Will artificial intelligence (AI) replace contact center agents completely? It’s possible, but it won’t happen for a while. If predictions from firms like McKinsey bear out, only 30% of working hours in the U.S. economy could be automated completely, and even that won’t happen until 2030.
What we do know for sure is that the role of the contact center agent is undergoing significant change. AI is playing a definitive role, but not quite the way that so many agents feared when the hype around AI-powered automation first began. Many contact center teams are finding that the future isn’t about replacement by AI, but rather an AI-assisted transformation of the role.
This is how it’s playing out for frontline workers in other contexts, such as manufacturing. At Lenovo’s South Smart Campus, for example, AI is augmenting and accelerating critical functions like quality assurance, training, and production tasks. At the same time, Lenovo seems to be doubling down on the recruitment and development of highly skilled workers.
It’s a similar situation in the contact center, where AI helps to automate manual, repeat tasks, so that human agents can take on more of the high-touch, relational, or complex work that cannot be automated. In addition, AI augments and enhances many of the processes that contact center leaders rely on—to extract insights from data; to put agents in a better position to succeed; and to inform better decision making.
What does this mean for agents moving forward? How can their leadership teams prepare them for the future of work in the contact center, in which AI stands to play a critical role?
How traditional contact center roles are evolving
It’s not easy to keep and develop contact center agents. The average contact center worker makes it 18 months, worsening an already volatile labor market. It should surprise no one that contact center teams are looking for any and all ways to get as much out of their existing staff as possible.
Which is part of the reason the automation of customer service roles isn’t all that bad. Using AI, contact centers can take the added pressure of repetitive tasks—routing customer inquiries, solution lookup, etc.—off the everyday agent’s plate.
AI-powered chatbots and virtual assistants being prime examples. In Generative AI Chatbots vs. Human Agents: Why Contact Centers Need Both, we detail the many ways that contact centers use AI to take pressure off agents with better self-service options or augment the agent experience so that they can do more with less, including:
- 24/7 self-service
- Handling of routine inquiries and FAQ
- Assisting agents during live calls
- Real-time information retrieval (e.g., account lookup)
- Appointment scheduling
- Emergency support
- Automated payments and transactions
- Order status and tracking
- Interactive troubleshooting
With these and other transactional responsibilities effectively automated, the role of a customer service agent can center around :
Remote and hybrid work productivity
Remote or hybrid work environments can help contact centers save on operating costs—if they’re executed properly. Without proper training, oversight, and support, agents can flounder, leading to decreased productivity and increased agent attrition. Despite the prevalence of remote work environments, only 30% of managers have the training they need to lead hybrid teams.
Moving forward, contact centers must make their hybrid work environments as productive as possible without leaving agents high and dry. Platform integrations help, as does the integrated use of AI enhancements throughout the agent experience. The focus should be on freeing up agents to train and refine their remote work proficiency in this new normal.
Collaboration
High-touch customer issues often require high-touch solutions. AI can free up agents to participate in collaborative problem solving, such as the service swarming—aka intelligent swarming—method.
In a service-swarming model, agents can collaborate with relevant subject matter experts on a given issue, often arriving at the most viable solution much faster. When integrated with Salesforce, Webex Contact Center supports such cross-organizational collaboration, which can result in a number of benefits:
- Better knowledge sharing and skills development
- Improved inter-team cooperation and morale
- More scalable automation
Customer advocacy
Customer service agents play a critical role in driving customer satisfaction, loyalty, and even brand advocacy. New use cases for contact center AI can help agents develop in this area, moving beyond simply resolving customer issues to becoming trusted advisors who build relationships, understand customer needs, and proactively recommend solutions.
Data-driven decision making
Even an expert’s best guess can be wrong. Now, contact center leaders have numerous opportunities to integrate AI-powered decision-making into every agent’s day-to-day activities. Perhaps the best example of this is Einstein Next Best Action from Salesforce, which enables agents to personalize interactions and proactively address customer concerns.
What agents need to thrive in the next new normal
Beyond the basics of an agent’s job function, what core skills should contact center leaders look for—and develop—in their agents?
