Overview

A global Energy & Utility Enterprise required transforming end-user support to meet growing digital expectations and support demand. Operational inefficiency and heavy reliance on voice-based support impacted user experience dramatically.

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A global Energy & Utility Enterprise required transforming end-user support to meet growing digital expectations and support demand. Operational inefficiency and heavy reliance on voice-based support impacted user experience dramatically.

Tech Mahindra designed and deployed a scalable self-service model powered by AI, analytics, and intelligent automation. As a result, the enterprise was able to shift from a reactive support model to a proactive, digital-first operating model.

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Industry Challenge

A global energy and utility infrastructure supporting distribution of gas, oil, and renewable energy was dealing with a dispersed workforce and major dependency on voice support for end users. Further with over 25,000 monthly contacts, fragmented support channels, lack of automation, and limited multilingual capabilities, there was an increasing pressure to improve end-user experience.

Our Approach and Solution

We deployed a future-ready agentless service desk by leveraging AI, analytics, intelligent automation, and knowledge engineering.

Digital Self-Service

Self-service and digital assistant ecosystem to reduce dependency on voice support

AI-Powered Multilingual Conversational Support

Multilingual conversational assistants to handle high-volume use cases

Intelligent Service Desk Automation

Incident logging, categorization, routing, and resolution to accelerate ticket fulfilment

Agentic AI

Use of agentic AI to improve accuracy of self-service responses

Digital Experience Monitoring

End-user experience monitoring to identify and resolve potential issues proactively

Continuous Optimization

Continuous improvement framework to identify automation opportunities

Business and Community Impact

  • 98%+ improvement in end-user experience score
  • 65%+ digitalisation of support interactions
  • 54% reduction in end-user downtime
  • 70% reduction in business escalations
  • 56% support tickets eliminated
  • <10% voice support dependency