Mostly Resilient

Last Update: 8/30/2026

AI Resilience Score for Mat. Moving Machine Sup.:

51.4%

Median Score

Meaningful human contribution

Med

Long-term employer demand

Med

Sustained economic opportunity

Med

Our confidence in this score:
Medium-high

Contributing sources

Methodology and Scoring Rationale

To score how resilient supervising material-moving machine and vehicle operators is to AI, we ask one question in three parts:

First, how much of the job still needs a human, read from five AI-exposure sources: our own AI Resilience Model, Anthropic's Observed Exposure, Microsoft's AI Applicability, Will Robots Take My Job, and OpenAI Signals. We call this dimension Meaningful Human Contribution (MHC) and weight it at 40%.

Next, whether employers will keep hiring for this job over the long term. This dimension, which we call Long-term Employer Demand (LTE), is calculated from BLS data and weighted at 30%.

Last, whether pay and mobility will hold up. We use wage bill and adaptive capacity data from independent researchers (Althoff & Reichardt, 2026; Manning & Aguirre, 2026). We call this dimension Sustained Economic Opportunity (SEO) and weight it at 30%.

For material-moving machine supervisors, six of eight sources had data (Anthropic and Microsoft had none), and the sources that did respond showed solid agreement: AI Resilience Model, Will Robots Take My Job, and OpenAI Signals all rated AI exposure as Medium. Demand and pay signals were steady, with Adaptive Capacity coming in High, pushing the score toward "Mostly Resilient."

AI Resilience Report forFirst-Line Supervisors of Material-Moving Machine and Vehicle Operators

$62,890 median salary900 annual openingsSOC Code: 53-1043.00

First-Line Supervisors of Material-Moving Machine and Vehicle Operators are somewhat more resilient to AI impacts than most occupations, according to our analysis of 6 sources.

This career is labeled "Mostly Resilient" because while AI is taking over some of the more routine tasks (like scheduling, record-keeping, and safety monitoring), the core of the job still depends on human judgment, people skills, and on-the-floor problem-solving that AI simply cannot replicate. The role is actually evolving in an exciting direction: supervisors are becoming managers of both human workers and automated systems like robots and self-driving vehicles, which means the job is shifting rather than disappearing.

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This role is mostly resilient

This career is labeled "Mostly Resilient" because while AI is taking over some of the more routine tasks (like scheduling, record-keeping, and safety monitoring), the core of the job still depends on human judgment, people skills, and on-the-floor problem-solving that AI simply cannot replicate. The role is actually evolving in an exciting direction: supervisors are becoming managers of both human workers and automated systems like robots and self-driving vehicles, which means the job is shifting rather than disappearing.

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Analysis of Current AI Resilience

Mat. Moving Machine Sup.

Updated Quarterly

Analysis
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State of Automation

How is AI changing Mat. Moving Machine Sup. jobs?

If you're picturing warehouses full of robots replacing every human, the reality on the floor in 2026 is more nuanced — AI is mostly augmenting supervisors, not erasing them. In Modern Materials Handling's July 2026 feature on the state of AI in warehousing, industry experts describe AI as intelligently orchestrating the entire warehouse in real time, shifting operations from static, rules-based systems to intelligent, orchestrated ecosystems. On the reporting and scheduling side, agentic AI platforms like Aura let users upload packing and process instructions so the system builds the workflow and connects it to automation, and new employees can simply ask the system what to do in each scenario — that directly touches supervisors' record-keeping, reporting, and work-sequencing tasks (the ones with 68–75% automation exposure).

On the operations side, autonomous vehicles are reshaping what supervisors oversee. Vecna Robotics' chief commercial officer told Modern Materials Handling that it's very natural for a picker running a forklift to become a supervisor managing the material flow of the entire automation solution, and new automation-oriented roles are emerging. Crown Equipment describes a role called an AGV tender — typically a former lift truck operator — where five tenders can manage a 50-truck fleet of automated vehicles.

AI safety cameras and computer-vision systems are also taking over parts of the "enforce safety rules" task by flagging near-misses automatically, though the human judgment piece (coaching workers, resolving problems) still belongs to people.

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AI Adoption

How fast is AI adoption growing for Mat. Moving Machine Sup.?

Adoption is happening fast in this field for a few clear reasons. Roland Berger's April 2026 outlook projects the warehouse automation market growing at a 7–10% CAGR through 2030, with the US returning to double-digit growth fueled by greenfield warehouses, reshoring, and renewed e-commerce momentum, and mobile automation like AMRs and AGVs is forecast to grow around 30% annually [1] between 2025 and 2030. Labor economics are pushing hard: a Manufacturing Institute study cited by Hyster found 1.9 million manufacturing jobs could go unfilled over the next decade, and labor is the No. 1 ask from customers because they're struggling with turnover and rising wages.

