Somewhat Resilient

Last Update: 8/30/2026

AI Resilience Score for Material Moving Workers:

47.8%

Median Score

Meaningful human contribution

High

Long-term employer demand

Med

Sustained economic opportunity

Low

Our confidence in this score:
Medium

Contributing sources

Methodology and Scoring Rationale

To score how resilient material moving work 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 workers, five of eight sources had data. Among AI exposure sources, AI Resilience Model rated the work High in resilience while OpenAI Signals landed at Medium, a modest split that keeps confidence at medium. Strong physical, on-site demands push human contribution high, but low wage growth pulls the score down, settling this role at "Somewhat Resilient."

AI Resilience Report forMaterial Moving Workers, All Other

$41,800 median salary2,800 annual openingsSOC Code: 53-7199.00

Material Moving Workers, All Other are somewhat less resilient to AI impacts than most occupations, according to our analysis of 5 sources.

Material moving work is labeled "Somewhat Resilient" because automation is genuinely changing the day-to-day reality of this field, even if it is not wiping out jobs entirely. Robots, automated vehicles, and AI-guided systems are taking over many of the repetitive, predictable tasks like transporting pallets or managing warehouse routes, which means the work humans do is shifting rather than disappearing.

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This role is somewhat resilient

Material moving work is labeled "Somewhat Resilient" because automation is genuinely changing the day-to-day reality of this field, even if it is not wiping out jobs entirely. Robots, automated vehicles, and AI-guided systems are taking over many of the repetitive, predictable tasks like transporting pallets or managing warehouse routes, which means the work humans do is shifting rather than disappearing.

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Analysis of Current AI Resilience

Material Moving Workers

Updated Quarterly

Analysis
Suggested Actions
State of Automation

How is AI changing Material Moving Workers jobs?

If you're worried about robots taking over jobs that involve moving stuff around warehouses and construction sites, here's the honest picture: this field is being reshaped by AI, but mostly in a "human + machine" way rather than "machines only." While investments in AI or automation could promote safety and increase efficiencies, there are no warehouses that operate fully autonomously, a human is still required for some tasks.

Right now, AI is showing up as smart equipment that helps workers, not replaces them. On the safety side, ELOKON's ELOshieldAI [1] launched in April 2026 combines tag-based proximity detection with AI-powered vision detection to deliver up to 360-degree visibility, proactive collision prevention and vehicle control integration on forklifts. For moving materials, Global Trade Magazine reports [2] that many warehouses now use a combination of autonomous mobile robots (AMRs), automated guided vehicles (AGVs), conveyors and automated cranes to handle short-distance transport.

According to a Modern Materials Handling analysis [1], Gartner predicts that by 2030, 80% of humans in warehouses will engage with smart robots on a daily basis, and one in 20 supply chain managers will manage robots, rather than humans, by 2030 — so tomorrow's material movers may spend more time supervising, training, and maintaining robots than pushing pallets themselves.

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AI Adoption

How fast is AI adoption growing for Material Moving Workers?

Adoption is happening — but slower than the headlines suggest. The biggest push comes from labor shortages. As CUNY's Issue Number One [3] explains, open supply chain jobs like those in warehousing are actually driving automation investments.

More companies are considering robotics and AI solutions to pair with their current workforce, reduce future need for more workers and address safety concerns, despite high costs associated with the tech. Warehouse work is also physically risky, and AI-guided vehicles can reduce accidents.

But cost is a real brake. As one logistics professor put it, "There are some degrees of automation that are so costly, it's very hard to earn them back. These are huge investments which require a very long horizon." A 2026 MHI and Deloitte survey [4] found that 56% of organizations expect to increase their spending on supply chain innovation with 52% saying they are planning to spend over $1 million.

Seventeen percent plan to spend over $10 million. Yet even that money doesn't erase jobs overnight — the U.S. Bureau of Labor Statistics projects [5] that warehousing firms are increasingly implementing automation solutions to operate more efficiently, such as warehouse management systems, automated guided vehicles, robots, and AI-based systems. The productivity gains stemming from the adoption of these technologies are expected to limit labor demand and thus lead to slower-than-average employment growth in the warehousing and storage services industry from 2024 to 2034.

The takeaway for young people: the field isn't disappearing, but it is changing. Human judgment for messy real-world situations — inspecting equipment, handling slides or repairs, and troubleshooting robots — remains valuable. Building skills in equipment maintenance, safety, and basic robotics/data literacy will make you the person companies want on the floor as these smart systems roll out.

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Will AI replace Material Moving Workers?

Will AI replace Material Moving Workers?

Not entirely. We think AI will take over some tasks, but not the whole job.

Our 47.8% AI Resilience Score reflects real pressure on this field, but also real staying power. AI is already on the warehouse floor in the form of autonomous mobile robots, automated guided vehicles, and AI-powered safety systems that give forklifts 360-degree collision awareness [1]. By 2030, Gartner predicts 80% of warehouse workers will interact with smart robots daily [1]. That is a big shift, but it is a shift in how the job works, not a signal that the job disappears.

What keeps humans in the picture is the messy, unpredictable nature of real-world materials work. Inspecting equipment, troubleshooting a robot that gets stuck, handling unusual loads, and making judgment calls on safety are things machines still need people for. Even with heavy investment, logistics experts note that full automation carries enormous costs and very long payback horizons [3].

The BLS does project slower-than-average employment growth as automation limits labor demand [5], so the economic picture is genuinely mixed. The workers who will do best are those who build skills in equipment maintenance, safety, and basic robotics literacy, becoming the people companies need to keep their smart systems running.

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Latest AI news for Material Moving Workers

These articles highlight the evolving landscape for Material Moving Workers, All Other, emphasizing the need for adaptation in an AI-driven environment. For instance, as AI reshapes supply chains, workers are becoming central to these systems, indicating a shift rather than outright replacement. Additionally, understanding the AI risk score of 36/100 suggests that while there are challenges, there are also opportunities to enhance skills and remain valuable. Embracing AI resilience can lead to innovation and a stronger role in this transforming field.

More Career Info

Career: Material Moving Workers, All Other

They move and organize materials using equipment like forklifts or cranes to keep goods flowing smoothly in warehouses or construction sites.

Employment & Wage Data

Median Wage

$41,800

Jobs (2025)

27,800

Growth (2025-35)

+2.7%

Annual Openings

2,800

Education

No formal educational credential

Experience

None

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

92% ResilienceSupplemental

Perform manual labor to prepare or finish sites, such as shoveling materials by hand.

2

91% ResilienceCore Task

Handle slides, mud, or pit cleanings or maintenance.

3

90% ResilienceCore Task

Lubricate, adjust, or repair machinery and replace parts, such as gears, bearings, or bucket teeth.

4

88% ResilienceCore Task

Move levers, depress foot pedals, and turn dials to operate power machinery, such as power shovels, stripping shovels, scraper loaders, or backhoes.

5

88% ResilienceCore Task

Create or maintain inclines or ramps.

6

86% ResilienceCore Task

Operate machinery to perform activities such as backfilling excavations, vibrating or breaking rock or concrete, or making winter roads.

7

85% ResilienceCore Task

Observe hand signals, grade stakes, or other markings when operating machines so that work can be performed to specifications.

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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