Network field technicians (fibre, mobile)
ISCO-08 7422, 7413Fibre installation technician, FTTH connection technician, Mobile site maintenance technician, Network field technician, Fibre splicing technician
Headcount need, in FTE
Target AI skills
level 1 to 4Job skills
Growing in value
- Diagnosis of complex and intermittent faults
- Customer relationship during home visits
- Quality of photos and as-built data
- Using diagnostic assistants on site
Losing value
- Writing intervention reports by hand
- Searching technical documentation on site
- Paper-based as-built drawings
How the job will change
AI does not climb masts or splice fibre. What it changes is the work around the intervention: dispatch and routing optimised by planning tools, reports dictated or generated from photos, automatic checks of connection quality from a picture of the termination box, and an assistant that suggests the probable cause of a fault before the technician arrives.
The core of the job stays manual, on site and in front of the customer. A good technician tomorrow documents carefully, because photo and data quality now feed automated controls, and takes on the harder faults that remote diagnosis could not solve. Experience of the field and safety at height or near power lines keep all their value.
- 2026-2027
- Dictated reports and automatic photo checks of connections.
- 2028-2030
- Remote diagnosis filters simple faults; predictive maintenance trims some preventive visits.
- 2031+
- Fewer unnecessary truck rolls, technicians focused on complex repairs.
The main risk is an ageing population of experienced technicians and a tight recruitment market, while fibre maintenance and copper switch-off keep field demand high. See the seniority outlook below.
What if you hired fewer juniors?
Your 2036 seniors are the juniors you hire today.
Advanced settings modified
2026 2036
The AI Cookbook 2026
albert's guide to cut through the noise around generative AI and turn it into workforce decisions.
- What AI actually changes in jobs and skills
- Why the junior pipeline matters more than most companies realise
- How to integrate AI into workforce planning

Run these scenarios on your actual workforce
AI Impact Diagnostic: 6 to 8 weeks, your data in albert, three costed scenarios and the projected seniority mix for each job family.
How the numbers are built
Every headcount figure combines four assumptions. Three come pre-filled from public research and job family defaults. The strategic ceiling is yours to set.
Seniority outlook
A flow model with three levels of experience in the profession. Promotion and exit rates are set so that today's mix stays stable when hiring does not change: any gap you see comes from the junior hiring cut alone.
Sources
- International Labour OrganizationGenerative AI and jobs: a refined global index of occupational exposure (2025)
- ILO datasetTask-level GenAI exposure scores by ISCO-08 occupation
- AnthropicAnthropic Economic Index (June 2026 release, April and May 2026 usage data)
- Stanford Digital Economy LabCanaries in the Coal Mine? Six facts about the recent employment effects of AI