Hr onboarding · Production

TELUS Digital cuts onboarding time by 20% using ElevenLabs Agents

The problem

TELUS Digital manages 70,000 contact center associates with 20,000 to 30,000 new hires per year, but ramp-up takes weeks and attrition rates often reach 30–45%. Traditional training methods — classroom sessions, shadowing, and occasional roleplay — did not scale and failed to reflect real-world scenarios, leaving agents underprepared for live environments.

First attempt

Traditional training methods — classroom sessions, shadowing, and occasional roleplay — did not scale and lacked realism, resulting in agents entering live environments underprepared with low confidence and causing frequent escalations.

Workflow diagram · grounded in source
1
Agent initiates practice session
Trigger
Agents practice everything from simple inquiries to complex complaints in a safe, repeatable environment.
▾ source quote
“enabling agents to practice everything from simple inquiries to complex complaints in a safe, repeatable environment”
2
Agent Trainer generates simulations
Ai action
Agent Trainer generates dynamic, lifelike simulations across voice and chat.
▾ source quote
“It generates dynamic, lifelike simulations across voice and chat”
3
ElevenLabs Agents deliver voice interaction
Ai action
ElevenLabs Agents deliver natural, low-latency voice interactions that sound and behave like real customers.
▾ source quote
“ElevenLabs Agents deliver natural, low-latency voice interactions that sound and behave like real customers. These simulations adapt in real time, and support multilingual scenarios, helping agents build both skill and confidence faster”
4
Manager reviews performance reports
Output
Managers receive detailed performance reports to identify and address skill gaps.
▾ source quote
“Managers receive detailed performance reports to identify and address skill gaps”
Reported outcome

TELUS Digital reduced onboarding time by 20% and the platform completed more than 50,000 customer simulations, with improved agent confidence showing early signs of lowering churn.

Reported metrics
Onboarding time reduction20%
Customer simulations completedmore than 50,000
Contact center associates70,000
New hires per year20,000 to 30,000
Show all 6 reported metrics
onboarding time reduction20%
customer simulations completedmore than 50,000
contact center associates70,000
new hires per year20,000 to 30,000
contact center attrition rate30–45%
agent churnearly signs of lowering churn
Reported stack
ElevenLabs AgentsElevenLabs Text to SpeechAgent Trainer
◆ Does this fit your context?

Compare to your context

Tell us your scale, team, and constraints. We'll show what changes at your size, what fails at your scale, and whether this case is a fit, needs adaptation, or won't scale to you. Free demo, no signup.

Compare to your context →
~30 seconds · free
Source
https://elevenlabs.io/blog/fuel-ix-telus-digital
Read source ↗

Frequently asked questions

What did this team achieve with this AI workflow?

TELUS Digital reduced onboarding time by 20% and the platform completed more than 50,000 customer simulations, with improved agent confidence showing early signs of lowering churn.

What tools did this team use?

ElevenLabs Agents, ElevenLabs Text to Speech, Agent Trainer.

What results were reported?

Onboarding time reduction: 20%; Customer simulations completed: more than 50,000; Contact center associates: 70,000; New hires per year: 20,000 to 30,000 (source-reported, not independently verified).

What failed first in this deployment?

Traditional training methods — classroom sessions, shadowing, and occasional roleplay — did not scale and lacked realism, resulting in agents entering live environments underprepared with low confidence and causing fr…

How is this hr onboarding AI workflow structured?

Agent initiates practice session → Agent Trainer generates simulations → ElevenLabs Agents deliver voice interaction → Manager reviews performance reports.

Related hr onboarding cases

WHAT TO DO WITH THIS

Now compare it to your context

This case is one data point. Whether its pattern fits you depends on your volumes, your stack, and your exception load — that comparison is the step no case study can do for you.

Browse the Hr onboarding cases →