. Given many of the current implementations reliance on data, the quality of that data is paramount. And, as Micklethwait points out in his memo, “one irony of automation is that it is only as good as humans make it.” That, of course, extends to the media organizations that deploy algorithmic approaches, which must balance efficiency, transparency, and the consumer demands of more information, faster—but who also love a good read.