Delivery truck drivers and driver/sales workers: AI exposure and career outlook
Delivery truck drivers and driver/sales workers (SOC 53-3033) sit at the 23rd percentile for measured AI exposure among the 342 occupations tracked here, measured from a composite of Microsoft Research and Anthropic Economic Index telemetry. An estimated 12% of tasks are already automated and 28% are being reshaped rather than replaced — both modelled figures, not direct measurements. Insulated group: little measured AI exposure so far. No urgency here, though the tools are still worth having in your hands. In Canada the role maps to NOC 75201 (Delivery service drivers and door-to-door distributors), and ESDC's COPS 2024–2033 outlook for that unit group is balance.
Figures last updated 2026-06. Every number on this page is labelled measured or modelled; where a source has no coverage for this occupation, it says so rather than showing a zero.
Key facts
- SOC code
- 53-3033
- Canada NOC 2021
- 75201
- TEER level
- Not available
- COPS outlook
- Balance
What the measurements actually say
Three independent studies measure AI exposure for this occupation directly. The two percentages below them are ours, modelled from those measurements.
| Metric | Value | Provenance |
|---|---|---|
| AI applicability | 12% | Measured — Microsoft Research, from 200,000 Copilot conversations classified against O*NET work activities. |
| Observed AI usage | 0% | Measured — Anthropic Economic Index, share of tasks observed being performed with Claude (CC-BY 4.0). |
| Academic AI exposure | 15th percentile | Measured — Felten-Raj-Seamans AIOE index across 774 occupations; the index underlying Statistics Canada's Canadian estimates. |
| Automation-pattern usage | Not available | Not covered by Anthropic's collaboration-mode dataset. |
| Augmentation-pattern usage | Not available | Not covered by Anthropic's collaboration-mode dataset. |
| Estimated task automation (modelled) | 12% | Modelled from this occupation's measured telemetry composite, mapped through anchors calibrated to Anthropic's published aggregate findings. Our estimate, not per-occupation telemetry. |
| Estimated task reshaping (modelled) | 28% | Share of tasks where AI acts as co-pilot rather than replacement. Modelled from the measured telemetry composite, calibrated to BCG's published aggregate reshaping rates. Our estimate. |
This skill domain has minimal AI substitution risk. AI is primarily augmenting — not replacing — professionals here.
In Canada: NOC 75201
Delivery truck drivers and driver/sales workers map to NOC 75201 — Delivery service drivers and door-to-door distributors. ESDC's COPS 2024–2033 projection for this unit group is Balance.
Mapped via Statistics Canada's official SOC 2018 → NOC 2016 → NOC 2021 correspondence tables (closest match of several correspondence candidates). TEER is the second digit of the NOC code, so it is only as certain as the code is. Several correspondence candidates were available here and we took the closest by title, so we do not report a TEER level for it.
What this job actually involves
These are the O*NET task statements for Delivery truck drivers and driver/sales workers— the work itself, as reported by people doing the job — grouped by the work activity each task belongs to. Showing 12 of 13, core tasks first.
The exposure figures above are for the occupation as a whole. We do not have a per-task measurement: no published dataset tells us which of these specific tasks AI is doing. Read this as what the job is made of, not as a ranking of what is at risk.
Microsoft's applicability score was itself produced by classifying Copilot conversations against the O*NET work-activity catalogue — the same catalogue these groups come from. The published file gives one number per occupation, not one per activity, so we can tell you that 12% of this occupation's work activities are covered by observed AI usage, but not which ones.
Operating Vehicles, Mechanized Devices, or Equipment · 2 tasks
Obey traffic laws and follow established traffic and transportation procedures.
Core task · Importance 4.8/5 (O*NET)
Drive vehicles with capacities under three tons to transport materials to and from specified destinations, such as railroad stations, plants, residences, offices, or within industrial yards.
Core task · Importance 4.0/5 (O*NET)
Communicating with Supervisors, Peers, or Subordinates · 2 tasks
Report any mechanical problems encountered with vehicles.
Core task · Importance 4.8/5 (O*NET)
Report delays, accidents, or other traffic and transportation situations to bases or other vehicles, using telephones or mobile two-way radios.
