How AI Impacts Contact Center Agents

May 14, 2021

Change management is part of every successful technology transformation effort. You can nail the technical implementation, but if the people using the new capabilities aren't on board, your project will struggle out the gate.

Implementing artificial intelligence in your contact center is no different. There is a very real human aspect to contact center AI. You need to think through the impacts on agents and staff, communicate often, and bring them along with you. Having employees on board is a key to the success of AI initiatives.

Addressing agent concerns and helping them embrace process changes are particularly important. They might be concerned that bots will replace them or degrade the experience for the customers they care so much about. They may feel like they'll be under constant surveillance with certain AI solutions. And post-implementation, they could find themselves taking hand-offs from a bot or receiving real-time performance feedback during customer interactions.

People generally don't like change, but if you understand how call center agents can be affected by artificial intelligence, you'll be prepared with good communication and training plans to ensure they understand AI will make their lives easier – not harder. This article will provide you with the information necessary to craft effective change management plans as part of your AI strategy.

How artificial intelligence is transforming contact centers

Contact center AI capabilities extend far beyond bots, although bots are certainly an important AI-powered solution. Artificial intelligence can be found in contact center software applications like ACDs, IVRs, and even workforce management. Infusing AI into these core applications can transform how contact centers route interactions, forecast volume, provide self-service, develop agents, and analyze performance.

Let's take a closer look at some of these transformative capabilities.

Real-time interaction guidance

Real-time interaction guidance provides on-the-spot agent coaching while interactions are taking place. This solution measures customer sentiment and assesses agent behavior in real-time and provides tips statistically proven to improve customer satisfaction. Providing feedback during an interaction, rather than days later, gives the agent the opportunity to positively change the outcome.

Interaction analytics

Artificial intelligence is really good at quickly analyzing huge amounts of data to identify patterns. Interaction analytics leverages this capability to analyze every interaction from every channel in near real-time, enabling the software to identify contact drivers, trending topics, compliance issues, emerging problems, customer sentiment, and more. It empowers contact center leaders to make data-driven decisions, proactively manage issues, and develop and reward agents based on their customer sentiment scores.

AI routing

Artificial intelligence has even improved the way call centers route interactions to agents. AI routing accesses a giant database of consumer information to build profiles of inbound callers and matches them to agents that have past success handling customers with that profile type. Routing customers based on qualities like personality and communication preferences takes personalization to the next level.

Agent assistants

AI-powered assistants can also help agents handle interactions more efficiently and effectively. Because artificial intelligence can listen to and interpret conversations, automated agent assistants can perform tasks like retrieving knowledge base articles, recommending the next course of action, and even completing agent tasks like scheduling a customer’s appointment or completing a form or process. These capabilities can help new agents get up to speed and help all agents decrease handle time, increase first contact resolution, and spend more time talking to and building rapport with their customers, and less time completing in-system processes.

Bots and conversational IVRs

A truly transformative capability of artificial intelligence is natural language processing (NLP). NLP allows the software to understand and interpret human speech and respond back to people conversationally. This is used in bots and IVRs to provide customer self-service or to collect customer information to pass to agents. Smarter self-service means fewer of the simpler transactions will be handled by agents.

AI-infused forecasting and scheduling

Because artificial intelligence thrives on data, it's well-suited to assist with forecasting and scheduling. It can help with forecasting by recommending the best algorithm for a specific situation. And when scheduling software uses AI with machine learning, schedules improve with every run.

Each of these capabilities has the potential to improve specific tasks and processes. Combined, it's pretty easy to see how artificial intelligence is transforming contact centers. And note that every one of these examples impacts agents. Artificial intelligence doesn't get implemented in a vacuum. It becomes part of a contact center's ecosystem, which means it affects people, in positive ways.

AI will up-level the role of contact center agents

Artificial intelligence doesn't just have the potential to transform contact center operations; it will also eventually transform the agent job itself. As contact centers gradually add the AI capabilities discussed, the nature of an agent's tasks will change until their role looks very different from their pre-AI days.

In some ways, AI will make an agent's job both easier and more challenging and altogether more engaging. AI solutions like automated assistants and real-time feedback will make agents more successful at resolving interactions, but smarter self-service will make the nature of the interactions that agents handle more challenging. As customers solve more and more of their own simple problems, agents will be left to solve more complex issues, requiring a higher level of problem-solving skills.

