Contact Centre Salespersons

← The GenAI exposure gradient

On the International Labour Organization's 2025 global study, the 8 task statements that define Contact Centre Salespersons (ISCO-08 5244) score an average of 0.61 on a 0–1 exposure scale — more exposed than about 98% of the 427 placed occupations. Roughly 100% of its tasks fall somewhere on the exposed part of the gradient, and the typical task lands in the Gradient 4 band.

Exposure is task overlap, not a verdict. A high score means a generative-AI model can do part of the content of these tasks — it says nothing about whether the work is automated, whether anyone uses AI for it today, or whether jobs are lost. The gradient is scored on the international ISCO-08 system; the rest of Singulariki is U.S. O*NET/SOC, bridged below by an approximate, many-to-many crosswalk.

How its tasks split across the gradient

Each of the 8 scored tasks for this occupation, sorted into the six exposure bands — cool (human ground) to hot (almost fully assistable).

The most-exposed task

“Arranging appointments for sales representatives;”

Scores 0.76 on the 2025 scale. Arranging appointments for sales representatives involves scheduling and managing calendars, tasks well-suited to automation by Generative AI. AI tools like calendar assistants can efficiently handle this through processing availability and coordinating dates and times, very similar to the task of "scheduling sales meetings," which received a high automation score of 0.775. Other semantically related tasks like "planning and coordinating medical insurance sales activities" and "accepting orders and managing the rental schedule" highlight the potential of AI in data-driven, routine tasks, with scores of 0.34 and 0.485, respectively. However, arranging appointments may still require some human oversight for personalized engagements and handling complex scheduling conflicts, which AI currently manages less efficiently. Given Poland's robust technological infrastructure, facilitating efficient AI deployment, and considering the high potential for automating structured scheduling tasks, a score of 0.775 reflects the significant automation capability while acknowledging the necessity of human involvement in outlier scenarios.

Moving fastest, 2023 → 2025

“Arranging processing and despatch of goods and services, information kits and brochures to customers;”

Model capability on this task changed by +0.16 in two years — the gradient is not static, it is filling in.

U.S. occupations this maps to

The American O*NET/SOC roles that crosswalk to ISCO-08 5244, biggest by employment first, via the published (approximate, many-to-many) IBS O*NET-SOC ↔ ISCO-08 correspondence. These are the closest U.S. matches — not an asserted one-to-one identity.

• Telemarketers

In context

Part of the 5 - Service and sales workers major group. Return to the full gradient to see how the whole group sits.

Contact Centre Salespersons sit at the 98th percentile of the global GenAI exposure gradient

• Across 427 international occupations scored by the ILO, Contact Centre Salespersons rank in the 98th percentile for GenAI task exposure — overlap with what generative AI can attempt, not a projection of displacement. (ILO / Gmyrek et al. (2025) GenAI exposure gradient)
• About 100% of this occupation's tasks fall into an exposed gradient band. (ILO / Gmyrek et al. (2025))
• Mean task exposure fell by 0.08 between the 2023 and 2025 model-capability snapshots. (ILO / Gmyrek et al. (2025), 2023→2025)
• Its most-exposed task: "Arranging appointments for sales representatives;". (ILO / Gmyrek et al. (2025))

Source: Singulariki — "Contact Centre Salespersons". https://singulariki.com/gradient/5244-contact-centre-salespersons.html
Note: AI task overlap measures what today's AI can attempt, not automation, job loss, or a forecast.