At a time when conversations around artificial intelligence are often dominated by job loss fears, a new April 2026 report offers a more layered reality. It shows that while some parts of the workforce are highly exposed to automation, others remain firmly rooted in human capability.
The study by construction scheduling platform Planera focuses on physical and manual professions, and the numbers reveal a clear divide. Emergency services have the lowest average automation risk at 11%, followed by social services at 12% and healthcare at 16%. These sectors rely heavily on human judgment, empathy, and real-time response, making them far harder to replace.
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But the deeper data shows how sharply the risk rises in other parts of the economy. Agriculture leads with an 89% automation risk, followed by production at 82%, utilities at 81%, and retail at 80%. Logistics and mining both stand at 77%, while transportation reaches 68%. Even food service, often seen as people-driven, faces a 62% risk. The pattern is consistent: the more repetitive and process-driven the work, the easier it is to automate.
That trend becomes even clearer when looking at individual roles most likely to be automated first. Patternmakers in metal and plastic top the list with a 99% automation risk, followed by underground mining machine operators at 97% and milling and planing machine operators at 91%. Agricultural graders and sorters stand at 89%, while cashiers face an 88% risk. A wide range of production-line roles, from sewing machine operators to grinding and polishing workers, fall in the mid-to-high 80% range, while jobs like postal service sorters, meter readers, and drivers continue to see risks above 75%.
Service roles are not immune either. Retail salespersons show a 71% automation risk, while waiters and waitresses stand at 69%, and restaurant cooks at 57%. In construction and maintenance, the picture is more mixed, with several roles falling in the mid-range risk band, even as skilled trades show greater resilience.
Against this backdrop, the least automatable jobs stand out even more sharply. Emergency medical technicians top that list with just a 7% risk. As first responders, they are required to assess medical conditions and deliver life-saving care in unpredictable environments. That combination of urgency, physical skill, and decision-making keeps the role firmly human.
Firefighters follow at 9%, reinforcing the strength of emergency services overall. The sector’s average risk of 11% is significantly lower than industries like repair and maintenance at 37% or construction at 38%. Healthcare social workers come in at 12%, where empathy and communication remain central to the job.
Police officers and sheriff’s patrol officers also rank among the most secure at 13%. While parts of their administrative work can be automated, their core responsibilities continue to depend on human judgment and situational awareness.
Among the trades, electricians stand out with a 14% automation risk and strong demand growth. The report highlights that this role sits at the intersection of low automation risk and rising necessity, especially as infrastructure evolves.
An automation expert from Planera captured this shift, saying, “Low automation risk and growing demand are a rare combination in today’s job market, but electricians have both, as do many construction trades. The electrician shortage is projected to worsen through 2026, with over 80K new positions expected nationally, driven by aging infrastructure, EV charging networks, and the energy transition. The irony is that AI data centers, the very technology driving automation fears, need electricians to get built and kept running. That’s about as future-proof as a job can get.”
The study, which analyzed more than 55 manual professions, deliberately excluded office and technology roles to focus on what it describes as the physical backbone of the workforce. Using employment data from the U.S. Bureau of Labor Statistics’ Occupational Employment and Wage Statistics survey from May 2024, researchers narrowed down 63 roles across trades, production, logistics, healthcare, and service sectors. Automation risk estimates were drawn from a machine learning model trained on O*NET job attribute data, and each occupation was then ranked based on its likelihood of being automated.
What emerges is not just a warning, but a shift in perspective. Jobs built on repetition are moving closer to automation at scale, in some cases nearing complete replacement. At the same time, roles that depend on human instinct, adaptability, and connection are not just holding steady, they are becoming more essential in an AI-driven economy.
This story is based on the data shared with us by Planera