UK AI Exposure · Sales and customer service occupations
Customer service occupations n.e.c.
Job holders in this unit group perform a variety of customer service occupations not elsewhere classified in minor group 721: Customer service occupations.
- Employees (UK)
- 299k
- Median annual pay
- £24,438
- Exposure score ?
- 5.8/10 Moderate direct 5.8 · with tools 9.2
- Wage exposure
- £4.24bn
Higher exposure than 97% of the 379 UK occupations we scored.
What this score means
A meaningful slice of the task inventory is AI-reachable - the drafting, summarising, research and analysis parts especially. This role is at the point where the people who learn to direct AI well pull ahead of the people who don't.
If you're in this role, here's what to do now
Treat AI as a colleague you manage, not a tool you use. Identify the tasks where you'd describe the work to a capable junior - those are the tasks AI can do for you now. Spend your time on the judgment calls and the relationships instead.
The tasks in this role, ranked by AI exposure
Below are the real tasks O*NET records for this occupation, sorted highest exposure first. "AI can do this" means a language model can already handle the task directly. "AI can help" means an LLM can assist but not replace. "Human work" means today's AI doesn't touch it. Importance is O*NET's 1–5 rating of how central each task is to the role.
4 of 18 tasks in this role are things an AI can already do today. Task list mapped via O*NET "Receptionists and Information Clerks" (43-4171.00).
Analyze data to determine answers to questions from customers or members of the public.
Calculate and quote rates for tours, stocks, insurance policies, or other products or services.
Perform administrative support tasks, such as proofreading, transcribing handwritten information, or operating calculators or computers to work with pay records, invoices, balance sheets, or other documents.
Process and prepare memos, correspondence, travel vouchers, or other documents.
Operate telephone switchboard to answer, screen, or forward calls, providing information, taking messages, or scheduling appointments.
Greet persons entering establishment, determine nature and purpose of visit, and direct or escort them to specific destinations.
Receive payment and record receipts for services.
Schedule appointments and maintain and update appointment calendars.
Transmit information or documents to customers, using computer, mail, or facsimile machine.
Hear and resolve complaints from customers or the public.
File and maintain records.
Provide information about establishment, such as location of departments or offices, employees within the organization, or services provided.
Collect, sort, distribute, or prepare mail, messages, or courier deliveries.
Keep a current record of staff members' whereabouts and availability.
Schedule space or equipment for special programs and prepare lists of participants.
Perform duties, such as taking care of plants or straightening magazines to maintain lobby or reception area.
Enroll individuals to participate in programs and notify them of their acceptance.
Take orders for merchandise or materials and send them to the proper departments to be filled.
Where a project with Alex usually starts for this role
These are the highest-importance tasks in this role that a language model can already handle directly. In a typical engagement the first wins come from building workflows around these, so they stop eating your team's time.
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Analyze data to determine answers to questions from customers or members of the public.
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Calculate and quote rates for tours, stocks, insurance policies, or other products or services.
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Perform administrative support tasks, such as proofreading, transcribing handwritten information, or operating calculators or computers to work with pay records, invoices, balance sheets, or other documents.
Every role has three or four wedges like these. Finding them takes an hour. Turning them into a workflow your team actually uses takes a few days. Talk to Alex about a project →
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Methodology
This role's exposure score comes from Eloundou et al's 2023 GPT task labels, aggregated by O*NET importance within each O*NET-SOC code, then bridged to UK SOC 2020 via ISCO-08 (ONS Vol 2 coding index) and US SOC 2010 (BLS crosswalk). Employment and median pay come from ONS ASHE Table 14.7a, 2025 provisional. ASHE covers employees only, so self-employed workers are not counted.
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