Having these more mundane transactions lifted from their shoulders will enable agents to keep their minds sharply focused on solving problems rather than being lulled into autopilot by a series of repetitive tasks. I caught a game of mixed doubles pickleball on TV the other day (strangely fascinating!), and it reminded me of what agents experience throughout the course of their day. The women on the teams spent a looong time gently volleying the ball to each other across the net until - BAM! - someone made an aggressive move and scored a point. Repetitive tasks are like those gentle volleys and if an agent doesn't stay alert - BAM! - a complicated problem can find her unprepared.

The significant reduction of those "gentle volleys" will require agents to have a different mix of skills, heavier on problem-solving and soft skills and lighter on the ability to complete rote tasks. Agents will be able to add more value, which will make their jobs more engaging and elevate their roles within the organization.

Agents aren't going away

Your agents might be concerned about what AI means for their job security. For the reasons just discussed, agents will play an even more critical role once artificial intelligence solutions are implemented. AI isn't smart enough to replace human thought. It's well-suited to handle simple, narrow tasks but can falter when an interaction strays from what's expected. Human agents are still needed for more value-added interactions. Ultimately, AI can help agents, but won't replace them.

If anything, agents are more in demand than ever, despite the current accelerating adoption rates of call center AI. Research shows that 41% of businesses will increase the number of agents in the coming year. But 35% report they're having trouble finding people with the right skills. This agent shortage could lead contact centers to quickly implement AI solutions to supplement agent capacity. After all, customers still need support.

Paradoxically, artificial intelligence solutions may help contact centers overcome agent shortages by reducing turnover. Software that leverages AI can make agents more successful, develop their skills, and ensure work-life balance through more consistent scheduling. These outcomes, along with elevated job responsibilities, can make agents' jobs more satisfying and engaging, which can increase retention. Not only will businesses benefit by keeping more of their experienced agents, but higher employee engagement also results in better CX and business results.

AI can even improve an agent's quality of life

Artificial intelligence solutions can also help ease stress and improve work-life balance, both of which contribute to a better quality of life. When workforce management software is infused with AI, forecasts will be more accurate. This means there will be fewer situations in which agents are required to handle back-to-back interactions all day or be sent home early because the anticipated workload never materialized. Both situations are stressful in their own, unique ways.

Additionally, having a predictable schedule that accommodates their preferences is important to agents. It allows them to have a home life that includes regular, recurring classes, meetings, dinner dates, or whatever is important to them in their personal lives. Schedules built by smart, AI-powered WFM software can help ensure agents have the work-life balance they want and need.

How, specifically, can AI support agents?

handshake human artificial intelligence via laptop

All of the capabilities we've discussed can be used to support agents and make them more effective at serving customers. When implemented properly, including effective and frequent communication, agents can grow to appreciate the helping hand provided by artificial intelligence solutions.

AI-powered feedback gives agents specific, tailored guidance that will evolve as an agent's skills improve. Software that leverages AI can automate agent tasks and deliver relevant information at the right moment. And smarter routing will ensure agents are matched to issues they can handle and customers they'll have a natural rapport with.

Here are some examples of what this additional support can do for agents and CX.

Noah is having a tense conversation with a customer who is more inclined to vent than listen to Noah's solution. In order to be heard, Noah interrupts the customer several times. This triggers an alert from the real-time interaction guidance software making Noah aware of his behavior, informing him of the impact it might have on his customer, and suggesting a different approach.

Sarah is a new agent who is a little intimidated at the prospect of handling more complex interactions. When she handles an unusual refund request, the automated assistant retrieves the relevant policy and suggests that she get supervisor approval for the refund. The extra support makes her feel more confident about her ability to help customers.

Ever since her call center implemented AI routing, Hannah has noticed that she is connecting better with customers. She's enjoying the conversations more and customers are giving her higher satisfaction scores.

Andrew was bored being an agent. It seemed like every customer he helped just wanted to check their account balance or pay their bill. But now that customers can do those tasks themselves in the conversational IVR, he's been getting much more interesting issues to solve. He now finds his job more rewarding and likes that he's adding more value. Andrew isn't alone in being more engaged by more challenging work. PWC found that "74% of employees are ready to learn new skills or retrain to remain employable in the future."

It used to feel like Michelle’s contact center used to have really busy days or really slow days – but nothing in between. That meant that Michelle always felt either overwhelmed or bored, both of which are bad for agent engagement. But since her contact center started using AI-powered workforce management software, they much more accurately predict their interaction volumes and staff appropriately.

Final thoughts

When you talk to your call center agents about AI, be transparent and make sure they understand how new AI solutions will directly impact them. Be sure to tell them: