Mostly Resilient

Last Update: 5/19/2026

Your role’s AI Resilience Score is

53.8%

Median Score

Meaningful human contribution

Med

Long-term employer demand

Med

Sustained economic opportunity

Med

Our confidence in this score:
High

Contributing sources

AI Resilience Report forFirst-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers

First-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers are somewhat more resilient to AI impacts than most occupations, according to our analysis of 7 sources.

This career holds up well against AI because the heart of the job — leading a crew, reading a job site, handling unexpected problems, and keeping clients happy — requires human judgment and people skills that robots simply can't replicate. AI and autonomous mowers are definitely changing some of the work, taking over repetitive tasks like mowing open turf so supervisors can focus on the detail work that actually requires experience and decision-making.

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Learn more about how you can thrive in this position

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Analysis
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This role is mostly resilient

This career holds up well against AI because the heart of the job — leading a crew, reading a job site, handling unexpected problems, and keeping clients happy — requires human judgment and people skills that robots simply can't replicate. AI and autonomous mowers are definitely changing some of the work, taking over repetitive tasks like mowing open turf so supervisors can focus on the detail work that actually requires experience and decision-making.

Read full analysis

Analysis of Current AI Resilience

Landscaping Supervisors

Updated Quarterly • Last Update: 5/14/2026

Analysis
Suggested Actions
State of Automation

How is AI changing Landscaping Supervisors jobs?

Right now, AI is mostly augmenting — not replacing — landscape supervisors. The biggest shift is happening with autonomous mowers. According to a trade publication report, one of the most significant advancements in autonomous mowing is the shift from traditional boundary wires to GPS and real-time kinematic (RTK) technology, along with a sophisticated blend of cameras and computer vision, inertial measurement units, ultrasonic and lidar sensors, and precision mapping.

These machines now travel with crews from site to site as "your next team member" [1], letting supervisors deploy people on detail work while a robot handles open turf. A May 2026 industry analysis [2] notes the industry is moving from "rule-based automation" to spatially intelligent systems using AI vision and RTK positioning.

Supervisors' administrative tasks are also being augmented. NALP's 2026 report found that 62% of commercial landscape companies are using seven or more software systems, with the most common being accounting, invoicing, estimating, marketing automation, payroll, GPS tracking, and end-to-end business management. AI design tools are also gaining traction — though industry experts emphasize that contractors "need AI to be a helper, not a doer" [1], assisting with imaging, CAD drawings, and estimates rather than running the job.

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AI Adoption

How fast is AI adoption growing for Landscaping Supervisors?

Adoption pressure is strong but uneven. The U.S. Bureau of Labor Statistics projects [3] about 171,600 grounds-maintenance openings per year through 2034 — a chronic labor gap that pushes employers toward automation. NALP's survey confirms this: 54% cite recruiting and retaining staff as a major business risk, and 70% plan to raise wages, while the top reasons companies change software are to automate workflows (58%) and improve operational efficiency (51%).

Still, full adoption will be slow. Commercial autonomous mowers cost tens of thousands of dollars, and the work itself is messy, weather-exposed, and unpredictable — areas where humans still excel. The World Economic Forum's outlook [4] projects a net 78 million new roles by 2030 even as 22% of jobs change structurally, with human-centered skills remaining highly valued.

That's good news for you: supervisors who can lead crews, talk with clients, troubleshoot equipment, and learn new software will likely become more valuable, not less. The robot can mow the lawn, but it can't mentor a new hire, calm an upset homeowner, or decide what to do when a storm flattens a job site.

Sources

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More Career Info

Career: First-Line Supervisors of Landscaping, Lawn Service, and Groundskeeping Workers

They oversee teams that maintain and beautify outdoor spaces, ensuring tasks like mowing and planting are done correctly and safely.

Employment & Wage Data

Median Wage

$56,170

Jobs (2024)

224,700

Growth (2024-34)

+2.3%

Annual Openings

23,200

Education

High school diploma or equivalent

Experience

Less than 5 years

Source: Bureau of Labor Statistics, Employment Projections 2024-2034

Task-Level AI Resilience Scores

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

1

95% ResilienceSupplemental

Tour grounds, such as parks, botanical gardens, cemeteries, or golf courses, to inspect conditions of plants and soil.

2

93% ResilienceCore Task

Inventory supplies of tools, equipment, or materials to ensure that sufficient supplies are available and items are in usable condition.

3

92% ResilienceCore Task

Plant or maintain vegetation through activities such as mulching, fertilizing, watering, mowing, or pruning.

4

90% ResilienceCore Task

Direct activities of workers who perform duties such as landscaping, cultivating lawns, or pruning trees and shrubs.

5

90% ResilienceCore Task

Perform administrative duties, such as authorizing leaves or processing time sheets.

6

85% ResilienceCore Task

Establish and enforce operating procedures and work standards that will ensure adequate performance and personnel safety.

7

85% ResilienceCore Task

Review contracts or work assignments to determine service, machine, or workforce requirements for jobs.

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.

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