Transforming Customer Service with Artificial Intelligence

Manjunath Srinivasamurthy • October 21, 2020
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COVID-19 pandemic has forever changed the way enterprises operate. With lockdowns implemented in major parts of the world, companies were forced to relook at their business models and strategies to ensure business continuity and survival. However, the biggest challenge remains ensuring superior customer experience to thrive in the new normal.

Current customer service models are hinged on the availability of an agents to satisfactorily resolve customer queries. These agents would interact with the customer, understand their problems, and provide solutions. The CRM systems used by agents, typically came with case management features allowing them to create and classify cases, route it to the best possible individual/ team who would attempt to resolve them based on a combination of expertise and available knowledge in the system.


With companies keen to cut costs, customer service managers are forced to find novel ways to provide similar or enhanced level of support without expanding their team footprint. Consumer behavior too, is changing, with customers expecting personalized experiences, faster resolution times and ability to get queries resolved 24X7. This is where Artificial Intelligence and Machine Learning can play an integral part in reshaping customer service models.

AI/ML can offload routine tasks performed by agents, and also provide customers with self-service channels to find information quickly and raise a query when needed. They can also provide supervisors with real-time service ticket intelligence to optimize support operations. Finally, support managers will be able to scale up operations in a very short time to support multiple product / service lines.

Key goals of enterprises for delivering an AI-powered customer service include:

  • Strengthen customer relationships
  • Scale support operations at speed
  • Boost implementation ROI
  • Insight driven decision making
  • Improve business functions



The benefits of AI, though significant on agents and customers, will be seen across the ecosystem. Let us explore scenarios where AI can enhance customer interaction and improve agent productivity.  

Elevate self-service scenarios

With customer service becoming a key differentiator, companies know they need to be available to the customer 24X7. Initially, companies were able to accomplish this by providing generic information via multiple sources such as FAQs, trouble-shooting videos, and guides. But lack of personalization meant that customers were overwhelmed which ultimately led to frustration. In fact, a Gartner survey found that only 9% of customers reported resolving their issues completely via self-service.

AI takes this to the next level by humanizing the delivery of this information. Conversational bots using ML can handle majority of customer queries by looking up transactions related to accounts, make updates to personal information, and handle simple tasks like account unlock and password resets. They are also able to seamlessly hand-off to an agent for more complex interactions in addition to passing on the already collected data. This is also true in case of virtual assistants like Alexa, Google Home etc where NLP can be leveraged to “listen” to customer queries.

AI-powered Customer Communities

Customers love to look up information on the website before reaching the support desk and hence it is crucial to have a robust community portal with relevant information. An AI – powered customer community can understand the intent and contextualize the customer’s search by cross-referencing it with customer’s transaction and location history, behavior etc. and can suggest the most relevant answer.

An AI powered community can mash-up information from multiple sources such as product manuals, training videos and even point to a similar query that has already been answered. This improves case deflection rates, and enhance customer satisfaction as queries are resolved instantly.

Intelligent ticket routing and automated response

An L1 agent is tasked with triaging incoming tickets and classifying them to routing them to the right team. This is often time consuming and may quickly overwhelm if there is a deluge of tickets due to an ongoing service outage. AI can automate the complete process of tagging incoming tickets from multiple channels and may summarize, gauge intent, understand urgency and effectively route them to the rightly skilled specialist. Additionally, a contextualized response is generated and send to the customer instantaneously.

Imagine a scenario where customer is facing issue in installing or configuring the product. When the customer raises a ticket, links to installation videos or setup FAQs are often sent while ticket is being serviced by a team. This will help the customer troubleshoot the problem before raising a query with the support desk.

Empowering Agents with Cognitive search

The support agent of today is expected to do more than just solve customer queries. They are expected to build customer relationships by generating leads, providing product information, cross-sell/ up-sell and be the voice of customer to the enterprise. All of this can be made possible only if they are armed with the right information that is also contextual. Knowledge Centered Support (KCS) is one of the guiding principles for a successful customer support operation.          

AI-driven Cognitive search can bring in relevant information that is stored across CRM systems, knowledge portal, company intranet, rich media and blend it in an easily consumable format. This will allow the agent to find relevant information without sifting through long search results. Customer service is one of the major areas where AI is being used and showing an impact. Being in an era of personalized customer service and customer experiences, equipping CRM platform with AI can be a great way to take the plunge into the business transformation. All the right tools and techniques can help agents to be more effective in this new normal. 

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