Energy and Utility companies depend heavily on their contact centers to support customers with billing, service requests, outages, and technical issues. However, contact center operations continue to face major challenges, especially in hiring and retaining skilled agents.
Training new agents is costly and time‑consuming. In many organizations, it takes five months or more for an agent to become fully productive. Most companies still use classroom or virtual training programs that do not keep up with rapid changes in technology, regulations, and customer expectations.
At the same time, solution providers are investing heavily in AI and Generative AI (GenAI) to bring new capabilities to contact centers. These tools help identify customer intent, detect sentiment, analyze agent behavior, and generate call summaries, now a standard feature in modern solutions.
Â
How GenAI Supports Live Agents
GenAI tools are being widely used to automate common customer inquiries. When customers speak with a live agent, AI systems convert speech to text and instantly search the knowledgebase to recommend the right response. AI can also pull customer‑specific details such as payment history, service address, or outage status from backend systems and present them to the agent in real time.
In Energy & Utility environments, typical customer intents include:
Checking account balance
Paying bills
Enrolling in payment plans
Starting or stopping services
Understanding available products and programs
Most of these requests can be resolved by automated agents without needing a live representative. However, analytics consistently show that customers still choose to speak with live agents. This behavior increases call volume and puts pressure on the contact center.
Â
Why Customers Still Request Live Agents
There are several reasons customers bypass digital channels and automation:
They may not be using available digital tools such as mobile apps, chatbots, or web portals.
Automated menu options can be confusing or difficult to navigate.
Call flows may be poorly designed, leading customers to agents by default.
Customers often seek reassurance from a human when dealing with billing issues or service disruptions.
Regardless of the reason, the result is the same: higher call volumes and operational strain.
This directly affects key contact center KPIs, including:
Abandon Rate – number of calls disconnected before speaking with an agent.
Average Handle Time (AHT) – how long agents spend on each call; important for staffing and forecasting.
Customer Satisfaction (CSAT) – how customers rate their experience after the interaction.
Average Speed of Answer (ASA) – how quickly calls are connected; closely related to abandon rates.
Â
Limitations in Current Training and Testing Environments
Many Energy & Utility companies struggle to predict customer behavior during testing. Training environments often lack:
A complete knowledgebase covering all customer questions
Tools to validate whether agents are fully prepared
Realistic simulation of customer scenarios
Automated ways to test if call flows work as expected
This results in gaps between what agents learn during training and what they experience in real customer interactions.
Â
How GenAI Improves Knowledgebases and Testing
Solution providers now offer AI‑powered digital assistants, GenAI‑based search tools for agents, and voice‑enabled knowledgebase search. While these tools improve response accuracy, they still rely heavily on the quality of the underlying knowledgebase.
This is where GenAI-based customer simulators bring transformative value.
GenAI Customer Simulators
A GenAI customer simulator can:
Generate realistic customer conversations
Predict customer scenarios across all service types
Continuously learn from SMEs, call transcripts, customer feedback, and historical interactions
Create training materials and improve the knowledgebase
Provide agents with practical, scenario-based training
These simulators behave like real customers and can cover thousands of scenarios, including outages, billing disputes, payment challenges, and service issues.
Â
Operational Benefits for Energy & Utility Companies
By using GenAI Customer simulators and knowledge tools, companies can:
Test contact center solutions more accurately
Measure KPIs in simulated environments
Improve call flows before going live
Build richer, more complete knowledgebases
Better prepare agents for real customer needs
These simulators can also be integrated into production environment to monitor and improve agent performance in real time.