Small businesses risk falling behind as AI spreads into blue-collar industries

New U.S. Census Bureau data shows AI adoption is rising faster at larger firms than at businesses with fewer than 20 employees, raising concerns that small operational companies could lose ground as AI becomes standard business infrastructure. In Milwaukee, Select Auto Parts & Sales founder Natasha Broxton is pushing practical AI use in recycling and repair operations.

Why it matters: - AI is moving into warehouses, repair shops, manufacturing facilities, logistics operations and recycling businesses, not just tech companies. - If larger firms adopt AI faster, small manufacturers, recyclers, repair businesses, contractors and logistics companies could face wider gaps in productivity, responsiveness and access to usable information. - Those gaps could affect which businesses win customers, attract workers, compete for contracts and remain locally owned. - Community impact is at stake because independent businesses employ local workers, train people and circulate economic activity through their regions.

What happened: - U.S. Census Bureau data from December 2025 through May 2026 showed overall business AI use hovering between 17% and 20%. - Thirty-seven percent of firms with at least 250 employees reported using AI in their business operations during that period. - AI use increased among firms with at least 20 employees. - AI use did not change significantly among businesses with fewer than 20 employees. - Natasha Broxton, founder and CEO of Select Auto Parts & Sales in Milwaukee, is applying AI-enabled and automated workflows inside a 125,000-square-foot indoor automotive recycling operation. - Broxton also speaks to business leaders, associations, chambers, workforce organizations and industry groups about practical AI implementation. - For interviews, keynote presentations and executive workshops, more information is available at AlituraGroup.com/speaking.

The details: - Select Auto Parts & Sales manages vehicles, used parts inventory, customer inquiries, dismantling, warehousing, transportation and the daily flow of operational information. - Broxton’s AI use focuses on capturing and following up on customer inquiries, organizing operational information and creating more consistent processes when work would otherwise depend on manual follow-up. - The goal is to help employees use information the business already generates, including customer calls, inventory records, estimates, photographs, emails, sales activity, service requests, schedules and operating experience. - In April 2026, the U.S. Department of Labor launched its AI in Registered Apprenticeship Innovation Portal. - The portal gives employers and workforce organizations resources to build AI literacy and add AI-related skills to Registered Apprenticeship programs. - The portal includes industry-specific training resources for advanced manufacturing and other sectors. - The portal also provides pathways for updating existing apprenticeship programs. - Broxton said many workers affected by the next phase of AI adoption will work in manufacturing, transportation, construction, repair, recycling, infrastructure and healthcare.

Between the lines: - The data suggests AI adoption is becoming a business infrastructure issue, not just a software choice. - Larger companies may gain an advantage if they can move faster on information systems, capacity and workflow automation while smaller firms lack the same resources. - That could deepen an existing divide between firms with access to technology support and those relying on manual processes. - Broxton is framing AI as a practical tool for operational businesses, not a branding exercise for tech companies. - The broader argument is that local ownership and economic opportunity may depend on whether small firms can use AI without a costly overhaul.

What's next: - Broxton is continuing to promote practical AI implementation through speaking engagements and executive workshops. - Employers and workforce groups are expected to keep using federal apprenticeship resources as they build AI-related training. - Small businesses will face increasing pressure to turn existing operational data into faster decisions and more consistent workflows. - The adoption gap between large firms and smaller businesses is likely to remain a central issue as AI becomes more common across blue-collar industries.

The bottom line: - AI is no longer only a tech-sector story. - The next competitive divide may be whether small operational businesses can adopt it fast enough to stay in the game.