In an era dominated by the relentless advance of technology, artificial intelligence (AI) has become both the beacon of innovation and a source of economic disparity across the United States. The rise in AI adoption, a staggering 266% in the last five years, has prompted a group of economists to delve into the intricate details of its impact. Their findings, based on a comprehensive 2018 survey covering 474,000 firms, paint a nuanced picture of the AI landscape in the country.
Clustering and contrasts in AI adoption
The report, distributed via the National Bureau of Economic Research, dissects the AI economy, focusing on five specific technologies: autonomous vehicles, machine learning, machine vision, natural language processing, and voice recognition. While less than 6% of businesses were utilizing these technologies in 2018, the adoption rate skyrocketed in larger firms, especially those with over 5,000 employees, where the average adoption reached more than 18%.
Recent data from a McKinsey study further underscores the widespread exposure to generative AI, with 79% of respondents reporting some level of interaction with the technology. This surge in AI adoption is not uniform across the nation, giving rise to what economists are dubbing the ‘AI divide.’
The authors of the report express concern about the potential emergence of an ‘AI divide’ across regions and cities, emphasizing that, despite the initial phase of AI adoption across the country, the uneven spread of AI use raises apprehensions about diverging economic outcomes. The concentration of AI usage is evident in tech hubs like California’s Silicon Valley and the San Francisco Bay Area. Surprisingly, other cities such as Nashville, San Antonio, Las Vegas, New Orleans, San Diego, and Tampa, as well as Riverside, Louisville, Columbus, Austin, and Atlanta, also showcase substantial AI activity.
Kristina McElheran, one of the authors and an associate professor of strategic management at the University of Toronto Scarborough, acknowledges the benefits of economic clustering for technological advancement. Kristina McElheran acknowledges the potential benefits of economic clustering, emphasizing the facilitation of idea and knowledge exchange among firms and workers due to geographical proximity. But, concerns arise if certain locales are consistently left behind or become overly specialized, risking challenges in the face of economic shocks.
Reflecting on her upbringing in Michigan, Kristina McElheran highlights the firsthand impact of a declining auto-intensive economy caused by the sharp downturn in domestic auto manufacturing. Her experience underscores the challenges associated with such economic shifts, emphasizing the difficulty of recovery from the ensuing regional imbalances.
Business leadership and innovation
The research not only highlights geographical disparities but also underscores the role of business leadership in shaping the AI landscape. In-depth analysis of over 75,000 young firms reveals a correlation between founders motivated to bring new ideas into the world and AI adoption. The study suggests that high-growth, innovative startups exert pressure on the rate and direction of AI change, potentially steering it in dynamic and positive ways.
McElheran suggests that the study unveils a fresh perspective: high-growth, innovative startups exerting influence on the pace and trajectory of change, hinting at a potentially positive and dynamic outcome.
Bridging the AI divide
As AI continues its meteoric rise, the concerns about an ‘AI divide’ persist. The economic benefits of AI adoption appear to be unevenly distributed, raising questions about the long-term consequences for regions and cities across the country. Can policies and investments bridge this gap, ensuring that the promises of AI reach all corners of the nation? The trajectory of AI adoption remains uncertain, and as the nation grapples with this technological revolution, the challenge is not just embracing the potential of AI but ensuring its benefits are shared by all.
