Biggest AI Trends Transforming the Customer Service Industry (And, How You Can Prepare for the Future)

88% of customers say the experience they get from the service agents is just as important as the products they use when they decide to purchase again from the same brand.

But hey!

Bad customer service is way worse than no service!

Customers have more expectations from the customer service departments in 2023 than last year. While business leaders believe whatever they are doing today to improve customer service is working, it is very far from the truth. Most brands are aware of their customer’s expectations, yet they fail to provide support that is at par with the promises they make about their products. Poor customer service could mean many things — zero response, long waiting time, faulty automated I.V.R. support, incoherent voice message, delayed escalation to a human service agent, or multiple transfers within the department to solve the same problem!

The value of a great product lies in the service and experience customers derive from using it.

All it takes for a customer to leave you is one bad service experience. Every bad experience snatches away your customers and firmly places them in the “trust zone” laid by your competitors. You did the hard work, but your service failed to retain the customers. What’s worse — your customers would just leave you because of poor service experience without telling you the exact reason behind their decision.

That’s it!

In the era of fast-paced omnichannel digital experiences, customers do not wait for their brands to make corrections. They only trust brands that use next-gen technologies to provide service and support in real time.

What do customers want more from such brands?

Customers want to engage with organizations that have a clear alignment with customer value and service. They want an easy, accessible channel of communication that makes it convenient for them to reach the company and extract correct information from a trustworthy representative. These instill loyalty and fuel empathetic cooperation within the community of consumers. In 2023, improving overall CX remains a top priority for business leaders. Yet, only 6 percent of brands saw any significant improvement in their CX results in 2023, a drop of 4 points compared to 2022.

Are business leaders falling short of expectations? Can they improve their CX results using new capabilities such as generative AI and deep learning?

AI can help brands create a persuasive and adaptable CX strategy with service and value at the center of every interaction.

That’s why so many brands are pinning their investments in customer service on conversational channels such as AI-based voice and chatbot assistants.

The search interest in AI-related technologies and applications has more than quadrupled since 2020 among business leaders from the customer service industry. In a stiff market environment, new AI models such as OpenAI’s ChatGPT and Google Bard have sparked a spurt of innovations in the customer service industry.

According to the Equinix 2023 Global Tech Trends Survey, business leaders are planning to invest heavily in Artificial Intelligence tools for contact centers (71%), sales (73%), Marketing (75%), Customer Experience Management (79%), and IT Operations (85%). Clearly, customer-centric teams are more likely to adopt AI tools and solutions to stay competitive in the vastly volatile market conditions in 2023. As per research, there is a clear uptick in the volume of search results related to AI trends in marketing, sales, communications, and customer service.

And, as organizations become more familiar with the next-gen AI models, there could be further penetration of these capabilities in cloud contact centers.

Customer Service Teams Infuse AI and Automation in Pursuit of Efficiency

Customer service is an important aspect of doing business today. Customers place a very high wager on organizations that meet expectations with their quality of service. AI, clearly, is at the core of every innovation that happens in the customer service industry today. Organizations leverage AI for two things:

1. Automation
2. Augmentation

There are hundreds of AI and machine learning applications for the customer service industry.

According to Colin Crowley, Senior Director of Customer Engagement at Freshworks, there are three main trends in AI and machine learning development that we see creating significant differentiation in the customer service industry. These are:

1. Sentiment analysis and predictive problem-solving
2. Pro-active delivery of value to customers using Predictive AI
3. Workforce management and forecasting using AI-powered predictive intelligence

Now, all these trends manifest in the form of chatbots, voice search, translation, generative AI, recommendation engines, automation, and hyper-personalization. Let’s understand the biggest trends related to the role of AI in the customer service industry.

Lorrissa Horton, Senior Vice President and Chief Product Officer, Cisco Collaboration Group provided valuable insights on the correlation between machines and humans in creating a CX journey for every customer. Lorrissa said, “With AI-assisted CX,  businesses can also provide agents with resources and insight to help problem solve even better and faster.