But adoption isn't a simple replacement story. PYMNTS reported that North American warehouses ordered nearly 18,000 robots worth roughly $1.2 billion in the first half of 2026, yet job openings in transportation, warehousing and utilities rose by 97,000 in June alone — one of the largest monthly increases across any industry tracked in the BLS JOLTS survey. The BLS 2024–34 projections still show transportation and material moving occupations growing by about 4.1%, adding roughly 580,000 jobs [2].

Costs, integration complexity, and safety/liability rules slow things down: Crown's Jim Gaskell warned that one of the biggest misconceptions is that you can replace a manual process with an automated system with little to no process changes. The most hopeful takeaway comes from Logistics Management's editor, who argues AI's greatest value is amplifying human capability rather than replacing workers, and the real differentiator will be an organization's ability to develop a workforce capable of managing, supervising, and scaling those technologies. In other words, supervisors who learn to coach both people and robots are the ones the industry is actively hiring for.

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Will AI replace Mat. Moving Machine Sup.?

Will AI replace Mat. Moving Machine Sup.?

No. We don't think AI will replace First-Line Supervisors of Material-Moving Machine and Vehicle Operators, though we do expect the job to change.

Our 51.4% AI Resilience Score puts this role in "Mostly Resilient" territory, and the data backs that up. AI is already reshaping warehouses fast: the warehouse automation market is projected to grow at 7 to 10% annually through 2030 [1], and autonomous vehicles are multiplying on floors everywhere. But that growth is creating new supervisory work, not eliminating it. One telling example: a single operator can now manage a fleet of dozens of automated vehicles, which means the supervisor role is expanding in scope, not disappearing.

What stays human is the part that actually holds operations together. Coaching workers, resolving unexpected problems, making judgment calls when something goes wrong, and keeping teams accountable are things AI systems flag but cannot own. The BLS projects transportation and material moving occupations to keep growing through 2034 [2], and job openings in the sector have been rising sharply. The supervisors who will thrive are the ones who get comfortable managing both people and machines, treating automation as a tool they direct rather than a force that directs them.

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Latest AI news for Mat. Moving Machine Sup.

These articles highlight how AI is reshaping the role of First-Line Supervisors of Material-Moving Machine and Vehicle Operators. While AI can handle routine scheduling, the human aspects of leadership and safety oversight remain crucial. For instance, the AI Resilience Report notes a 52.8% score for this role, indicating a solid capacity to adapt alongside AI advancements. Additionally, the IMF eLibrary article suggests that AI can enhance productivity, potentially increasing demand for skilled supervisors who can manage complex operations. Embracing these changes can position students for success in an evolving job landscape.

More Career Info

Career: First-Line Supervisors of Material-Moving Machine and Vehicle Operators

They oversee workers who operate machines and vehicles, ensuring tasks are done safely and efficiently while managing schedules and resolving any work issues.

Employment & Wage Data

* Data estimated from parent occupation

Median Wage

$62,890

Jobs (2025)

9,700

Growth (2025-35)

+9.3%

Annual Openings

900

Education

High school diploma or equivalent

Experience

Less than 5 years

Source: Bureau of Labor Statistics, Employment Projections 2025-2035

Task-Level AI Resilience Scores

AI-generated estimates of task resilience over the next 3 years

1

94% ResilienceSupplemental

Assist workers in tasks, such as loading vehicles.

2

92% ResilienceCore Task

Drive vehicles or operate machines or equipment to complete work assignments or to assist workers.

3

90% ResilienceCore Task

Resolve worker problems or collaborate with employees to assist in problem resolution.

4

88% ResilienceCore Task

Enforce safety rules and regulations.

5

82% ResilienceCore Task

Confer with customers, supervisors, contractors, or other personnel to exchange information or to resolve problems.

6

82% ResilienceCore Task

Recommend or implement personnel actions, such as employee selection, evaluation, rewards, or disciplinary actions.

7

80% ResilienceCore Task

Explain and demonstrate work tasks to new workers or assign training tasks to experienced workers.

Tasks are ranked by their AI resilience, with the most resilient tasks shown first. Core tasks are essential functions of this occupation, while supplemental tasks provide additional context.

The AI Resilience Report is a project from CareerVillage.org®, a registered 501(c)(3) nonprofit.

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