Answering written enquiries
Responding to inbound written questions from customers or the public.
Task automation exposure
Very high exposure
Exposure basis
[v3/median] score 85 (A 85 / B 95 / C 80, spread 15) Current LLMs with retrieval and fine‑tuning can answer most routine written customer queries accurately and professionally, though complex or nuanced cases may still need human escalation. (capable: GPT‑4o (large language model with retrieval‑augmented generation))
2 capabilities · 0 occupations
Basis
How exposure was assessed
[v3/median] score 85 (A 85 / B 95 / C 80, spread 15) Current LLMs with retrieval and fine‑tuning can answer most routine written customer queries accurately and professionally, though complex or nuanced cases may still need human escalation. (capable: GPT‑4o (large language model with retrieval‑augmented generation))
How much of this task's output current AI can produce or substantially assist.
Best current model strength on any capability this task requires.
This is an assessment of technical feasibility plus published evidence - not a forecast. Even fully automatable tasks are often not automated, because of cost, verification, liability, regulation or the fact that the task is bundled with other work.
Capabilities
AI capabilities involved
15 models tracked · strongest: GPT-5
3 models tracked · strongest: ElevenLabs v3 (alpha)
Occupations
Occupations that perform this task (0)
Importance is the O*NET-style weight of this task within each occupation. The same task can be highly exposed but peripheral to one job and core to another.
| Occupation | Industry | Importance | Role | Occupation AI exposure |
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Evidence
Evidence (0)
No evidence item is mapped to this specific task yet. The exposure figure above rests on the v1 editorial baseline and on the capability assessment, and should be treated as low-confidence. Pages with fewer than 0 evidence items are excluded from sitemaps.