Center for Global Business Survey of U.S. Business Executives Assesses AI Impact and Regulation Sentiments

As robust as artificial intelligence (AI) capabilities have become, it is still very much in its infancy. With governments formulating strategies for AI regulations, the onus is on U.S. businesses to successfully adapt to AI policies on the fly.

To better understand those implications, sentiments toward regulation and the overall impact of AI on business, the Center for Global Business at the University of Maryland’s Robert H. Smith School of Business surveyed 885 U.S. business executives and middle managers from for-profit companies. The findings were published in a report titled “AI Use and Regulation: A Survey of U.S. Business Executives,” which is part of the center’s AI Governance Project.

Survey respondents span eight key sectors, specifically financial services and insurance, healthcare and biotechnology, hospitality and leisure, information technology, manufacturing, retail trade, telecommunications and transportation, which comprise roughly half of the U.S. private sector workforce. A ninth category, “Other,” was included to represent individuals who did not fall in the eight main sectors. These sectors were chosen primarily based on the ability to provide diverse responses and viewpoints about how AI is being implemented across industries, says Kislaya Prasad, a Smith School research professor and Academic Director of the Center for Global Business.

“There is great similarity in patterns of use of AI across sectors, although levels vary widely. Information technology, telecommunications, financial services and insurance, and manufacturing have much higher levels of AI use than, say, retail and e-commerce. However, AI is being used in similar ways everywhere. Moreover, sentiments towards AI and its regulation are similar across sectors,” says Prasad, who designed the survey and authored the report. “It is my hope that the survey results provide useful information for the public debate surrounding AI regulation.”

For AI adoption among companies, almost 58% of respondents reported that their firms had incorporated AI into their business practices in some capacity, 35% reported in the negative, while the remaining 7% stated they were unsure about the level of AI integration at their company.

Further topics addressed in the report include job displacement, the level of support for AI regulation and export restrictions, sentiments on the patentability of AI-assisted creations and intellectual property infringement, AI use by sector, and the drivers and hurdles associated with AI adoption.

Here are five key takeaways from survey responses:

Job displacement concerns weigh heavily on executives. Regarding the potential adverse impact of AI on career prospects, roughly 20% of respondents expressed that they were either very or extremely concerned about the issue over the next five years. These worries resonated with 47% of participants from the financial services and insurance sector, and telecommunications with 32%. Additionally, 27.5% of respondents with less than 15 years of work experience and 26% of those considered AI decision-makers at their respective companies share this concern. Although there is discernable concern among people directly involved with AI in their work, “it’s not clear if this stems from more intimate knowledge of AI’s possibilities or from being in more vulnerable roles,” writes Prasad.

A strong backing for AI regulations exists. The Biden Administration’s 2023 Executive Order on AI aimed to establish new standards for AI safety and security, create privacy safeguards and promote innovation and competition in business. Over the past five years, 17 states have enacted 29 bills on AI regulation promoting similar principles. As for the extent of support among executives for regulation of AI-based systems, respondents were asked about three types of mandates—transparency about AI use and data collection, explainability of autonomous decisions by AI algorithms and third-party auditing for the presence of algorithmic bias in AI algorithms. Approximately 75% of responses declared to strongly or somewhat support regulation mandating transparency, with algorithmic bias regulation held in a similar regard. About 72% of respondents strongly supported explainability regulations.

Resounding support for restrictions on exporting key AI technologies. In addition to the 2023 Executive Order on AI, the U.S. Department of Commerce strengthened export controls on AI technology, targeting the sales of advanced chips and chipmaking equipment to China. According to Secretary Gina Raimondo, the goal was to limit China’s “access to advanced semiconductors that could fuel breakthroughs in artificial intelligence.” Support for those policies was apparent among survey respondents, with almost 60% strongly or somewhat supporting restrictions. Firms with 10% or greater international sales supported AI technology export restrictions more significantly. Manufacturing led all sectors by a sizeable margin, with 70% of its respondents strongly or somewhat supporting restrictions on exports of cutting-edge AI technology. Older respondents, people concerned about AI-related job displacement and those with high trust in the government are more likely to support export restrictions, too.

Generative AI has the early lead in AI adoption within business. When asked about the AI technologies implemented by their companies, 39% shared that generative AI, followed by computer vision (30%) and machine learning (27%), were in use. Firms with a significant global presence proved to be the most intensive users of AI for generative tasks. Among respondents from these firms, 33% said they used generative AI for chatbots, while 32% used it for marketing purposes and 30% for text generation. Regarding the decision-making tasks that currently use an autonomous decision system, respondents regularly cited inventory management, logistics, personalization and recruiting.

Customer experience and operations efficiency improvements are at the core of AI adoption. Drivers and hurdles, overall, were similar across sectors. However, at companies where AI is in use, those two drivers appeared among 66% and 72% of responses, respectively. Hurdles selected by more than 35% of firms with adopted AI technologies included high initial costs, difficulty recruiting skilled professionals and the challenge of integrating AI with existing IT infrastructure. As for companies with no level of AI technology adoption, the two most commonly cited reasons were the absence of a clear use case or perceived need for the technology and limited technical expertise or resources to implement and manage the technology.

Funding from the U.S. Department of Education through a Title VI grant under the CIBE program contributed to this research. 

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