Level AI introduces AI Workers designed to automate coaching, analytics, QA, and research workflows across enterprise contact centre operations.
Level AI has launched AI Workers, a suite of purpose-built AI agents designed to automate operational workflows across enterprise contact centre environments.
The new AI Workers are designed to support customer-centric teams, including coaches, analysts, QA leaders, and CX executives, by automating research, analysis, coaching, and planning tasks traditionally handled manually.
According to Level AI, nearly 100 enterprise contact centres are already using AI Workers, with more than 25,000 worker runs executed across operational environments.
The company stated that many enterprise AI investments within customer experience have historically focused on front-office automation such as chatbots, IVR systems, and self-service channels, while operational CX teams continue to rely heavily on manual workflows.
Level AI positions AI Workers as operational AI systems designed to move beyond summarisation and support end-to-end workflow execution across customer experience operations.
“Every AI tool CX operations has been given stops at summarisation. The actual workflow, from insight to coaching plan to quality improvement, still runs on manual effort,” said Ashish Nagar, Chief Executive Officer and Co-Founder, Level AI.
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AI Workers for Contact Centre Operations
Each AI Worker is designed around a specific operational role and produces structured outputs connected to existing customer intelligence systems.
The launch includes several specialised AI Workers, including:
- Coaching Plan Worker: Reviews customer interactions and generates structured coaching briefs with recommended focus areas and interaction examples.
- Conversation Research Worker: Searches transcripts semantically and produces thematic customer research reports.
- Executive Research Worker: Conducts multi-step investigations across operational data and generates cited analytical reports.
- Additional Workers: Include Conversation Analytics, Team Performance, Product Feedback, Resolution Insights, Sentiment Insights, iCSAT Insights, and Voice of Customer (VoC) capabilities.
According to the company, each worker operates on the same structured customer intelligence layer already used by QA and analytics teams, eliminating the need for parallel data systems or additional reconciliation workflows.
Shared Intelligence and Multi-Agent Orchestration
Level AI stated that AI Workers operate through a shared intelligence layer combining:
- Customer conversations and transcripts
- QA frameworks
- CRM data
- Team hierarchy information
- AI-enriched signals, including sentiment, effort, resolution outcomes, and VoC themes
The platform also includes a dual retrieval system that combines transcript search with structured data queries in a single workflow.
According to Level AI, a multi-agent orchestration layer breaks down complex operational requests into parallel subtasks while maintaining traceability back to source data.
Operational Impact Across CX Teams
Level AI stated that AI Workers are designed to help enterprise contact centres improve operational efficiency, accelerate coaching and analytics workflows, and reduce manual workload across customer experience teams.
An enterprise benefits administration company participating in the beta programme reported that AI Workers improved visibility into operational performance and coaching opportunities through prompt-based access to customer intelligence data.
“Contact centers ran out of headcount strategies years ago. Enterprise software is shifting from a system of record to a system of action. A copilot doubles a person’s throughput at best. A worker creates a new line on the org chart,” said Nagar.
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