Supplemental task · Importance 3.7/5 (O*NET)
Getting Information · 1 task
Read maps and follow written or verbal geographic directions.
Core task · Importance 4.7/5 (O*NET)
Inspecting Equipment, Structures, or Materials · 1 task
Inspect and maintain vehicle supplies and equipment, such as gas, oil, water, tires, lights, or brakes, to ensure that vehicles are in proper working condition.
Core task · Importance 4.7/5 (O*NET)
Processing Information · 1 task
Verify the contents of inventory loads against shipping papers.
Core task · Importance 4.8/5 (O*NET)
Performing General Physical Activities · 1 task
Load and unload trucks, vans, or automobiles.
Core task · Importance 4.6/5 (O*NET)
Repairing and Maintaining Electronic Equipment · 1 task
Use and maintain the tools or equipment found on commercial vehicles, such as weighing or measuring devices.
Supplemental task · Importance 4.0/5 (O*NET)
Documenting/Recording Information · 1 task
Maintain records, such as vehicle logs, records of cargo, or billing statements, in accordance with regulations.
Core task · Importance 4.4/5 (O*NET)
Performing Administrative Activities · 1 task
Turn in receipts and money received from deliveries.
Supplemental task · Importance 4.7/5 (O*NET)
Monitoring and Controlling Resources · 1 task
Present bills and receipts and collect payments for goods delivered or loaded.
Core task · Importance 4.5/5 (O*NET)
Task statements and work activities from the O*NET Database by the U.S. Department of Labor, Employment and Training Administration (USDOL/ETA), used under CC BY 4.0. O*NET® is a trademark of USDOL/ETA. USDOL/ETA has not reviewed or approved this material.
That's the average. Is this you?
Everything above describes Delivery truck drivers and driver/sales workers as a whole. Three questions, and nothing is stored or sent.
Where are you in your career?
What does your week mostly look like?
Is your employer deploying AI?
Where the leverage is
With low AI exposure, the focus for this role is on adopting productivity tools. Leverage AI for scheduling, administrative tasks, and analytics to double operational throughput.
Physical requirements and manual dexterity provide strong natural insulation from AI substitution. AI is primarily a peripheral tool for diagnostics.
Obtain technical certifications in advanced diagnostic tools and smart systems relevant to delivery truck drivers and driver/sales workers to prepare for future technological integrations.
This guidance is written per exposure band — three texts across all 342 occupations, framed on the ILO's transformation-versus-displacement distinction. It is editorial guidance for the safe band, not an occupation-specific research finding about delivery truck drivers and driver/sales workers.
Sources for this occupation
Only the sources that hold data for delivery truck drivers and driver/sales workers are listed. A study that does not cover this occupation is not cited here.
- Microsoft Research — Working with AI (Tomlinson et al., arXiv:2507.07935): Measured AI applicability, from 200,000 anonymised Copilot conversations classified against O*NET work activities.
- Anthropic Economic Index: Measured observed AI usage per occupation, from Anthropic's open per-SOC dataset (CC-BY 4.0).
- Felten, Raj & Seamans — AI Occupational Exposure index: Measured academic exposure percentile; the index underlying Statistics Canada's Canadian AI-exposure estimates (Mehdi & Morissette, 2024).
- O*NET Database 31.0 (USDOL/ETA), CC BY 4.0: The occupation's task statements and work activities, verbatim. Joined on SOC 2018 with no crosswalk — O*NET-SOC is built on SOC — and carrying no claim about which tasks AI touches.
- Statistics Canada NOC 2021 concordance: Official SOC 2018 → NOC 2016 V1.3 → NOC 2021 V1.0 correspondence tables. TEER is the second digit of the resolved code, so we report it only where the concordance gave a single candidate.
- ESDC COPS 2024–2033: Projected labour-market assessment per NOC 2021 unit group, from the Canadian Occupational Projection System open dataset.
- BCG — AI Will Reshape More Jobs Than It Replaces (April 3, 2026): Published aggregate reshaping rates, used to calibrate our modelled percentages. The per-occupation figures here are our estimates, not BCG's data.
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