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Will AI replace agricultural engineers?

A little.

This job scores 78 out of 100 on (higher is safer). Today people do 17% of the work with AI’s help, and 83% still needs a person.

Updated 3 October 2026 17-2021 2125 2026-Q4
Architecture and EngineeringAgricultural Engineers17-2021 · 2026-Q4
0% AI does it17% AI helps83% needs a human
Your job's name, lit by the work that still needs a human.Needs a human 83%AI helps 17%AI does it 0%

AI does it: AI can do the task largely by itself. AI helps: a person still does it, faster with AI. Needs a human: AI can do little of it yet.

Each ridge is a slice of the job's task time.Needs a human 83%AI helps 17%AI does it 0%
The job’s mark

No two jobs leave the same print

Every job gets its own fingerprint, drawn from its code. The amber ridges are the share of task time that still needs a person. Below them, the same ridges are written out in ones and zeros: slate for the work AI helps with, white for the work AI can do.

Agricultural Engineers, O*NET-SOC 17-2021. 83% of the job’s task time still needs a human, so 83 of every 100 ridges are amber; slate is what AI helps with, white what AI can do.

What AI can and cannot do

The tasks that make up the job, from , and where AI stands on each today: , (a person does it, with AI speeding it up) or . 83% of the still needs a human.

Each block is one task; its height is its share of working time.Needs a human 83%AI helps 17%AI does it 0%
The job's task list: the parts AI can do are blacked out.Needs a human 83%AI helps 17%AI does it 0%
Prepare reports, sketches, working drawings, specifications, proposals, and budgets for proposed sites or systems.AI helps
Visit sites to observe environmental problems, to consult with contractors, or to monitor construction activities.Needs a human
Meet with clients, such as district or regional councils, farmers, and developers, to discuss their needs.Needs a human
Discuss plans with clients, contractors, consultants, and other engineers so that they can be evaluated and necessary changes made.Needs a human
Test agricultural machinery and equipment to ensure adequate performance.Needs a human
Plan and direct construction of rural electric-power distribution systems, and irrigation, drainage, and flood control systems for soil and water conservation.Needs a human
Provide advice on water quality and issues related to pollution management, river control, and ground and surface water resources.AI helps
Design structures for crop storage, animal shelter and loading, and animal and crop processing, and supervise their construction.Needs a human
Conduct educational programs that provide farmers or farm cooperative members with information that can help them improve agricultural productivity.Needs a human
Design sensing, measuring, and recording devices, and other instrumentation used to study plant or animal life.Needs a human
Design agricultural machinery components and equipment, using computer-aided design (CAD) technology.Needs a human
Design and supervise environmental and land reclamation projects in agriculture and related industries.Needs a human
Design food processing plants and related mechanical systems.Needs a human
Supervise food processing or manufacturing plant operations.Needs a human

Is it better than a person? The evidence

No direct test against people in this job yet. Every study is , and vendor studies are labelled as such.

When could it be replaced?

When AI could largely do this job: 2037–2056

Most likely between 2037 and 2056 (8 in 10 of our scenarios). A range from our of how fast AI improves, how fast employers take it up and what holds it back, not a forecast that the job ends. “” has a strict meaning here. Today’s answer is at the top of the page; this is how it could change.

The sand is the human working years left, measured in the same 40-year glass for every job, so a safe trade starts nearly full and an exposed job with a thin layer.

The sand is the human working years left, in the same 40-year glass for every job.Years still needing a humanYears run out

How this job could shift, year by year

Where the job could sit on our scale each year to 2060, across the ten behind its .

Today
Will AI replace this job?
A little.
By 2045
70%
of our scenarios have AI largely doing this job by 2045 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)
By 2060
100%
of our scenarios have AI largely doing this job by 2060 (Largely.)
0% still have it mostly needing a person (A little. or Nah.)

We run this job as ten scenarios spread across its replacement range. In each, the score moves towards the bottom band (Largely: AI could largely do the job) by the year that scenario reaches it, slowly at first and faster later, as adoption usually goes. Each bar splits the ten by the band they put the job in. The model stops at 2060. How the timeline works

Share of this job's scenarios in each verdict band, today to 20600%25%50%75%100%2026: 100.0% of scenarios: AI could do a little of this job (A little.)100%Today2030: 90.0% of scenarios: AI could do a little of this job (A little.)90%2030: 10.0% of scenarios: AI could partly do this job (Partly.)10%20302035: 20.0% of scenarios: AI could do a little of this job (A little.)20%2035: 30.0% of scenarios: AI could partly do this job (Partly.)30%2035: 40.0% of scenarios: AI could mostly do this job (Mostly.)40%2035: 10.0% of scenarios: AI could largely do this job (Largely.)10%20352040: 30.0% of scenarios: AI could partly do this job (Partly.)30%2040: 20.0% of scenarios: AI could mostly do this job (Mostly.)20%2040: 50.0% of scenarios: AI could largely do this job (Largely.)50%20402045: 30.0% of scenarios: AI could mostly do this job (Mostly.)30%2045: 70.0% of scenarios: AI could largely do this job (Largely.)70%20452050: 10.0% of scenarios: AI could mostly do this job (Mostly.)10%2050: 90.0% of scenarios: AI could largely do this job (Largely.)90%20502055: 100.0% of scenarios: AI could largely do this job (Largely.)100%20552060: 100.0% of scenarios: AI could largely do this job (Largely.)100%2060
Will AI replace the job?Largely.Mostly.Partly.A little.Nah.
Share of this job's scenarios in each band, year by year. Updated with every release.
Show the data
YearLargelyMostlyPartlyA littleNah
Today (2026)0.0%0.0%0.0%100.0%0.0%
20300.0%0.0%10.0%90.0%0.0%
203510.0%40.0%30.0%20.0%0.0%
204050.0%20.0%30.0%0.0%0.0%
204570.0%30.0%0.0%0.0%0.0%
205090.0%10.0%0.0%0.0%0.0%
2055100.0%0.0%0.0%0.0%0.0%
2060100.0%0.0%0.0%0.0%0.0%

What’s stopping AI taking over?

