By Insight Editor / 3 Jan 2024 / Topics: Generative AI Customer experience Modern workplace
The survey results show a large interest in generative AI and how it can help teams manage day-to-day work and deliver better outcomes.
“It’s remarkable that most IT budgets did not even anticipate generative AI a year and a half ago,” said David McCurdy, chief enterprise architect and chief technology officer at Insight. “Just about every business leader is fixated on how this technology can reinvent their operations and create new business models. That said, there’s a certain ‘finesse’ that many employees still need to acquire in order to effectively leverage generative AI in their work. As we shift gears into the next phase of adoption, advanced training will be crucial to success.”
Explore the survey results below:
Most organizations have deployed generative AI and are relying on their workforce to devise practical uses to improve the business.
Business leaders are finding ample reasons to use gen AI to help manage their day-to-day work.
Companies report several benefits they are trying to achieve from generative AI initiatives, most notably improvements in productivity and customer engagement.
Relative to the many ways organizations are now using generative AI, business leaders express less concern about barriers to implement the technology.
A majority of leaders from across the business have been tasked with helping their company define the return on investment of implementing generative AI.
The research was conducted online in the United States by The Harris Poll on behalf of Insight Enterprises among 601 U.S. adults ages 25+ who are employed full time as a director or higher at a company with 1,000+ employees. The survey was conducted from Oct. 17-27, 2023.
Data are weighted where necessary by number of employees to bring them into line with their actual proportions in the population.
Respondents for this survey were selected from among those who have agreed to participate in our surveys. The sampling precision of Harris online polls is measured by using a Bayesian credible interval. For this study, the sample data is accurate to within ±4.06 percentage points using a 95% confidence level. This credible interval will be wider among subsets of the surveyed population of interest.
All sample surveys and polls, whether or not they use probability sampling, are subject to other multiple sources of error which are most often not possible to quantify or estimate, including, but not limited to coverage error, error associated with nonresponse, error associated with question wording and response options, and post-survey weighting and adjustments.
