A survey conducted by Insight Enterprises (NASDAQ:NSIT) in partnership with The Harris Poll found that two-thirds (66%) of business leaders say their company has deployed private, secure generative AI tools to the workforce, and a similar number (65%) say their department has been tasked to identify use cases for their organization.
Companies report several benefits they are trying to achieve from generative AI initiatives. More than half (54%) report improved productivity as a top outcome expected from the technology; around two in five cite improved customer experience (42%), improved customer service (40%), and/or reduced human error (37%). That said, employee knowledge or training on generative AI tools remains a top barrier to implementation (32%), indicating that more education and training is required.
Insight’s latest research, a follow-on to its June 2023 report Beyond Hypotheticals: Understanding the Real Possibilities of Generative AI, is designed to garner the latest insights on how 600 director level or above professionals at companies with 1,000+ employees are exploring generative AI technologies.
“It’s remarkable that most IT budgets did not even anticipate generative AI a year and a half ago. But now, as we enter 2024, just about every business leader is fixated on how this technology can reinvent their operations and create new business models,” said David McCurdy, chief enterprise architect and chief technology officer at Insight. “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.”
Further findings from the research:
- Generative AI is used frequently in day-to-day work, with more than three in five using the tools for data analysis and visualization (74%); task collaboration, such as using as a copilot for research or email summarization (66%); generating written content like reports or presentations (63%); and to help with personalized learning (62%).
- Deeper applications to improve the business also are being readily explored, with 59% reporting using generative AI for product design and development; 52% for software development.
- A majority of leaders from across the business have been tasked with helping their company define the return on investment of implementing generative AI, particularly delineating how to improve customer satisfaction (65%), enhance service availability (60%), reduce operational costs (57%) and augment staff to improve productivity (56%).
- Security concerns remain top of mind for business leaders when it comes to generative AI, with 38% citing security as a top barrier.
- However, only 15% consider costs of implementation — including technical debt due to outdated technical infrastructure, initial financial investment and ongoing maintenance costs — as hurdles for their organization.
“There’s a lot of exuberance in the market,” said Carm Taglienti, chief data officer of Insight’s solutions business. “We have seen companies move quickly to try to capitalize on this technology. However, as exciting as these developments are, adoption is happening at a mostly surface level. It’s being viewed through rose-colored glasses without enough attention being paid to data readiness or continuous training and upskilling at all levels of the organizations.”
To learn how to realize the full value of generative AI at your organization, visit insight.com/generativeAI. For more information on Insight, visit insight.com or call 800-INSIGHT.
Survey Methodology
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.
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