The things that keep this work with people, strongest first. Each is scored 0 to 100 from work context, licensing and the evidence we have.

LiabilityMistakes are rated 3.0 out of 5 for consequence and decisions 3.5 out of 5 for impact; someone has to answer for them.
Evidence gapNo study yet compares AI with people doing this job, so employers have no proof it is good enough.
Clients want a personFace-to-face contact is rated 4.3 and physical closeness 2.9 out of 5; caring for or serving people is 2.2 out of 5 in importance.
RegulationWorkers rate responsibility for others' health and safety 3.5 out of 5.
LicensingUsual entry requirement (BLS): bachelor's degree.
Physical work16% of the task time is physical; robots have been shown on 100% of that time.

What would it cost to hand the work to AI?

The share of the year AI could handle (360 of 2,080 hours a year), priced two ways. Both are ranges, not quotes.

AI model usage, a year
$40–$3,600
A person’s wage for the same hours
$11,770–$28,800

AI cost covers model usage only: no integration, licences, oversight or the human time still needed to review the work. Human cost is the wage for the same hours, without benefits or overheads. As of 2026-10.

Robots and humanoids

AI software can only take the work at a screen. The rest needs a robot that can do it.

16%
of the task time is physical work
Mobile robots
the kind of robot the physical work would need
Commercial in warehouses, hospitals and some outdoor sites; hands are still limited.

Source: Anthropic Economic Index, 'What work can robots do?' (30 September 2026); O*NET 31.0 task weights.

Which AI skills does this job lean on?

The job’s task time split by what an AI model would need to be good at, and where models stand today.

Each star is a task, grouped by the AI skill it leans on.Needs a human 83%AI helps 17%AI does it 0%
Writing · 9.7% of time
Strong
Drafts, edits and translates most routine documents at professional quality.
Analysis · 7.5% of time
Strong
Reliable on structured data and rules; uneven on judgement calls with thin information.
Coding · 6.8% of time
Strong
Agents complete many routine software tasks end to end; larger systems still need people.
Vision and design · 19.8% of time
Good
Reads documents, images and layouts well; specialist imaging needs dedicated, approved tools.
Speech · 8% of time
Good
Voice agents handle routine calls and live interpreting; complex or sensitive calls still go to people.
Planning and agents · 12.4% of time
Emerging
Multi-step agents work in narrow, well-tooled workflows; open-ended coordination is unreliable.
Physical manipulation · 15.8% of time
Early
Robots handle structured, repetitive handling; general dexterity outside fixed settings is not commercial.
Care and persuasion · 20% of time
Limited
Can script, coach and advise; trust, presence and accountability still need a person.
Amber matter holds its orbit, slate circles the inner disc, white falls in.Needs a human 83%AI helps 17%AI does it 0%
How exposed is it?

Still needs a human: 78/100↑ safer

The amber matter on the outside holds its orbit: that is the task time that still needs a person. The slate matter circling the inner disc is the work AI helps with. The white matter is the share AI can do; it spirals in and is gone over the edge.

The matter follows the job’s task split: 83% needs a human, 17% AI helps, 0% AI does it. Still needs a human: 78/100 ↑ safer. Will AI replace them? A little.

What the AIs say

We asked four AI assistants the same question: will AI replace this job in the next 10 years? One word (Yes, Partly or No), then one sentence. Our own answer, from the data: Still needs a human: 78/100 ↑ safer. Will AI replace them? A little.

ChatGPTPartly

AI will automate and augment many design, monitoring, and decision-support tasks, but agricultural engineers will still be needed for field implementation, systems integration, safety, and complex problem-solving.

gpt-5.5-2026-04-23 · asked 2026-10-03
ClaudeNo

AI will significantly augment agricultural engineers' capabilities through automation, predictive analytics, and precision tools, but the field's need for hands-on equipment design, on-site problem-solving, and adaptation to unpredictable environmental conditions will keep human engineers essential for the foreseeable future.

claude-sonnet-5 · asked 2026-10-03
GeminiPartly

While AI will automate routine tasks like data analysis, crop monitoring, and machinery operation, it cannot replace the complex on-site problem-solving, environmental adaptation, and hands-on system design performed by agricultural engineers.

gemini-3.8-flash · asked 2026-10-03
PerplexityPartly

AI will automate many routine analytical and design tasks, but agricultural engineers will remain necessary for field judgment, system integration, safety, and accountability.

sonar · asked 2026-10-03

Assistants answer from what they learned in training (Perplexity also searches the web), so they can be confidently wrong, and the same question can get a different answer tomorrow. Our score is built from task data and graded evidence. Answers collected through DataForSEO.

Cite this page

NeedsAHuman.com (2026). Will AI replace Agricultural Engineers? A little. Still needs a human: 78/100, higher is safer; release 2026-Q4. https://needsahuman.com/jobs/agricultural-engineers/ (accessed 4 October 2026).

Scores change with each , so cite the release. The data is open under : credit NeedsAHuman.com with a link. Open data · Press

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The badge updates itself with each release and links back to this page.

Sources

  • Tasks and work context: 31.0, ().
  • Jobs, pay and projections: US , and 2025–35.
  • How AI is used today: ; Microsoft Research, .
  • What AI can do: our task ratings ( r1) and the quality evidence register.
  • UK names and employment: coding index and .

How each score is built: methodology. Every figure on this page: open data. Release 2026-Q4.