AUTOMATION is rapidly reshaping labor-intensive industries, with new data showing high displacement risks for workers in manufacturing, agriculture and retail, according to a report by Planera, a workforce analytics and automation research firm.
The study found that several occupations face significant automation exposure, particularly roles that involve repetitive physical tasks.
Loading and moving machine operators in underground mining face a 97-percent automation risk, with employment projected to decline by more than 22 percent.
In manufacturing, milling and planing machine operators face a 14.4-percent risk of job loss over the next decade.
Agricultural graders and sorters face an 89-percent automation risk, while cashiers — one of the largest employment groups — face an 88-percent risk of displacement.
“The conversation about automation has been almost entirely focused on office workers and knowledge jobs, but the production floor is quietly going through an equally significant shift,” an automation expert from Planera said.
“Patternmakers and machine operators don’t make headlines the way software engineers do, but the people in these roles are facing some of the most immediate disruption in the entire job market.”
The findings highlight how automation is expanding beyond white-collar roles and increasingly affecting frontline and industrial jobs that have historically received less attention in discussions about artificial intelligence.
Uneven impact on labor markets
This trend is consistent with broader global labor assessments. The International Labour Organization (ILO), a United Nations agency focused on labor and employment issues, has warned that automation and digital technologies are likely to disproportionately affect routine and manual jobs, particularly in developing economies where large segments of the workforce are engaged in low-skilled work.
According to the ILO, while automation can improve productivity and create new forms of employment, it also risks widening inequality if workers are not equipped with the skills required to transition into new roles. The organization has emphasized that sectors such as manufacturing, retail and agriculture — which align closely with Planera’s findings — are among the most vulnerable to technological disruption.
The ILO has also noted that the pace of change is accelerating, with digital transformation compressing what were once gradual labor shifts into shorter timeframes. This creates pressure on governments and industries to implement reskilling and social protection mechanisms to mitigate job displacement.
At the same time, global trade dynamics are being reshaped by the same technological forces. The World Trade Organization (WTO), an international body that regulates global trade, has reported that automation and AI are altering supply chains, production models and competitiveness across economies.
The WTO has observed that advanced manufacturing technologies, including robotics and AI-driven systems, are reducing the importance of low-cost labor as a competitive advantage. This shift could affect export-oriented economies that rely heavily on labor-intensive industries, particularly in Asia.
Automation is also enabling more localized and flexible production, allowing companies to move closer to end markets and reduce reliance on complex global supply chains. While this can improve efficiency and resilience, it may also disrupt traditional trade patterns and employment structures tied to manufacturing hubs.
These structural shifts are unfolding alongside the rapid emergence of physical artificial intelligence (PAI), which integrates digital intelligence directly into machines and industrial systems.
Physical AI reaches deployment phase
A separate report by Deloitte, a global professional services firm, said physical AI — systems that combine AI with machines such as robots and autonomous vehicles — is moving from experimental use to real-world deployment across industries.
Physical AI enables machines to perceive their environment, make decisions in real time and act in the physical world, bridging digital intelligence and industrial operations.
“PAI is no longer a question of ‘if’ or ‘when’ — it is a question of readiness,” the report said.
Deloitte noted that only 3 percent of firms have extensively integrated physical AI into operations today, but this is expected to rise to 18 percent within two years.
Within three years, 41 percent of business leaders expect the technology to have a transformational impact on their organizations.
Industrial robotics is emerging as the primary testing ground, where AI-enabled machines are already reducing human error, optimizing resources and enabling self-adjusting production systems.
Globally, the deployment of industrial robots continues to expand, reflecting growing investment in automation technologies and the increasing maturity of AI-enabled systems.
Despite this momentum, companies face operational and technical barriers, including high costs, limited use cases, talent shortages and gaps in data infrastructure.
Deloitte emphasized that successful adoption depends not only on technological capability but also on organizational readiness. Companies must establish standardized processes, integrate digital systems and develop the necessary workforce skills to fully realize the benefits of physical AI.
The report also pointed to a growing need for hybrid professionals who understand both industrial operations and data science, a talent pool that remains limited and takes years to develop.
The convergence of these trends — rising automation risk, evolving global trade dynamics and accelerating AI adoption — suggests a widening gap between technological capability and workforce readiness.
For policymakers and businesses, the challenge is no longer whether automation will reshape work, but how quickly and how unevenly that transformation will occur.
While physical AI promises efficiency gains, improved productivity and new business models, the parallel rise in automation risk underscores the need for coordinated workforce transition strategies, including reskilling, education reform and stronger labor protections.
The ILO has stressed that without deliberate intervention, technological progress could deepen existing inequalities, particularly in regions where workers have limited access to training and digital infrastructure.
Meanwhile, the WTO has highlighted the importance of aligning trade policies with technological change to ensure that the benefits of innovation are more broadly distributed.
Together, the findings point to a structural shift in how work is performed, as machines increasingly take on physical and repetitive tasks once carried out by human labor, and organizations adapt to a new balance between human and machine intelligence.