Generative AI • June 29, 2024

Beyond Human Touch: AI’s Role in Evolving Contact Centers

Contact centers experienced a significant boom in the late '90s and early 2000s, thanks to the advent of internet connectivity and telephones. This evolution enabled 24/7 customer service, giving rise to offshore contact centers that could operate at a fraction of the cost, revolutionizing industries like banking, insurance, and telecommunications. Now, over two decades later, we stand at the brink of another transformative wave with the advent of Generative AI.

To understand how this change will unfold, it's essential to consider the daily experiences of different personas involved in contact centers.

The Agent Experience

Having worked with various BPOs, I recognize the challenges agents face in meeting their targets while keeping customers satisfied. Agents often juggle between 4 to 9 tools simultaneously. Their performance metrics include:

  • Average Handle Time (AHT): The average time spent on a customer call
  • Not Ready-Wrap Time: Post-call time for adding notes
  • Hold Time: Time spent putting a customer on hold to research a query
  • Customer Satisfaction (CSAT): A measure of the customer's overall satisfaction
  • Quality Scores: Assess if the right information was provided and protocols were followed
  • Schedule Adherence: The degree to which agents stick to their schedule, with even minor deviations impacting their monthly scores

These metrics can vary by process, but they highlight the demanding nature of an agent's role.

The Owner Experience

Contact center owners and management have their own set of key performance indicators (KPIs):

Service Level Agreements (SLAs) are formal agreements between business owners and service providers that define the expected service standards. These agreements specify metrics such as the number of calls handled daily, the number of customers in the queue awaiting service, and the agent headcount available at any given hour.

Compliance and Quality represent the average quality score of all agents at a specific site. Typically, this score ranges between 90% and 93%, reflecting the adherence to quality standards and customer satisfaction.

Site Adherence measures the percentage of time an agent is available to take or make calls. It is a critical indicator of workforce efficiency and service availability.

Attrition: High turnover is a significant challenge in the industry, leading to substantial financial losses. Attrition costs can range from $1.6 million to $4.8 million due to the time and expense involved in recruiting and training new agents.

The Current Customer Experience

Customer satisfaction is crucial for contact centers. Common issues include:

  • Long Wait Times: Over 44% of customers are dissatisfied with long wait times, which delay resolution and create negative sentiments
  • Repetition: More than 53% of customers find it frustrating to repeat their issues, often due to poor documentation and missing information
  • Personalization: Modern customers expect personalized interactions and seamless communication to feel valued and build lasting relationships

The Age of Generative AI in Contact Centers

Generative AI has the potential to transform the experiences of customers, agents, and owners:

Customer Experience:

  • Virtual Agents: Powered by Generative AI, virtual agents can provide instant in-context information on account balances, transaction details, claim statuses, and more, offering hyper-personalized and faster resolutions. This reduces the contact center's load by handling simpler queries automatically, allowing human agents to focus on complex problems
  • Natural Language Processing (NLP) and Predictive Flows: Enhanced self-service capabilities enable customers to resolve issues independently, improving satisfaction and reducing call volumes

Agent Experience:

  • Agent Knowledge Assist: AI can listen to live calls, suggest relevant articles from the database, and ensure the right resolution is provided quickly, reducing customer wait times, and enhancing the overall quality
  • Call Summarization: AI transcribes calls and captures relevant information, reducing the agent's post-call wrap-up time making themselves available for the next calls faster, thereby improving SLAs
  • Real-Time Assistance: AI can provide agents with real-time insights and guidance, making it easier to handle customer queries efficiently and accurately

Owner Experience:

  • Know Your Customers: AI identifies major call drivers and sentiment trends, ensuring adequate staffing during peak times and highlighting process issues
  • Intelligence and Analytics: AI analyzes user and agent sentiments, identifying repetitive callers and potential agent churn
  • Continuous Learning: Machine learning models continually learn from real-time data, reducing compliance risks and gaining insights, especially in sectors like fraud prevention and insurance.
  • Multimodal Support: Large Language Models (LLMs) can handle queries across chat, email, calls, social media, and more, ensuring customers don’t need to repeat themselves and context from previous conversations are captured and analyzed on-the-go

Shaping the Future of Contact Centers

The integration of Generative AI into contact centers is not just a step forward, it's a leap into a future where customer service is more efficient, personalized, and responsive. Here are some ways this technology will shape the future of contact centers:

Enhanced Personalization

Generative AI allows for a deeper understanding of customer preferences and behaviors. By analyzing past interactions and purchase histories, AI can tailor responses and recommendations to each individual. This level of personalization will foster stronger customer relationships and loyalty.

Predictive Analytics

AI-powered predictive analytics can forecast call volumes, identify peak times, and predict the types of inquiries that are likely to come in. This allows contact centers to optimize staffing levels, ensuring that they are neither understaffed nor overstaffed at any given time. Predictive analytics also help in anticipating customer needs, leading to proactive customer service.

Proactive Issue Resolution

AI can monitor and analyze data to detect potential issues before they become significant problems. For example, if a product defect is identified, AI can alert the contact center and initiate a customer outreach program to address the issue proactively. This reduces inbound call volumes and enhances customer satisfaction by addressing concerns before they escalate.

Cost Efficiency

By automating routine tasks and providing agents with real-time support, Generative AI significantly reduces operational costs. Contact centers can handle more inquiries without increasing headcount, and the efficiency gains lead to substantial cost savings. Additionally, the reduction in agent turnover due to improved job satisfaction further lowers costs related to recruitment and training.

Seamless Omnichannel Support

Generative AI enables seamless support across multiple channels - phone, email, chat, and social media. Customers can start an inquiry on one channel and continue it on another without repeating themselves. This omnichannel capability ensures a smooth and consistent customer experience, regardless of the platform they choose to use.

Continuous Improvement

AI systems are continually learning and improving from every interaction. This means that the quality of customer service will keep getting better over time. AI can identify gaps in knowledge, suggest training for agents, and update its own algorithms to provide more accurate and helpful responses.

Enhanced Data Security

With AI handling a significant portion of customer interactions, data security becomes even more critical. AI systems can be designed with robust security protocols to protect sensitive customer information. Additionally, by reducing the need to transfer data to third-party companies, organizations can better control and secure their data.

Improved Employee Experience

AI not only benefits customers but also enhances the agent experience. By automating mundane tasks and providing real-time assistance, AI allows agents to focus on more complex and rewarding aspects of their jobs. This leads to higher job satisfaction, reduced burnout, and lower attrition rates.


Transforming current contact centers with Generative AI will not only enhance customer experience but also enable banks and insurance companies to save millions by reducing the need to transfer data to third-party companies. This transformation provides clearer insights into product performance and identifies areas needing improvement.

Quantiphi, with over eleven years of award-winning expertise in AI-led digital transformation initiatives, offers a range of accelerators to modernize your entire contact center operations from start to finish. Get in touch to learn more about our capabilities and discover the power of Generative AI to reimagine your contact center.

Contact Us Today!

Written by

Aniruddha Pisharody

Senior Business Analyst

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