When IBM began to weave artificial intelligence (A.I.) and other technology platforms more deeply into its workplace processes, there was one big casualty: Human resource (HR) staffers. According to IBM CEO Ginny Rometty, an improved technology stack led to a 30 percent reduction in the headcount of its global human resources department. The positions that are left, she added, pay more and demand sophisticated skillsets. (Hat tip to CNBC for the link.) IBM has already bet heavily that its Watson artificial intelligence platform will allow it to stand out among rivals in the tech space. Now the company seems equally determined to use A.I. to streamline its workforce; for example, one internal app can predict (with 95 percent accuracy, supposedly) which employees are in imminent danger of leaving, allowing executives to dangle incentives to get them to stay. “You have to put A.I. through everything you do,” Rometty told the audience at CNBC’s @ Work Talent + HR Summit. But how did A.I. radically reduce IBM’s HR? The company reportedly relied on systems such as “My Career Advisor,” a portal with self-serve resources for career advancement. After the paradigm shift, a new, A.I.-powered platform provided employees with job recommendations based on inputs such as the employee’s skills and previous projects. And that’s just one example of how Big Blue tooled its systems in a “machine-first” way. IBM isn’t alone in these kinds of efforts. Recruiters and human-resources professionals have turned increasingly to tools that make certain inferences based on data, or automate processes previously left to humans. For example, recruiting-technology platforms such as Montage can automate scheduling and initial applicant screenings. And if companies beyond IBM begin leveraging algorithms to power HR portals—rather than relying on flesh-and-blood staffers—it’s not out of the question that the HR industry as a whole could suffer fairly radical attrition over the long term. Although automating parts of the recruitment and HR process might ease some tech pros’ longtime complaints about recruiting and HR (such as the near-constant rumors of candidate blacklisting), A.I. isn’t necessarily the cure for those core issues. Indeed, if companies such as IBM merely use A.I. to reduce costs associated with HR, it’s likely that new, aggravating problems will emerge—imagine the damage control after an algorithm decides to reject candidates based on gender or race. Indeed, given all the hype over A.I. and machine learning, it’s easy to forget these aren’t omnisciently wise systems; it’s “garbage in, garbage out,” and often the datasets fueling the process are quite “noisy.” A.I. and machine learning is also in a relatively nascent stage; remember, it’s sometimes hard to get an Alexa or Siri to do something as simple as order up the right song or tell you today’s weather—and HR processes are generally far more sophisticated, with a tricky human element. A.I. won’t eliminate HR staff and recruiters completely, but companies will look to the technology to cut overhead and pare down staffers. The big question is whether that will result in poorer service for tech pros looking for jobs or trying to advance their careers.