09/03/2024 | Press release | Distributed by Public on 09/03/2024 01:13
\r\nSeptember 03, 2024
September 03, 2024
Our research shows generative AI won't replace service agents -but will, rather, make them more effective.
\r\n"}}" id="text-2a36675fb9" class="cmp-text">Our research shows generative AI won't replace service agents -but will, rather, make them more effective.
As generative AI takes hold, there's a great deal of curiosity and unease about the future of work. Amid some dire predictions, it's been assumed by many that some professions will be hit hard, largely replaced by chatbots and other AI programs.
\r\nCustomer service representatives (CSRs), including call center professionals, are among those who've been warned to watch their backs. Businesses have long sought to automate customer service, and at first glance, gen AI appears to have the potential to take this to the next level.
\r\nOur New work, new world research finds CSRs are likely to be significantly impacted by generative AI. According to our calculations, these workers today have an exposure score of 11% (meaning the percentage of the job's tasks that could be automated or augmented by gen AI. By 2032, that number could leap to 64%.
\r\n"}}" id="text-d62d460f58" class="cmp-text">As generative AI takes hold, there's a great deal of curiosity and unease about the future of work. Amid some dire predictions, it's been assumed by many that some professions will be hit hard, largely replaced by chatbots and other AI programs.
Customer service representatives (CSRs), including call center professionals, are among those who've been warned to watch their backs. Businesses have long sought to automate customer service, and at first glance, gen AI appears to have the potential to take this to the next level.
Our New work, new world research finds CSRs are likely to be significantly impacted by generative AI. According to our calculations, these workers today have an exposure score of 11% (meaning the percentage of the job's tasks that could be automated or augmented by gen AI. By 2032, that number could leap to 64%.
But contrary to popular opinion, we don't think gen AI will make customer service representatives extinct-not by a longshot. Instead, the technology is poised to supercharge service delivery, in part by empowering junior customer service representatives to act like senior ones.
\r\n"}}">But contrary to popular opinion, we don't think gen AI will make customer service representatives extinct-not by a longshot. Instead, the technology is poised to supercharge service delivery, in part by empowering junior customer service representatives to act like senior ones.
\r\nIn the future, we don't think there will be fewer customer service representatives. In fact, our research indicates you may see more-and they'll all be upleveled by gen AI.
Based on both our own analysis and additional research examining how customer service is set to change, we believe gen AI will supercharge reps in the following ways:
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1. Enhanced personalization. Gen AI will allow customer service representatives to offer highly personalized assistance by analyzing vast amounts of data-far more than any human could. CSRs will be able to tailor their support more effectively.
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\r\nThis could involve, for example, recommending specific products or services that align with a customer's needs and financial situation. The idea may not be revolutionary-what's exciting is the sheer number of data points that AI-infused systems can factor in.
2. Predictive support. AI-driven algorithms will anticipate customer inquiries and issues before they arise, allowing reps to proactively address concerns. By leveraging predictive analytics, customer service representatives can anticipate customer needs. This proactive approach will enhance customer satisfaction and deliver support before an issue gets escalated.
\r\n3. Intelligent and automated documentation. Through natural language processing capabilities, AI systems can automatically transcribe and summarize conversations between reps and customers. This not only saves time but also ensures accurate record-keeping, which is essential for compliance and resolving disputes.
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Working with a leading healthcare payer, we've created a system that-among other capabilities-summarizes call notes and triggers automated responses. The intelligent call summarization provides myriad benefits to the client, including a 15% to 20% reduction in both training time and how long it takes customer service representative to attain proficiency. This is a prime example of the customer service future, with junior reps quickly reaching similar service levels as senior reps.
\r\n
In the future, we don't think there will be fewer customer service representatives. In fact, our research indicates you may see more-and they'll all be upleveled by gen AI.
Based on both our own analysis and additional research examining how customer service is set to change, we believe gen AI will supercharge reps in the following ways:
1. Enhanced personalization. Gen AI will allow customer service representatives to offer highly personalized assistance by analyzing vast amounts of data-far more than any human could. CSRs will be able to tailor their support more effectively.
This could involve, for example, recommending specific products or services that align with a customer's needs and financial situation. The idea may not be revolutionary-what's exciting is the sheer number of data points that AI-infused systems can factor in.
2. Predictive support. AI-driven algorithms will anticipate customer inquiries and issues before they arise, allowing reps to proactively address concerns. By leveraging predictive analytics, customer service representatives can anticipate customer needs. This proactive approach will enhance customer satisfaction and deliver support before an issue gets escalated.
3. Intelligent and automated documentation. Through natural language processing capabilities, AI systems can automatically transcribe and summarize conversations between reps and customers. This not only saves time but also ensures accurate record-keeping, which is essential for compliance and resolving disputes.
Working with a leading healthcare payer, we've created a system that-among other capabilities-summarizes call notes and triggers automated responses. The intelligent call summarization provides myriad benefits to the client, including a 15% to 20% reduction in both training time and how long it takes customer service representative to attain proficiency. This is a prime example of the customer service future, with junior reps quickly reaching similar service levels as senior reps.
\r\n 4. Automated handling of routine inquiries. In addition to providing round-the-clock support, complementing the efforts of human reps, virtual agents can handle routine inquiries, freeing up humans to focus on more complex issues that require empathy and critical thinking. This expanded and upleveled availability improves access to prompt service and enhances overall service levels.
For a global client in the technology sector, we've developed a system that manages conversations between customers and customer service representatives and handles standard queries on its own. For complex and critical calls, the agent takes over the conversation. Early results show an impressive 50% improvement in call center efficiency.
