Despite the various advancements in artificial intelligence (AI), the technology is still in its infancy and is not yet widely adopted by firms. However, while AI adoption across industry is low, new data from the National Science Foundation (NSF) shows that big companies are leading the way.
The NSF’s recently released Annual Business Survey (ABS), among other things, provides data about how companies across the United States are adopting AI. Primarily, the data shows that AI adoption in almost all U.S. industries is low. In manufacturing, where the advent of AI can transform how products are designed, fabricated, operated, and serviced, as well as the operations and processes of manufacturing supply chains, 89 percent of manufacturers report that they are not using AI at all. As figure 1 shows, in key manufacturing industries such as machinery, electronic products, and transportation equipment, fewer than 7 percent of companies report using AI as a production technology in any capacity. The same is true in nonmanufacturing industries such as finance and insurance, where AI could help detect fraud, identify financial risk, and predict cash flow events; healthcare, where AI could help predict health outcomes, forecast diseases, and analyze medical images; and professional services including legal, accounting, and advertising, where AI could help record, sort, and process swaths of data.
Figure 1: Percentage of companies using AI as a production technology for goods and services, by industry.
These low adoption numbers are likely because AI is one of a suite of emerging digital technologies transforming industries, and in many cases, successful applications of AI depend on businesses implementing the proper antecedents. For instance, in the manufacturing environment, production equipment needs to be IoT-sensor enabled in order to produce a real-time data stream and to create the datasets on which manufacturers can then run AI algorithms. As an ITIF survey in 2019 found, most manufacturers are currently focused on implementing more of the foundational digital technologies, before progressing to more sophisticated AI applications.
One of the most important technologies many companies will adopt before AI is cloud computing, a platform that makes it easier and cheaper for businesses to innovate with AI by operating and maintaining the IT infrastructure and services they need. Figure 2 shows the proportion of firms in selected industries using high levels of cloud computing is much greater than those using AI shown in figure 1. For instance, more than 5 percent of manufacturers of food, chemicals, plastics, machinery, and computer and electronic products report using high levels of cloud computing. Moreover, in non-manufacturing industries, higher levels of cloud computing correlate with higher levels of AI usage. For example, out of the six non-manufacturing industries highlighted in figures 1 and 2, professional, scientific, and technical services industries have the highest level of use of cloud computing and AI while retail trade and transportation have the lowest.
Figure 2: Percentage of companies with high use of cloud-based computing systems and applications as a production technology for goods and services, by industry.
While overall adoption of AI is low, NSF’s ABS data shows that larger companies are the leading AI adopters. As figure 3 shows, more than 25 percent of the largest companies are using AI tools to create high-quality goods and services whereas only 3 to 4 percent of small and medium-sized enterprises (SMEs) are.
Figure 3: Percentage of companies using AI as a production technology for goods and services by company size.
There are several reasons that may explain why larger companies outpace smaller ones in AI adoption. For one, because large firms tend to serve large markets, they can better amortize the high fixed costs associated with employing AI production technologies over more sales, making the unit costs of producing products with AI lower. For another, because a sizable share of the talent needed to harness AI is foreign-born, larger companies can better afford the time, fees, and personnel resources inherent in the U.S. visa process to attract AI workers. Larger firms also offer higher wages and more benefits, increasing the pool of top AI talent these firms have access to. Finally, because vendors of AI systems benefit from supplying companies with the largest consumer base, vendors may focus on creating relationships and contracts with larger firms, enabling these firms to be more exposed to the value AI systems can bring to their businesses.
Overall, while AI is still in a nascent phase, it is poised to add important new capabilities that make companies more effective and productive. Companies and countries should recognize that the stakes are high for them both as the use of AI and other digital technologies reshape the landscape of global competitiveness. To stay ahead, companies and countries will need to drive broader AI adoption for production workloads and encourage enterprise-wide impact.
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