The real story of AI in America3 min read

Reading Time: 3 minutesReading Time: 3 minutes

A recent article by Brian Eastwood discusses research spearheaded by Kristina McElheran in collaboration with the National Bureau of Economic Research, the U.S. Census Bureau, and the National Center for Science and Engineering Statistics. Experts analyze 850,000 firms across the private non-farm economy. The study sheds light on the early adoption and diffusion of five AI-related technologies (automated-guided vehicles, machine learning, machine vision, natural language processing, and voice recognition) in various sectors and regions in America. As of 2017, larger firms and specific industries, particularly in manufacturing, information technology, and health services, concentrated on the low overall adoption of AI.

Here are the detailed findings based on the document:

Overall AI use: Only 2% of firms reported any use of AI. The adoption rates of specific AI-related technologies were below 3% across the board, with machine learning being the highest at 2.9% and automated guided vehicles the lowest at 0.8%.
AI use by firm size: AI use appears highly skewed and concentrated among larger firms. The majority of firms with more than 5000 employees reported at least some use of AI, with over a quarter of the largest firms using AI intensively.
AI use by sector: Manufacturing and information-sector firms led in early AI adoption with roughly 12% adoption rates. Health-related firms and professional services followed in intensity of use. Sectors like construction and retail trade lagged at approximately 4% each. Finance, insurance, and real estate sectors had adoption rates below 6%, despite high levels of digitization.
AI and technology interdependencies: Firms that reported AI use were most likely to analyze data using cloud-based IT services and store their production information digitally. The interdependencies between AI, cloud computing, and digitization suggest that firms adopting AI prefer to engage in broader technological advancements.
AI in entrepreneurship: Owners with an advanced degree (31.5% vs. 22.4% overall) and venture capital funding (2.9% vs. 0.9% overall) characterized AI-using startups. These AI-using startups also reported larger capitalization on average and focused on innovation and business strategies, with 39.3% engaged in process innovation and 66.3% in product innovation.
Geography of AI-using startups: Metro areas with populations of 1 million or more host over 50% of AI-using startups, featuring significant concentrations in technology hubs such as Silicon Valley and Research Triangle, along with other areas across the South and West, including Nashville, San Antonio, Las Vegas, New Orleans, San Diego, and Tampa.

The study also addresses the challenges of AI integration, noting inertia and adjustment costs as significant barriers. Routine practices within companies and the costs associated with adopting new technologies can hinder AI’s spread. Moreover, the transition towards AI can lead to economic adjustments, including job losses and a shift in skill demand, disproportionately affecting older workers.

This detailed examination brings to light the multifaceted nature of AI integration in the American economy, stressing the need for a balanced and informed approach. It underscores the importance of recognizing both the opportunities AI presents and the challenges it poses, from sectoral impacts to regional disparities. Maximizing AI benefits demands a concerted effort to mitigate its potential downsides, focusing keenly on economic and societal wellbeing.

Adding to this perspective, recent findings from BCG highlight a key strategy among AI adoption leaders: a deep commitment to workforce development. Notably, 21% of organizations investing over $50 million in AI and GenAI projects this year have already educated more than a quarter of their staff. This educational initiative encompasses the general workforce and top executives, underscoring the critical role of comprehensive learning and development throughout the organization.

A new BCG survey involving over 1,400 C-suite executives across 50 markets has illuminated a significant concern that 66% of leaders express ambivalence or dissatisfaction with their company’s advancements in these areas. This sentiment underscores a pressing need for organizations to accelerate their efforts in embracing transformative technologies and fostering a culture of learning and adaptation. By doing so, companies can better position themselves to navigate the challenges of digital transformation and harness the opportunities it presents.