Technical proficiency
Despite a shift to a more relational role, customer service agents must be technically proficient. This includes familiarity with AI-powered tools, data analytics platforms, and omnichannel communication solutions. Of course, by combining much of this technology into a single interface or app, can significantly reduce the proficiency and training required by a cross-platform/app approach.
Salesforce identifies a few other areas of technical expertise that most customer service agents will need:
- CRM and agent consoles
- Ticketing systems
- Chat and voice software
- Collaboration tools
- Knowledge management systems
Multitasking
Contact center teams would do well to limit so-called context switching for their agents: it can save time and influence important performance metrics, such as average handle time. Yet, all agents interact with multiple tools and tasks at once. Knowing how to multitask efficiently is a must. Rather than relying on more experienced agents to share best practices, make them part of agent training from the get-go.
Adaptability and continuous learning
Technology and customer needs evolve fast, and agents need to do all they can to keep up. Agents need avenues for learning and developing their adaptability, ideally without disrupting their day-to-day workflows. Consider an integrated training platform that offers career coaching, certificate programs for specific technical skills, and AI simulations.
Creativity and critical thinking
With many of the pre-scripted responses now automated, agents must be able to find creative solutions for complex customer situations. This starts with a closer understanding of each customer relationship (which AI can enhance).
Collaboration helps to Ideally, assigning cases to the right experts would be done at the IVR level; when that doesn’t happen, your agents need to know who (a specialist, for example) is best suited to resolve a particular problem.
Strong communication and interpersonal skills
Agents have always needed strong empathy, active listening skills, and clear communication. In an environment where so many AI interactions take place, people expect more of the human agents they interact with. Tone recommendations can only do so much. Focus on developing the soft skills that underpin the quality of communication that today’s customer looks for.
5 strategies for preparing your contact center workforce
As for how to equip agents with the necessary skills to succeed in the evolving landscape, consider these five strategies:
1. Invest in upskilling and reskilling
Approximately 87% of companies are experiencing some form of talent gap. For example, 70% of managers don’t have the training they need to manage hybrid teams. Across the board, customer service teams will need viable programs for upskilling and reskilling, especially as the labor market continues to slump.
2. Foster a culture of learning
Create a learning environment that encourages continuous improvement, exploration of new technologies, and knowledge sharing within the team. This can include:
- Allocating time for self-led learning
- Integrating coaching and mentorship
- Rewarding curiosity, success stories, and achievements
- Connecting learning initiatives to performance metrics
- Investing in modern learning platforms
3. Empower agents with (the right) technology
Salesforce Flows is a good example. With Flows, contact centers can “orchestrate parallel multi user, multistep workflows” that are driven by AI-powered automation. Perfect for making case management workflows a lot more efficient.
4. Evolve evaluations
Moving forward, many contact center teams are evaluating their agents based on the metrics that best align with overall business objectives. While traditional metrics associated with agency efficiency still matter, the ones tied to customer experience are taking center stage.
Look for experience-oriented metrics, such as lifetime value, sentiment, CSAT, NPS, and Cost to Serve, to become more prominent in the evaluation of agent performance.
5. Prepare contact center supervisors
Let’s not forget contact center supervisors. Often, supervisors are given the reins of service teams without adequate managerial training. Even with the best training, most managers are expected to handle 51% more responsibilities than they can possibly manage. Like agents, supervisors need ongoing training and development to succeed in the future of work.
Toward a new workplace model in the contact center
In its extensive exploration of future workplace trends, Deloitte recommends that business leaders “deliberately design the experience in service of outcomes and value.” In the contact center, nearly all outcomes and value come down to one thing: the customer.
This helps us understand where new tech, like AI, fits into the changing service landscape—not as a replacement of human agents, but as a valuable tool that empowers them to focus on the human aspects of customer service. The ability of agents to deliver a high standard of relational value is more important than ever.
What lies ahead for customer service teams is an opportunity to embrace professional growth, skill development, and career advancement—to design a new workplace model that puts agents in the best position possible to help customers win.
