AI Implementation in the U.S. Lags, With Major Corporations Pioneering the Field
In the rapidly evolving global landscape, the adoption of Artificial Intelligence (AI) is a key factor for companies and countries aiming to stay ahead. Approximately one-third of organizations in the U.S. are currently using AI, with many more considering its adoption in the near future [1].
The technology industry and large enterprises are leading the charge, leveraging AI for advanced tasks beyond routine automation [1][4]. For instance, the technology sector is at the forefront of AI adoption, but this integration comes with a potential downside—AI-driven workforce reductions, indicating a high degree of AI transformation [3].
On the other hand, industries like retail and consumer goods are progressing beyond basic AI use into more sophisticated applications [1]. Marketing departments, in particular, are using AI for content creation and customer analytics, although adoption can be slower in other business units [2].
Size matters when it comes to AI adoption. Large companies are more likely to have advanced AI deployment, with better integration across departments and scalability of AI projects [1][4]. These companies benefit from more resources, dedicated AI talent, and strategic leadership involvement, which aids broader adoption [1][4]. In contrast, small companies face steeper challenges due to limited budgets, fewer trained personnel, and sometimes less managerial impetus to adopt AI fully [2].
Factors contributing to these differences include resource availability, talent and training, leadership involvement, integration scope, and policy and regulatory environment [2][4][5]. For example, larger enterprises have greater financial and technical resources to implement, scale, and sustain AI initiatives [1][4]. Bigger firms can also invest in AI-skilled employees, training programs, and generational adaptation strategies, while smaller businesses often rely on more limited training and staff familiarity [2][5].
As AI adoption continues to grow, projected to expand at about a 36% Compound Annual Growth Rate (CAGR) through 2030, scalability and full business value capture remain significant hurdles, particularly for smaller companies and less tech-intensive industries [1][4]. In manufacturing, for instance, 89% of manufacturers report not using AI at all [1].
Cloud computing is one of the most important technologies many companies will adopt before AI. More than 5% of manufacturers of food, chemicals, plastics, machinery, and computer and electronic products report using high levels of cloud computing [1]. AI is poised to add important new capabilities that make companies more effective and productive.
The National Science Foundation's Annual Business Survey provides data about AI adoption across U.S. industries [1]. AI adoption is low across almost all U.S. industries, including manufacturing, finance, insurance, healthcare, and professional services. Vendors of AI systems 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 [1].
The use of AI and other digital technologies is reshaping the landscape of global competitiveness. Companies and countries should encourage broader AI adoption for production workloads and enterprise-wide impact to stay ahead in this rapidly changing global landscape [1].
- The technology sector, leading the AI adoption, is utilizing AI for advanced tasks, but its integration may result in AI-driven workforce reductions, signifying a high degree of AI transformation.
- Marketing departments within retail and consumer goods industries are using AI for content creation and customer analytics, although adoption may be slower in other business units.
- Large companies are benefiting from more resources, dedicated AI talent, and strategic leadership involvement, which aids broader AI adoption compared to smaller companies facing steeper challenges due to limited budgets and fewer trained personnel.
- Cloud computing, a technology many companies will adopt before AI, is expected to provide important capabilities that make companies more effective and productive.
- To stay ahead in the rapidly changing global landscape, companies and countries should encourage broader AI adoption for production workloads and enterprise-wide impact, as the use of AI and other digital technologies reshapes the landscape of global competitiveness.