However, one should note that we need both AI and human agents for CX to be successful. At Webex, we believe artificial intelligence can create “super agents” as one of the most misunderstood beliefs about AI is that it will eventually replace human employees. AI will certainly change workloads, staffing and processes that may lead to redefining how your contact center is staffed, but a primary advantage of AI is that it augments agents to make them more scalable and efficient.

Take the example of a chatbot. When the bot detects that the interaction needs to be escalated to a human agent, it brings along with it the history of the conversation to enable a seamless transition from self-service chat to assisted chat. The agent can then very quickly and effortlessly take over the interaction with everything they need to be displayed right in front of them.

In this regard, AI is an enabler for better live agent assistance, not a replacement of it.”

AI-powered contact center software for the service industry has countless benefits. Establishing a contactless, friction-free conversational channel that practically answers every customer query with empathy is probably the most sought-after benefit that AI delivers to contact centers.

According to Salesforce, 45% of service organizations use artificial intelligence-led solutions to meet the expanding customer expectations.

58% of service organizations across various industries rely on process or workflow automation technologies to achieve efficiency. With agent attrition rate in the service industry at an all-time high, it makes sense to invest in AI-enabled platforms for automation and augmentation of the existing human workforce and back-office processes. When people and AI collaborate in service organizations, it can help brands create meaningful personalized experiences with streamlined communication.

Choosing a mission-driven AI roadmap for your customer service organization can be overwhelming, especially when you have so many options spread before you. In this article, I have identified fifteen AI trends that would enable service organizations to adapt to a fast-evolving digital-first environment.

AI-powered chatbots

AI-powered chatbots are a disruptive force in the service industry. In the current service-first economy, chatbots have emerged as a solid support to contact centers that previously complained about redundant documentation, repetitive tasks, and administrative overloads.

You should get a chatbot for your contact center if you are facing these scenarios:

• Getting too many similar-sounding calls from customers who want an instant resolution to their problems
• Having reduced workforce efficiency due to turnovers, absenteeism, and human fatigue
• You want to turn your contact center into a perpetual 24×7 service organization

Chatbots can solve all these problems. Modernized applications of chatbots include the ability to track and analyze consumer behavior and emotions.

Jennifer Bers, CRO at Unbabel said, “There are a variety of ways that AI is currently being used in customer service — from automated messages to live chatbots and machine translations – all of which can serve to contribute to time and cost savings and ultimately the ROI for a business.

Given the demands placed on customer service teams by customers and management, AI technology must play an increasingly large role in automating or streamlining repetitive, low-value work, freeing up agents to focus on complex or novel inquiries and tasks. Language is a great example of this, where machine translation has advanced to the point that businesses don’t need to hire for language skills, and instead can look for skills in prioritization, customer empathy, technical skills, product knowledge, and so on. It also means customer service organizations don’t need to silo their operations, training, HR, corporate updates, learning and development, etc. by language, which is a tremendous time saver.

Moreover, augmenting agents with machine translation allows organizations to expand rapidly to new markets that wouldn’t be feasible with native-speaking agents alone, without compromising on quality. Overall, AI can prove invaluable, especially in the world of translation, to improve the quality of translations while saving time and money.”

Kevin Bobowski, CMO at Aware, agrees. Kevin said, “AI can significantly enhance the performance of call centers by driving quantifiable results. AI-powered virtual assistants or chatbots can handle routine customer inquiries, freeing up live agents to focus on more complex tasks that require critical thinking. Chatbots can provide instant responses, gather necessary information, and offer basic support, improving response times and reducing live agent workload. AI can also benefit call centers by analyzing customer interactions in real time to detect sentiment, recurring themes, and emotional cues. This allows decision-makers to identify customer dissatisfaction or potential escalations early on and intervene to provide prompt assistance or address issues proactively. Recurring themes are indicative of gaps in the service model, which can be proactively managed to better enable the employee, who in turn can deliver a better customer experience.”

