While the artificial intelligence chatbot only recently started garnering worldwide attention last November, 48% of companies using the technology note that it has supplanted workers, according to a February survey by ResumeBuilder.com of 1,000 U.S. business leaders. The survey also revealed that 49% of businesses are already using ChatGPT, with a quarter of respondents saying it has saved them more that $75,000. The vast majority of respondents (93%) who are now using ChatGPT also plan to expand their usage of it and 90% of business leaders note that recruits should focus on making ChatGPT a job skill they can list.

ChatGPT is expected to have an enormous impact in the HR and recruitment space. “In talent acquisition, the more mundane tasks like writing job descriptions, interview questions, and following up with candidates are already being replaced by ChatGPT,” says Stacie Haller, chief career advisor at Resume Builder. “Writing code is another area where this technology can provide output, while employees focus on more strategic initiatives.”

ChatGPT is an outgrowth from “large language models (LLMs)…a type of artificial intelligence (AI) system that's been trained on large amounts of text data,” Anthony Lancaster, chief robotics officer at Professional Robots, writes for Forbes.

“They can understand natural language and produce human-like responses to inputs. These models use advanced machine learning (ML) algorithms to understand and analyze the nuances of human speech, including syntax, semantics and context meanings,” Lancaster writes. “They are used in various applications, including chatbots, virtual assistants, language translation, content creation and scientific research."

Howard Ting, CEO of Cyberhaven, a data security firm based in Palo Alto, California, notes that ChatGPT captivates its users because the text it spits out “feels very human,” Society for Human Resource Management reports. But the actual technology that makes ChatGPT work “is actually quite simple.”

“It predicts which word will come next in a sentence based on the word order it saw across its training data, about 300 billion words worth of content from books, the Web and the interactions it has with people in its chat window,” Ting said. While ChatGPT is predicted by many to take over many work tasks done by humans now, the machine-generated content it produces will still need to be vetted by humans as “accuracy is a significant problem with the output of LLMs,” Patrick Thibodeau writes for Tech Target.

Still, large language models “can speed up many HR tasks, including writing emails, memos and even performance reviews; analyzing and translating dashboards into text; customizing training materials; and offering much-improved humanlike chatbots that provide onboarding and benefits information,” he notes. “HR vendors will work to figure out how LLMs can be married to internal HR processes and how they can use in-house and external data--because to work effectively, LLMs need access to a vast amount of data.”