According to a recent report from Glassdoor released on Jan. 25, the percentage of professionals utilizing ChatGPT or similar AI tools in the workplace has more than doubled within a year. Initially, when the tool debuted, 27% of professionals acknowledged using ChatGPT or similar AI tools. By January 2023, this figure surged to 43%, and currently, it stands at 62%, based on Glassdoor’s data. Reflecting on the rapid integration of ChatGPT into the professional sphere, the Glassdoor Economic Research team reminisced about its widespread adoption since its launch in November 2022.
A survey of 5,017 professionals conducted by Glassdoor posed a straightforward question: “Have you used ChatGPT, or other AI tools, to help you with tasks at work?” The responses revealed that marketing exhibited the highest adoption rate, with 77% of professionals admitting to using ChatGPT or AI tools, followed by 71% in consulting and 67% in advertising.
Conversely, industries like insurance, legal, and healthcare showed lower usage rates, with 33%, 38%, and 40% of professionals respectively admitting to using AI tools.
While slightly more men reported using AI tools compared to women, the majority of both groups acknowledged their utilization in the workplace. By generation, Generation Z led with 66% usage, followed by millennials at 63%, and Gen X at 57%.
Despite lingering apprehensions about AI, worker confidence in its capabilities appears to be growing. Respondents to a Robert Half survey expressed beliefs that AI tools can streamline tasks, enhance efficiency, and boost productivity, contingent upon clear guidelines and flexibility from leadership.
However, reports suggest that while AI tools are widely used, they haven’t yet led to significant productivity gains. Many employees require training to fully harness the benefits of generative AI in the workplace.
From an HR perspective, AI tools offer time-saving solutions for various tasks such as performance reviews, onboarding, and talent screening. HR teams can strategically define problem areas for AI integration and utilize trial-and-error approaches to automate tasks effectively.
