Can AI replace Contact Center Agents in the future?

Tags: artificialintellegen, contactcenter
Published: 2022-01-28 06:23:40


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With the surge of consumerism, several new technologies are now being used to create the most personalized experiences for customers. Among the ones in the fray, Artificial Intelligence (AI) is leading the pack. Call center solutions, a quintessential tool for customer communication in this era, have also evolved to pack AI in the call center software. 

Today, AI deployment in call center solutions is being widely done to overcome human errors and serve customers in the 24/7 online environment. AI can glean insights for enhancing the customer experience with real-time feedback, predictive analytics, and in-depth analysis, effective in the [virtual call center](https://www.ecosmob.com/call-center-solution/) ecosystem too. While other technologies like IVR (Integrated Voice Response) and call routing systems have made inroads already, AI is touted as a tool to boost customer retention, drive loyalty, while creating hyper-personalized experiences leading ultimately to higher revenue. 

A report by [MarketsandMarkets](https://www.marketsandmarkets.com/Market-Reports/call-center-ai-market-263925467.html) estimates the size of the AI market for call centers to increase from USD 800 million in 2019 to USD 2800 million by 2024. This is a stupendous rise of CAGR 28.5% during the five-year period. The biggest growth drivers are customer engagement via social media platforms. And the burgeoning amount of data generated through various means like the Internet of Things (IoT), social media, and advancements in imaging technologies.

However, the big question that confronts many CX leaders today is: Will AI replace contact center agents? Let’s look at this from another angle to understand it better. 

## What AI can do and what it cannot?

Only a few could have grappled with the true proportion of the impact AI (Artificial Intelligence) would leave on humankind. Why AI stands out is perhaps due to its nature– applicability in most scenarios. An [AI development company](https://www.ecosmob.com/offerings-ai-ml/) can literally plug AI into any process that requires automation. 

Customer assistants powered by AI 

A sizable proportion of tasks performed by service agents are simple one-line responses to standard questions. Trained contact center agents usually match their accent and speech with measured sentences to provide a standard response to customer queries. This is where the customer assistants developed with [artificial intelligence solutions](https://www.ecosmob.com/offerings-ai-ml/) come into play. The AI-powered solution aims to resolve such problems in record time, keeping the call queue under control and saving valuable time for customers. 

Conversational-AI powered IVR

The widely used traditional IVR systems work on two parameters—text-based input and voice-based input. Text inputs mandate pressing numbers or text as the case may be, while voice uses Automatic Speech Response (ASR). Though, it poses restrictions with colloquial accent recognition and inferring context limited to a set of queries.   

[AI development services](https://www.ecosmob.com/offerings-ai-ml/) help to overcome these concerns quicker with conversational AI combined with Natural Language Processing (NLP) and machine learning. To understand the real-life implications, consider a bank or an insurance services customer service hotline. Standard queries such as the account balance and banking product information can be easily accessed in seconds. In another instance, search giant Google introduced updates in Dialogflow in February 2019 to augment the capabilities of conversational AI with virtual agents for intuitive customer interactions. 

AI-powered predictive call routing 

Predictive routing of calls using AI takes place by analyzing a caller’s traits and their historical behavior. According to the caller’s personality, predictive behavior routing (PBR) assigns calls to agents who are best suited to handle such personality types. 

With customers becoming increasingly demanding, PBR calling is a valuable resource at the hand of state-of-the-art AI call centers. 

NLU powered by AI

Natural Language Understanding or NLU falls under NLP, though it differs in meaning. It is similar to NLU, which uses syntactic and semantic analysis in text and speech to decipher a sentence correctly. The likeness ends here. NLU goes a step beyond understanding its ontology by deriving the relationship between words and phrases using a data structure. 

Powered by AI, the contact center of a [large telecom](https://www.forbes.com/sites/blakemorgan/2018/12/20/10-examples-of-predictive-customer-experience-outcomes-powered-by-ai/?sh=fff5ab95d0b4) company identifies customers at the risk of churn to connect with them proactively and offer personalized products. 

Big data management with AI

Using AI in call centers, organizations can mine hordes of data. Today, call center solutions house data of customers from all walks. An AI development services company can help to deploy a powerful analytical system to extract insights from multiple platforms—social media, emails, messaging, and calls. 

For example, if a company has accidentally rolled out a product that is seeing a rising number of customer issues with discussions splattered all over social media. Then the state-of-the-art AI contact center can alert the agents of the incoming high volume of calls. At the same time, recorded messages altered to reflect the current situation better can be relayed. A small step can save the company even in the face of a crisis with [call center software](https://www.ecosmob.com/call-center-solution/). 

## What AI cannot do?

While it may seem that AI in a call center is a panacea to all the problems, the reality is different. Automated chatbots and immediate email responses are insufficient to perform tasks that a human can.

Solving complex issues

A customer service representative is better placed to solve difficult queries or a significant purchase of a high-value product. Several studies now point out that overlooking humble phone calling can have important implications. The reasons cited for inadequate experiences account for the responses not being detailed to the AI in the call center being less helpful.

A survey by [Clutch](https://www.prnewswire.com/news-releases/nearly-90-of-people-prefer-speaking-to-a-live-customer-service-agent-on-the-phone-despite-efficiency-of-phone-menus-for-businesses-300830525.html) found that 88% of customers prefer speaking to a human customer service agent instead of navigating a phone menu. As many as a third of customers end up speaking with a customer service agent after coming across an IVR menu. Unable to reach a human agent, 70% of callers surveyed said they press “0” or utter words like “agent”.

A call center solution delivers greater value from the simplest of the problems to the most sophisticated jobs just by employing the human connection. Voice experiences hold a higher value than any AI-powered chatbots. The good part is that AI-enabled call center virtual call centers can construe that agents can earmark their time for valuable and high-stake conversations to drive relationships and loyalty.

Gauge emotions

Humans are better suited than their AI counterparts to assimilate information and understand emotions. Going over customer concerns, an agent using a call center software can immediately placate an irate customer to put him at ease.

Deciphering a customer’s frustration and confusion on a timely basis can save brand ghosting and abandonment by customers, now common in every business. Artificial intelligence in call centers even with NLU and NLP fails to elicit contextual information from customers that can soothe them.

Many customers calling a call center solution in distress want to share their information with a human agent only in contextualized conversations. Also, any misinformation in data can only be overcome when a customer service agent is at the other end to understand, interpret and make the necessary corrections. For example, data gleaned from a customer’s social media activity.

Better connections, less training

Every time artificial intelligence in call center deployment hinges on training the system to interpret, understand and collate information and present the right answer within the time span. On its own, AI lacks the prowess that human connections can bring. A customer may use a more casual speech and tone, making it difficult for AI to interpret and pick the nuances. 

## What does the future hold?

Understandably, AI is not going to eat up jobs or replace contact center agents. We live in a connected, competitive, and consumeristic world. AI call centers are likely to drive efficiencies and help connect the dots that seep in with human errors and limitations. A hand-in-hand approach, collectively by employing an AI development company to create custom solutions aiding customer service representatives will see an upswing. These may result in:

Intelligent call routing
In-call guidance
Less search with AI-enabled processes
Cognitive calling capabilities
Data crunching with AI
Mutually symbiotic relationship

Not thinking in absolute terms in arriving at the decision to employ both holds the key. For lower-level tasks, a chatbot may be efficient while human representatives can take up jobs that need thoughtful actions and personalization. Both serve their own purpose and organizations should try to create a balance in employing them by understanding their own needs. Every kind of business requires a differently tailored call center solution.

We provide customized yet intuitive AI solutions for all contact center needs. Reach us @ ecosmob.com for more information.