Contact center managers could utilize AI-powered chatbots to assist human service reps while offering contextual guidance to customers in a way that would showcase the highest quality of service. They have the power to not only generate accurate responses to complex customer queries but also can simplify contact center management processes with personalized engagement, content management, and information retention. They augment their capabilities to address specific business needs, thus freeing valuable time for human agents which they can utilize to attend to other important tasks.

Hardy Myers, SVP of Business Development and Strategy at Cognigy, mentioned the role of Conversational AI in our interview series. Hardy said, “Any industry that has a large customer base will benefit from deploying Conversational AI-based solutions. The insurance, automotive, manufacturing, financial services, retail, utilities, healthcare, and telecommunications industries are among the first to adopt, and benefit from, CAI. Bosch, for example, taps into the power of Conversational AI to cultivate a resilient, creative, productive workforce. E.ON is masterfully managing a portfolio of more than 30 voice- and chatbots, achieving unprecedented levels of automation for both its customers and employees. Toyota’s vehicles now proactively call vehicle owners when warning lights are overlooked or service is required.”

Is an AI-assisted customer service plan better than human-only efforts?

Fabrice Martin, Chief Product Officer of Qualtrics XM for Customer Frontlines spoke to me about the idea of having chatbots at the heart of your service department. Fabrice said – “Research from Qualtrics shows that consumers are generally confident AI can provide faster customer service, but worry about their privacy and whether something like an AI-powered chatbot can respond empathetically to different human emotions. The key is to augment the work of human agents with AI tools that make them more effective and power personalization at scale. Generative AI and Machine Learning solutions can analyze customer needs and emotions in real-time, then deliver brand-specific suggestions, personalized experiences and offers, relevant knowledge base articles, and related answers, helping the agent focus on listening to the customer and reducing the time it takes for an agent to resolve each customer’s issue.”

Are chatbots useful?

6 out of 10 customers would prefer to engage with a chatbot rather than wait for a customer service agent to take their call. Familiarity with the concept of chatbots among Gen Z and millennial customers also makes it easy for service organizations to place these AI-powered assets at contact centers. 88% of customers have already experienced what it feels to interact with a chatbot when they call the service department.

How to prepare for the future with the contact center chatbots?

If you want to prevent your customers from getting frustrated every time the call is transferred to a different agent, you need a dedicated AI-powered chatbot. Chatbots can engage customers who switch between service channels based on convenience and availability. Having a chatbot for recommendations and for answering FAQs can free up your agency time so that you can focus on more important activities.

Call center RPA

Are you looking for a huge differentiator in your niche, sector, or industry?

Try robotic process automation.

Robotic process automation (RPA) is a shot in the arm for the service industry. In an era where the pandemic created unforeseeable challenges for every industry, the services organizations managed to come out of the turbulence fairly unscathed.

Reason?

They leveraged the power of RPA in their call centers to stay connected to their customer base, delivering responsive service and convenience through digital channels. Call center also empowered service teams to do more with less in highly erratic remote settings, without losing vision of their current goals.

Barry Cooper, President, CX Division, NICE, explained. “Automation is a powerful way to empower contact center agents to deliver exceptional customer experience and improve overall operational efficiency. Through intelligent automation (I.A.), repetitive and mundane tasks can be taken off an agent’s workload, freeing them up to pursue higher-level priorities and greatly improving workflows. Through recent technological advancements, generative AI can be combined with purpose-built AI to uncover targeted automation opportunities for businesses, seamlessly and in real-time, with very little back-end work by the business.”

Unlike other AI applications in the service industry, RPA has been around for some time now.

The whole idea of call center automation finds its genesis in the RPA innovation bowl.

According to research, more than 14 million contact center employees are working worldwide across a range of sectors, company sizes, and geographical regions. Most of them face similar challenges at their contact centers. While the issues with customer contact centers are widespread for both organizations and customers, it is possible to implement RPA to solve these challenges quickly.