\r\n5. Personalized training. Over time, gen AI systems will learn from customer interactions and feedback, enabling continuous improvement in service delivery. By analyzing patterns in inquiries, sentiment and resolution outcomes, AI algorithms can identify areas for optimization and suggest training topics for human reps. This iterative process ensures that the business's customer service function remains responsive to evolving needs and market dynamics.
\r\n6. More focused time with customers. AI technologies will empower human reps to leverage their expertise more effectively. With AI handling repetitive queries and basic transactions, CSRs can focus on building deeper relationships with customers.
\r\nWe worked with a leading airline to build a booking automation solution. The system provides real-time conversation assistance to CSRs working with customers to modify reservations-often a fraught, emotional process for consumers. The solution has brought about a 20% reduction in average handling time, as well as noteworthy improvements in customer experience and accuracy of resolution.
\r\n7. Sentiment analysis and emotional intelligence: Gen AI can analyze customer sentiments based on interactions, helping CSRs tailor their responses accordingly. By understanding emotional cues, CSRs can provide empathetic and compassionate support, enhancing overall customer satisfaction.
\r\n8. Multilingual support: Gen AI can assist with language translation, enabling CSRs to communicate effectively with a diverse customer base. Whether it's chatbots handling initial queries or AI-powered language tools, multilingual capabilities improve accessibility.
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Will generative AI have a powerful impact on the field of customer service? Absolutely. Will it do so by replacing people with software on a grand scale? Absolutely not. Understanding this, forward-looking businesses must proactively use the technology to boost customer service representatives' capabilities. Used properly, gen AI will supercharge human customer service representatives, empowering them to perform deeper, relationship-building work.
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4. Automated handling of routine inquiries. In addition to providing round-the-clock support, complementing the efforts of human reps, virtual agents can handle routine inquiries, freeing up humans to focus on more complex issues that require empathy and critical thinking. This expanded and upleveled availability improves access to prompt service and enhances overall service levels.
For a global client in the technology sector, we've developed a system that manages conversations between customers and customer service representatives and handles standard queries on its own. For complex and critical calls, the agent takes over the conversation. Early results show an impressive 50% improvement in call center efficiency.
5. Personalized training. Over time, gen AI systems will learn from customer interactions and feedback, enabling continuous improvement in service delivery. By analyzing patterns in inquiries, sentiment and resolution outcomes, AI algorithms can identify areas for optimization and suggest training topics for human reps. This iterative process ensures that the business's customer service function remains responsive to evolving needs and market dynamics.
6. More focused time with customers. AI technologies will empower human reps to leverage their expertise more effectively. With AI handling repetitive queries and basic transactions, CSRs can focus on building deeper relationships with customers.
We worked with a leading airline to build a booking automation solution. The system provides real-time conversation assistance to CSRs working with customers to modify reservations-often a fraught, emotional process for consumers. The solution has brought about a 20% reduction in average handling time, as well as noteworthy improvements in customer experience and accuracy of resolution.
7. Sentiment analysis and emotional intelligence: Gen AI can analyze customer sentiments based on interactions, helping CSRs tailor their responses accordingly. By understanding emotional cues, CSRs can provide empathetic and compassionate support, enhancing overall customer satisfaction.
8. Multilingual support: Gen AI can assist with language translation, enabling CSRs to communicate effectively with a diverse customer base. Whether it's chatbots handling initial queries or AI-powered language tools, multilingual capabilities improve accessibility.
Will generative AI have a powerful impact on the field of customer service? Absolutely. Will it do so by replacing people with software on a grand scale? Absolutely not. Understanding this, forward-looking businesses must proactively use the technology to boost customer service representatives' capabilities. Used properly, gen AI will supercharge human customer service representatives, empowering them to perform deeper, relationship-building work.
SVP, Cognizant Business Process Services
\r\n"}}">SVP, Cognizant Business Process Services
Sandeep Bhasin leads the commercial team across P&R functions including sales, solution and pre-sales for Cognizant Business Services. He has over 22 years of experience in business process services, leading business transformation, operations, consulting, delivery centers and sales.
\r\n"}}" id="text-fdef366ebb" class="cmp-text">Sandeep Bhasin leads the commercial team across P&R functions including sales, solution and pre-sales for Cognizant Business Services. He has over 22 years of experience in business process services, leading business transformation, operations, consulting, delivery centers and sales.
Head of Research, UK
\r\n"}}">Head of Research, UK
Ollie O'Donoghue leads Cognizant Research, leveraging over a decade of experience as an industry analyst and consultant. His primary focus is on understanding the impact of new economic and technological trends on businesses and industries.
\r\n"}}" id="text-612da48a29" class="cmp-text">Ollie O'Donoghue leads Cognizant Research, leveraging over a decade of experience as an industry analyst and consultant. His primary focus is on understanding the impact of new economic and technological trends on businesses and industries.
Manager, Cognizant Business Process Services
\r\n"}}">Manager, Cognizant Business Process Services
Sneha Bharadwaj has over 15 years of experience in business analysis, product management, and software development. She has led significant mobile app development projects, Smart Factory Manufacturing Cloud Infrastructure initiatives, implementing AWS and machine learning models for real-time equipment monitoring and cost savings.
\r\n"}}" id="text-5eb618c6bc" class="cmp-text">Sneha Bharadwaj has over 15 years of experience in business analysis, product management, and software development. She has led significant mobile app development projects, Smart Factory Manufacturing Cloud Infrastructure initiatives, implementing AWS and machine learning models for real-time equipment monitoring and cost savings.