How AI Can Empower Your Contact Center Employees

The impacts of automation and artificial intelligence are everywhere around you. Self-checkout stands and smart home devices that make routine tasks seamless are inventions most people are used to by now. While the future of AI promises self-driving cars and human-like robots, the world isn’t quite ready for those applications yet. However, artificial intelligence is starting to play a larger role in organizations and professional environments.

Contact centers, in particular, are being transformed by AI’s capabilities. The way customers receive service, the complexity of agents’ work, and managerial decision making are changing. Call center operations, including hiring strategies, keep improving and elevating to higher levels. Employee empowerment isn’t an item on leaders’ wish lists — it’s the new reality AI is helping to create.
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Below are some of the ways this technology is making it happen.

More Complex and Rewarding Work

A decade or more ago, a typical day for contact center agents involved handling repetitive calls. Requests to add minutes to prepaid cell phone plans, make bill payments, or change service plans came in back to back. While you might think this makes for an easy day, completing routine tasks can lead to stress. This stress arises from boredom and burnout because a job isn’t challenging or meaningful enough.

But with conversational AI tools, agents no longer have to deal with repetitive, simple requests day in and day out. Enter chatbots and interactive voice response systems that respond intelligently to customers’ questions about their invoices, service plans, and orders. Only the more complicated problems and inquiries get through to live agents. This gives employees opportunities to use their critical thinking skills and feel like they’re making a difference.

Shortened Learning Curves and Greater Confidence

The statistics on new hire failure rates are sobering. Research shows that 46% of new employees falter within 18 months. In addition, 50% of hourly workers either quit or get terminated within their first six months on the job. Poor performance may be easy to blame because it’s the most visible reason. However, the root causes are often more complicated and exist beneath the surface.

A perceived lack of support and tools to do the work can manifest as subpar performance.
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New call center employees often feel put on the spot when they start handling support requests. Taking calls that don’t go well and searching resources in vain for answers can erode agents’ confidence. When AI is there to pull up applicable procedures and information, employees get the real-time support they need. Staff will learn faster and feel more competent.

Predictable Schedules and Balanced Staff Levels

Although contact centers have used resource planning tools to create schedules for years, they haven’t always been the most accurate. It was common for supervisors to send some agents home early because of excessive downtime. Unfortunately, the opposite scenario — where there weren’t enough employees to handle calls — also occurred.

Dozens of calls waiting in the queues all day or not having enough to do creates a stressful work environment.
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Employees are either dealing with a bunch of angry customers or worrying about whether they’ll earn enough to survive. Resource planning and staffing tools backed by artificial intelligence increase the accuracy of employee scheduling. Agents experience more balanced workloads and predictable schedules, reducing the stress that comes from uncertainty.

Ability to Adapt to Customers in Real Time

Agents face obstacles when customers are upset or won’t let them get a word in edgewise. In such cases, employees have a difficult time reaching a satisfactory resolution or responding appropriately.

A frustrated client might result in a staff member acting in ways that add fuel to the fire. For example, the agent could subconsciously start raising their voice to mirror the customer’s emotion. The call goes south quickly, and the client hangs up in frustration.

Artificial intelligence has the ability to provide real-time interaction analytics and guidance. While it might be obvious that a customer is angry, an agent’s own behavior may not be so apparent to them. AI notifies employees of mannerisms and speech patterns that will lead to lower customer satisfaction. Using instantaneous suggestions, agents can correct their responses. Interaction analytics also alerts employees to more subtle customer sentiments and issue trends.

Personalized Agent Routing

It’s a fact of life that some personalities get along while others clash. This can be due to seeing the world and responding to environmental cues differently.
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Habits, mannerisms, and approaches are subject to interpretation and easily misunderstood. However, it’s communication style variances that often cause the most problems.

For instance, introverts might prefer written communication since it gives them time to sort out their thoughts. But to extroverts, the tendency to send emails rather than talk in person might come across as cold. Likewise, people who focus on the big picture can irritate those who are detail-oriented.

AI routing offers the ability to sync customer and agent profiles. With a greater chance of a match between communication styles and personalities, participants on a call can get off on the right foot.


By nature, being a call center agent means dealing with human and technical challenges. Supporting end users and clients can be rewarding, but some aspects of the job can cause stress and dissatisfaction. Artificial intelligence removes or mitigates sources of frustration, creating a more fulfilling role with career potential.

When AI takes care of routine support requests, provides real-time guidance, removes unpredictability, and personalizes interactions, agents become more empowered. Employees gain confidence, increasing their engagement and investment.
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Equipped to handle the human and technical trials that come their way, contact center agents will deliver better customer experiences.

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