For example, call center employees may need to examine as many as 20 systems to handle a single client issue. Additionally, there is pressure to shorten call times and, ideally, fix problems during the first interaction. RPA software can do it all, at a fraction of the time (almost 20% faster) of what a human agent would take in a practical scenario. By 2027, agents would save 40% of time spent on mundane tasks — thanks to call center RPA software running on advanced machine learning models and AIOps infrastructure.

UiPath’s senior leader explained the scenario to me.

Brad Beumer, Customer Experience and Contact Center Automation Lead, UiPath, said, “When a customer calls a contact center, they often have to repeat information, wait for agents to find data, or are even put on hold. However, AI-powered automation can support a contactless contact center. Organizations can automate the sorting of customer requests, rate the tone and sentiment of requests, and prioritize requests to manage the most sensitive or urgent requests first. Tools like Communications Mining can also assert the true intent of the customer request, even if the customer did not file it in the correct category. Automation is also constantly monitoring new queue items to alert agents to t********** and can display all relevant information about the request. AI-powered automation also provides agents with a recommended next-best action based on the case type and business context. An agent can choose an action such as changes to the customer account or offering a refund. Then, automation processes those transactions while the agent focuses on communicating with the customer rather than making the customer wait. With AI-powered automation, organizations can reduce the amount of data processing required by humans, lowering error rates and the need for rework. For example, Transcom, an outsourcing company, embraced UiPath’s business automation platform and the company has saved over 60,000 hours a year with automation, with 2,000,000 tasks executed yearly by automation.”

Agent Performance Management 

Isn’t it tempting to figure out who is your best agent, and what qualities make them a clear winner?

But wait, the best agents do not stay in the same role or organization for very long.

That’s a problem for the service organizations that want to field their best reps on every high-value call. It just doesn’t happen. And, customers know about this problem in the contact centers.

But, AI can solve this problem for you with innovative techniques.

Let’s peel the layers.

The service industry has always been at the receiving end as far as agent performance management goes. Organizations face a dual challenge when it comes to managing agent performance — first, they have to improve the overall customer satisfaction scores at all times; second, they have to reduce operating costs.

Providing consistent and high-quality customer service still involves human agents. In more ways than one, customer experience and agent experience are linked to each other. Thankfully, by using AI, service organizations can track agent performance management in a cost-optimized manner without losing sight of their CX goals. AI tools can tap into the workflows and conversation patterns of your most tenured and skilled agents, gather institutional knowledge, and combine these and other data points to recruit, train, and develop new agents who can increase the overall workplace productivity and quality of service.

Yew Hwee Ng, SVP, Asia, Zendesk said, “Consumer expectations continue to rise year on year. And yet, businesses today are under significant pressure to do more with less amid the uncertain macroeconomic environment. Done right, AI can be a force multiplier for CX teams, helping them be more consistent, better understand customers, and glean more actionable insights. One of the biggest opportunities lies in its ability to eliminate significant amounts of manual workload that can be time-consuming and low value, thus freeing up time for agents and admins to work on more meaningful tasks. Insights derived through AI can also help businesses identify knowledge gaps and pinpoint problems before they snowball into large-volume issues.

When it comes to interacting with brands, consumers today know what they want.

They want fluid, personal, and natural interactions that put them in control and do not interrupt current tasks. In fact, 72% of customers in APAC spend more with brands that provide a seamless experience between all points of contact.

As AI is increasingly being embedded across the entire customer journey, it is also helping companies shift from reactive service to a proactive, conversational one. This can include chatbots that provide human-like conversational experiences and can intelligently triage queries, as well as the ability for a customer to start an interaction on one channel and seamlessly switch to another channel without the need to repeat themselves. It can also provide agents with an accurate summary of the customer’s situation and past interactions to suggest the perfect reply with the right tone that’s on brand.

