Companies are going beyond the hypotheticals to understand the real use cases for generative AI
A survey conducted by The Harris Poll on behalf of Insight Enterprises , a Fortune 500 Solutions Integrator focused on driving client success through digital transformation, finds that within the next three years, most business leaders expect to adopt generative AI to make employees more productive (72%) and enhance customer service (66%). Around half of the respondents for Insight’s generative AI report, released today, say they expect to use the technology to assist with research and development (53%) and/or software development/ testing (50%).
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“History tells us if you give people the right tools, they become more productive and discover new ways to work to their benefit. Embracing this technology gives employees an unprecedented opportunity to evolve and elevate how they work and, for some, even discover new career paths.”
“Generative AI has opened up amazing new possibilities to build companies, to grow companies, and to make companies more efficient and profitable,” said Matt Jackson, Insight global chief technology officer. “The pace of exploration and adoption of this technology is unprecedented. People are sitting in meeting rooms or virtual rooms discussing how generative AI can help them achieve near-term business goals while trying to stave off being disrupted by somebody else who is a faster, more efficient adopter.”
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The survey was designed to garner insights on how director level or above professionals at companies with 1,000+ employees are thinking about and exploring generative AI technologies.
Key findings from the survey reveal that:
- 81% say their company already has established or implemented policies/strategies around generative AI or are currently in the process of doing so.
- 90% of professionals believe specific roles will be impacted by the adoption of generative AI, including:
- Data analyst/data scientist (44%) tops the list of these roles.
- This is followed by software developer (37%), software tester (37%), financial operations (32%) and communications (30%) roles.
- About half of the respondents expressed concerns about the implementation of generative AI technologies at their organization, with quality and control (51%) and safety and security risks (49%) topping the list.
- More than 1 in 3 cite concerns that it will limit human innovation (39%), cost of implementation/budgetary constraints (38%), and legal and regulatory compliance (35%).
- Another 38% have concerns about human error due to a lack of understanding of how to use the tool or accidental breaches of their organization’s data.
- Slightly more than 1 in 4 professionals (26%) say one of their concerns about the implementation of generative AI technologies is workforce displacement.
“Some of the most pressing questions involve generative AI’s impact on employees. We are asking ourselves: How do we collaborate with it? How will it change our jobs? Will it replace us? These questions are valid, but the power of generative AI is its ability to augment, not replace, human intelligence,” said Jackson. “History tells us if you give people the right tools, they become more productive and discover new ways to work to their benefit. Embracing this technology gives employees an unprecedented opportunity to evolve and elevate how they work and, for some, even discover new career paths.”
Survey Methodology
The research was conducted online in the United States by The Harris Poll on behalf of Insight Enterprises among 405 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 April 26 to May 3, 2023. Data are weighted where necessary by number of businesses to bring them into line with their actual proportions in the population.
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 ±5.0 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 that 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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