For telecoms operators, the contact center has long been the default channel for everything: billing queries, service activations, troubleshooting, complaints. The model works until it doesn't - and the point at which it stops working tends to arrive at the worst possible moment: during a surge, a service outage, or a period of rapid subscriber growth
The structural problem is that voice-based service does not scale gracefully: more calls mean more turnover. This is exactly where AI Agents change the equation: by absorbing the repetitive, high-volume requests, they free human agents to focus on the complex, high- value conversations where they make a real difference. For operators with hundreds of thousands or millions of subscribers, AI-assisted agents turn what was a business model constraint into a scalable operation.
Digital-first customer service changes the equation. When a well-built AI agent can handle three quarters of all inbound interactions autonomously, the contact center stops being a bottleneck and starts being a precision instrument, reserved for the cases that genuinely require human judgment, empathy, or access to systems the agent cannot reach. Thus, the human agents are doing more of what they are actually needed for.
The company's goals were to:
Before deploying the AI Agent, the telecom operator's contact center was receiving over one million voice calls per month. The digital channel - RingCentral for social and messaging - was handling over 100,000 interactions.
Managing this volume required around 800 part-time agents - a staffing strategy designed to maintain quality through rotation and fresh engagement. But the model carried significant overhead: annual turnover of around 70% meant onboarding 30 to 50 new agents every month, each needing a full month of training before handling calls independently.
At a certain point, it oversaturated:
The telecom operator deployed a Druid AI-powered customer agent, to transform how subscribers interact with the company across digital channels.
The deployment was intentionally phased: the A AgentI launched in late 2024 with extended knowledge base functionality and was systematically expanded over twelve months to version Laila 2.0 by adding transactional capabilities, additional language support, and deeper system integrations before the team was confident enough to actively redirect voice customers to the digital channel.
That patience proved decisive.
The solution includes several core capabilities:
Readiness before redirection
Asiacell spent twelve months building and tuning the AI Agent before actively redirecting voice customers to digital. By waiting until containment was genuinely high, the team ensured that when redirection started, customers stayed.
Redeployment multiplies the return on automation
When the AI Agent absorbed routine inbound volume, the telecom company redirected freed agent capacity into outbound revenue campaigns. The contact center gained a revenue-generating capability from the same team, turning efficiency into growth.
Speed of iteration is a competitive moat
Taking an idea from conversation to production in 24 to 48 hours becomes a strategic advantage. In telecoms, the operator that responds to customer needs fastest wins.
Quality earns adoption
Digital share grew from 12% to 43% because conversations felt human enough that customers completed transactions without noticing they were talking to an AI. Adoption grew organically, driven by the strength of the experience itself.