The conversational capabilities and easy accessibility of generative AI give companies the ability to respond to customers quickly, on whichever channel they are on, with the right amount of detail and context when trained well.

As AI becomes more cost-effective and easier to build, train, and maintain, there will be wider adoption of the technology, especially generative AI with its conversational capabilities, redefining how companies engage with their customers.”

Workflow Design and optimization

All great service organizations have one thing in common — they all have robust workflow management and optimization for marketing, sales, service, CX, and employee experience.

And, they are using AI workflow automation to beat the blues in the service industry.

Bjorn Andersson, Senior Director, Global Digital Innovation Marketing and Strategy at Hitachi Vantara explains the logic behind adopting an AI-assisted customer service plan rather than going ahead with human-only efforts. Bjorn said, “By harnessing the power of AI-assisted customer service and predictive analytics strategies, companies can implement faster customer response times and increase internal productivity amongst team members. Additionally, AI-powered tools allow employees to better understand other facets of company operations by automating or accelerating tasks that were previously “human-only.”

Furthermore, companies can invest in employee development by using AI to support customer service personnel. This allows for optimized onboarding and transitioning for new hires from the beginner stage to the intermediate and beyond. AI-assisted customer service plans also allow for the creation of more agile company strategies that focus on optimizing customer results, experience, and engagement and maintaining competitive advantage in today’s constantly evolving technological landscape. AI enables companies to have complete visibility into their data stack, allowing them to access critical customer information in a digestible, accurate way, and offers a clear, contextual picture of customer needs. This, in turn, allows companies to create targeted approaches to fulfilling customer satisfaction consistently.”

Pega’s Christopher Patterson said, “AI has the incredible power to help human agents be more efficient and productive than ever before, giving both agents and customers a better, faster service experience. To start, customers can benefit from AI-powered self-service that can quickly resolve both simple and complex inquiries before a human agent needs to get involved.

Without RPA, CSRs face many different manual and tedious tasks in a typical day – entering data, toggling between screens to find information, and more. These manual tasks are error-prone and cause CSRs frustration –  making their jobs more difficult than they have to be and taking time away from focusing on what’s most important – solving the issue for the customer. With RPA, contact centers can eliminate the time agents spend navigating multiple applications while speeding up processes, eliminating errors, and getting work done fast. By taking these frustrations out of the CSR’s experience, they can focus on providing empathetic, relevant, and helpful interactions that not only solve a customer’s issues quickly but ultimately provide a great experience that helps promote brand loyalty.“

Running a highly efficient contact center involves seamless and collaborative engagement between the human resources and their AI assistants. It requires a scientific approach toward designing and optimization of different workflows. High-performing service organizations infuse their contact center management approach with AI and machine learning applications. This enables them to build a synergistic customer experience strategy where agents and customers don’t have to repeat their actions and words to get value out of their efforts.

Using AI and machine learning, service teams can quickly design a consistent workflow management and optimization process that can be trained and re-engineered for a wide range of operations. These could be agent assistance, I.V.R. menu setting, workforce forecasting, call routing and automation, virtual assistance, voice search, and call scheduling.

Why should you use AI workflow management and optimization?

• It is the foremost component in a service organization’s digital transformation strategy
• It’s effective and time-saving
• It’s accurate
• It’s scalable with time
• It’s cost-effective in the long run

EdgeTier co-founder and CEO, Shane Lynn says, “In an ideal world, everyone would have human-only customer care, with every human highly qualified and knowledgeable in every area of the business. But in the real world, we have constraints: budget, staff acquisition, and training. And, customer service agents often need support in managing the volume and complexity of tasks to consistently achieve a high customer satisfaction result…

That’s why many contact centers have either automated simple requests – password changes, account updates, and cancellations – or allow customers to manage the process via a self-service portal. This elevates human agents to perform the genuinely difficult task of interacting with clients and understanding their situation while operating multiple systems. This is where AI can further assist agents in delivering a consistently high level of service. From retrieving customer account data and prompting the agent with answers throughout the conversation, to automatically routing and sorting calls based on their value or urgency, humans working seamlessly in conjunction with AI results in a faster and more individualized service experience delivered by more knowledgeable agents. Undoubtedly a bonus for both the company and the customer.”

