Mostly Resilient
Last Update: 8/30/2026
AI Resilience Score for Mat. Moving Machine Sup.:
51.4%
Median Score
Meaningful human contribution
Measures the parts of the occupation that still require a human touch. This score averages data from up to four AI exposure datasets, focusing on the role’s resilience against automation.
Med
Long-term employer demand
Predicts the health of the job market for this role through 2034. Using Bureau of Labor Statistics data, it balances projected annual job openings (60%) with overall employment growth (40%).
Med
Sustained economic opportunity
Measures future earning potential and career flexibility. This score is a blend of total projected labor income (67%) and the role’s inherent ability to adapt to economic and technological shifts (33%).
Med
This reflects the reliability of your score based on the number of data sources available for this career and how closely those sources agree on the outlook. A higher confidence means more consistent evidence from labor experts and AI models.
Most data sources align, with only minor variation. This is a well-supported result.
Contributing sources
AI Resilience Report forFirst-Line Supervisors of Material-Moving Machine and Vehicle Operators
$62,890 median salary•900 annual openings•SOC 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.
Learn more about how you can thrive in this position
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.
Read full analysisLearn more about how you can thrive in this position
Analysis of Current AI Resilience
Mat. Moving Machine Sup.
Updated Quarterly

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.

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.
Sources

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.
Sources

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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.
Will AI Replace First-Line Supervisors of Transportation ...
aicareerindex.com • 8/20/2026
AI absorbs routine scheduling ; the durable work is the on-site team leadership, the operational judgment, and the supervisory accountability under safety ...
AI Resilience Report for First-Line Supervisors of Material- ...
www.airesilience.org • 8/20/2026
Jun 19, 2026 — First-Line Supervisors of Material-Moving Machine and Vehicle Operators have a 52.8% AI Resilience Score — slightly more resilient than most ...
The Labor Market Impact of Artificial Intelligence - IMF eLibrary
www.elibrary.imf.org • 8/20/2026
Sep 13, 2024 — On the other hand, AI can boost productivity and value-added, thereby increasing labor demand in non-automated tasks. AI can also create new ... Read more
First-Line Supervisors of Material-Moving Machine and ... - AI Job Risk
www.willaitakemyjob.app • 8/20/2026
What this job actually involves · 01Drive vehicles or operate machines or equipment to complete work assignments or to assist workers. · 02Enforce safety rules ...

Opinion | How AI is impacting 700 professions — and might impact yours
www.washingtonpost.com • 7/28/2025
Companies are rushing to embrace artificial intelligence to cut costs, increase efficiency and better understand this new technology.
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.
Parent Careers
Similar Careers
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
Assist workers in tasks, such as loading vehicles.
2
Drive vehicles or operate machines or equipment to complete work assignments or to assist workers.
3
Resolve worker problems or collaborate with employees to assist in problem resolution.
4
Enforce safety rules and regulations.
5
Confer with customers, supervisors, contractors, or other personnel to exchange information or to resolve problems.
6
Recommend or implement personnel actions, such as employee selection, evaluation, rewards, or disciplinary actions.
7
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.