Recommendation Engines

It’s exciting times to be working with AI in the service industry. The effervescent rise of generative AI tools such as ChatGPT, Salesforce Slack GPT for Service, DALL-E, Synthesia, BARD and others have shifted the playing field in favor of AI-enabled contact centers. In a written statement to our editorial team, Salesforce’s marketing team provided context to how Contact Service teams benefit from using generative AI capabilities.

Salesforce said –

“Generative AI capabilities can empower contact service teams to scale service operations from the contact center to the field while also reducing costs. Recent research has shown that 63% of service professionals say generative AI will help them serve customers faster. Among service professionals who have already implemented generative AI solutions, nine out of 10 say it helps them serve customers faster. Contact Service teams have reported that generative AI is helpful for content creation, personalized service communications, customer self-service options, and service data analysis.

To stay competitive in today’s market, service teams need access to the latest data and technology to improve customer experiences. AI tools will help them collect relevant data and information, while also presenting the most relevant information to brief service workers on customer history, past visits, and notes from the service event. Teams will essentially be equipped with a “digital toolbox,” helping workers connect with subject matter experts instantly via Slack to resolve issues, easily access step-by-step repair and knowledge articles, and better identify up-sell opportunities for customers – all from their mobile devices.”

For large-sized call centers, is it worth using generative AI tools that fuel conversations with customers?

According to Salesforce, it is indeed worth using conversational AI tools that receive recommendations and responses based on real-time CRM and CDP data.

Salesforce offered industry-specific examples. 

“Conversational AI tools like Slack GPT for Service can help teams resolve cases and respond to customers faster with personalized AI-generated replies that are grounded in relevant data sources.

Large lines of customer queries can be quickly alleviated by AI-generated responses and customer self-service guides based on real-time data. Using AI-generated knowledge articles and step-by-step guides, customers can easily tackle simple troubleshooting issues on their own, eliminating the need for an in-person technician visit. This often leads to higher customer satisfaction scores, since solving issues themselves is quicker and offers less of a disruption to their schedules.

By combining generative AI, real-time data, and CRM, Service GPT can create personalized responses to resolve customer issues faster and at scale. That means service agents don’t have to manually craft replies to common issues, freeing them up to focus on more complex issues and unique customer concerns.”

Patrick Martin, Coveo’s GM of Service, also thinks that AI-powered recommendations for customer service are a great asset for the industry.

“Cloud contact centers can use AI-powered recommendations in several ways: one, to circulate carefully curated knowledge base articles (plus other content types that help expand customers’ knowledge and use of a product or service) among customers in the form of self-service. 

For example, Xero, a cloud accounting platform for small businesses, uses Coveo to offer high-quality customer support. Around 95% of questions asked at Xero are answered by self-service help content powered by Coveo, deflecting over a million queries from Xero’s support team each month. Proactive AI-driven content recommendations help customers find what they’re looking for as they’re searching. 

Another way is by empowering agents with the information they need to resolve novel issues as they appear. Salesforce uses Coveo’s AI-driven search across their knowledge base. CRM-embedded Insight Panels, accessed by Salesforce’s agents for roughly 75% of support requests, is a huge time saver by eliminating the need for manual searches. Being able to resolve customer issues quickly and with empathy has helped Salesforce achieve its highest-ever CSAT scores.

A unique feature of Insight Panels is the ability to show what a customer has already interacted with in a digital experience — we call these User Actions. This information coupled with contact details or a customer’s own explanation helps put agents five steps ahead. Rather than repeating a litany of already-tried (and failed) solutions, the agent can immediately focus on the untried solution to resolve issues faster.”

1-to-1 Personalized messaging

Taking one step ahead in the direction of AI-generated conversations, call center agents can truly get closer to their callers by utilizing deep learning and analytical tools for personalization. Combining these with other capabilities such as Web3, AR VR, and the Metaverse, agents can transform the roadmap for AI in the service industry by 2030.

David Lambert, VP & GM, Strategy & Growth, APAC, Medallia, said, “With AI and machine learning advancements, speech and text analytics can now process and analyze data in real-time. Call centers can monitor ongoing customer interactions, identify emerging trends, and take immediate action. Real-time speech and text analytics help detect potential issues during calls or chats, provide real-time guidance to agents or bots, and allow call center supervisors to make data-driven decisions on the spot.

In summary, these AI and machine learning development trends empower call centers with prescriptive intelligence and advanced analytics capabilities. They enable call centers to see customer journeys, anticipate customer needs and personalize interactions in real-time, and continuously orchestrate every customer’s journey to improve their experience.”

Gaurav Sharma, CEO and founder of JustCall by SaaS Labs beautifully explains the role of Conversation intelligence AI. The CEO states that conversational AI enables contact centers to provide highly personalized and contextualized experiences to customers. “Through advanced features like real-time guidance, sentiment analysis, and automated call scoring, contact center agents can deliver tailored support, address customer needs more accurately, and adapt their approach in real-time. This level of customization significantly enhances customer satisfaction and engagement. Furthermore, conversation intelligence  AI streamlines contact center operations, improving efficiency and productivity.”

“Automated processes, such as compliance tasks, workflow simplification, and post-call reports, free up agents’ time, allowing them to focus on revenue-generating activities and providing superior customer service. This is game-changing for businesses as recent reports indicate that 40% of customers stop doing business with brands with bad customer support. By harnessing the power of conversation intelligence  AI, contact center owners can transform their customer experience strategy by delivering personalized experiences, optimizing operational efficiency, and ultimately driving improved business outcomes,” Gaurav added.

How to Thrive in the Era of Generative AI

Will AI replace agents forever from the service industry? What are the chances of having a superior customer experience delivered by AI-powered tools working in singularity compared to one that is a mix of AI and human intelligence?

Let’s understand the two scenarios.

Manish Grover, Head – GTM & Strategy, Ignitho states that customer service over any channel is enhanced by the use of AI. He added, “Conversational agent capabilities have improved significantly with the advent of AI. While the older agents were mostly rule-based with some NLP and sentiment analysis thrown in, the new conversational AI agents can now also analyze data sources and provide accurate answers. 

AI-based conversational agents can lower average call handling times and faster first-time resolutions. They can also improve in-app customer experiences and reduce the cost of software engineering.

1. Knowledge base documentation can be analyzed by AI and the answers can be provided dynamically. An example of this is when customers call in with questions about their insurance eligibility. Today, an agent must pull up the right document, read and then explain the eligibility to the customer. Any scenario analysis must also be addressed. This can be simplified with AI that can easily engage in Q&A based on the contents of the document.
2. A customer-facing conversational AI agent can handle most mundane questions, and only hand over to a live agent when the topic needs more than 1 attempt to resolve. This frees up agents to handle a higher volume of inbound requests.
3. Customer behavior can be tracked and addressed as well. For example, if customers have been to a screen multiple times, and have navigated to help content as well, then a conversational AI agent can interpret these signals in real-time and offer assistance to the customer. 
4. Conversational AI can also be used to bridge software engineering gaps. For example, a common scenario is for customers to search for an item on their credit card, or try to make sense of an item on their statement. These queries can be handled by conversational AI agents that access the database in real time and provide answers in natural language thus alleviating the need for additional software development to account for these cases that are difficult to nail down.”

Now, answering the fear of AI replacing human agents from the service industry, Sarah Gilchriest, President of Circus Street, comments on how businesses and their employees can ensure they thrive in the era of AI.

Sarah said, “With the latest developments in AI, and tools such as ChatGPT becoming mainstream, it is understandable that some workers are worried about the impact that this could have on the future of their career. A lot has been said about the potential for job losses, and this appears to be starting to happen with BT announcing it would replace a significant number of its workforce with AI. However, the reality is that this is going to be a drawn-out process, and we remain a long way from AI being capable of taking on a lot of skilled jobs. There’s no doubt though that increasing automation in businesses is making certain jobs, such as customer service or data entry, potentially redundant. 

“The reality is that there is a lot employees can do to future-proof their careers if they think they are under threat. If people want to make sure they are not left obsolete by developments in tech, they need to be thinking about the steps they can take to protect themselves, rather than worrying about whether these advances will mean that robots replace humans. Individuals should look upon it as an opportunity to incorporate cutting-edge tech into their day-to-day work and consider how to upskill themselves to be able to work alongside it. If not, the truth could well be that AI will not replace you, but a person using AI will! Whilst AI will eliminate certain roles, it will also create millions of new jobs. This will not be confined to data scientists, analysts, and machine learning engineers – it will include people specialized in getting the most out of AI solutions and managing automated systems. For example, copywriters who may see gen AI take on the bulk of their writing could find that upskilling themself in search engineering on tools like ChatGPT, to produce the best possible copy will enable them to carve out a new career. This is very similar to the way many stop motion animators continued their careers by lending their insights and expertise to CGI companies to produce better graphics. 

“Business leaders need to make sure that their teams are well placed to work with, and benefit from, the latest innovations, and so need to focus on retraining their staff to support that. It would be flawed to take the view that costs can be cut by making redundancies, with machines able to carry out all the work going forward. It is not as simple as firing everyone and replacing them with an algorithm. Human oversight and management are essential because AI is far from flawless. To be able to manage, apply, and monitor AI tools, businesses need a good level of data knowledge and expertise. Due to the skills gap in data, the most cost-effective and practical way to do this is to upskill and retrain existing staff. Businesses that prematurely let go of staff in favor of automation may soon find themselves quickly having to rehire experts at a premium. 

“The benefits do not stop with the ability to make the most of innovations in AI. A workforce trained in a variety of cutting-edge skills is also much more flexible and resilient – people can more easily move between industries and it can be a key driver of innovation. The more people who can understand and use the latest tech, the greater the chance of new applications and consequently breakthroughs which create new industries.”

The Future of AI-based Service Industry

Customers care about speed, quality, and personalization of conversations with contact centers. They expect agents to understand their problems even before starting the call. With so much information about chatbots, analytics, and generative AI available online, consumers are smarter than ever before — they know which brands are using technology to improve CX and which ones are missing out on the show.

Shirli Zelcer, Head of Data and Analytics at Merkle concluded the topic for us. Shirli said, “Customer service teams have been using chatbots and other forms of AI for quite some time now. What’s new (recently) is the ability to train AI models on large repositories of customer contact data, to provide much more personalized, more responsive, more detailed, and more natural responses to customer queries.

Large language models can also be used internally to provide customer service managers and other stakeholders with much easier access to data & insights from customer contact databases and other data sources. What contact center owners should do – to get started – is to make sure their logs and other data sources are in good shape, and ideally integrated with other forms of customer data in a data lake or other common warehousing solution – because this is what will enable a partner like Merkle to help deploy generative AI technologies to accelerate insights and deliver more seamless customer interactions.”

For brands, it is a make-or-break situation with AI-based automation and analytics capabilities. A minute’s delay in adopting the new generation AI solutions for service management can derail your CX strategy, exposing you to unforeseeable forces that result in unplugged customer churn, loss of productivity, and eventually, a shattered business growth.

If your current contact center management strategy is leaving out AI and automation from the picture, you could be missing out on your organizational CX goals. Customers love AI as much as agents do. With adequate AI coaching and content sharing across the board, you can fast-track your digital transformation in the call center.

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