The emergence of generative artificial intelligence promises to bring significant efficiency and productivity gains to the call center industry. However, in a field where human interaction and empathy are crucial, the adoption of new AI tools brings both exciting prospects and notable challenges.
As call center leaders and customer service agents adapt to this new AI-powered landscape, it becomes crucial to evaluate AI tech with a discerning eye and a critical lens. Here are three ways that call centers should evaluate AI tools for their customer service teams.
Look Beyond the Marketing
AI tools for customer service often come with bold marketing claims promising to improve efficiency and customer satisfaction. However, not all AI tools live up to their marketing hype. Failing to do your due diligence can lead to wasted resources and disappointing results.
Call centers should conduct thorough research and seek real-world evidence of AI tools' effectiveness. This means digging deeper into case studies, customer testimonials, and independent reviews to gain an accurate understanding of how tools perform in practical scenarios.
Organizations should be wary of exaggerated promises and buzzwords that obscure the true capabilities of an AI solution. By adopting a skeptical mindset and conducting thorough due diligence, call center teams can avoid being misled by marketing tactics and select AI tools that genuinely enhance their customer service operations.
Assess Integration Capabilities
One key consideration when evaluating AI tools for customer service teams is the ability to seamlessly integrate them with existing call center technologies. It's often more practical and cost-effective for organizations to adopt AI solutions that integrate with their existing systems than to replace them entirely.
Look for AI tools that offer robust integration capabilities or use plug-ins to seamlessly connect with popular call center software and platforms. This strategy reduces downtime and disruption during implementation by maintaining familiar workflows and easing the transition for agents.
AI solutions integrated with existing systems can use existing data to provide more personalized and contextually relevant customer service. This allows call centers to maximize the value of existing technology investments while harnessing the power of AI to drive improved customer experiences.
Compare Expectations vs. Reality
While AI can certainly streamline routine tasks such as answering common questions or categorizing queries and summarizing conversations, it should not be seen as a replacement for human agents. Instead, AI can free up agents to address more complex issues that require nuanced problem-solving and empathy.
It's important to maintain realistic expectations regarding these tools' limitations and supervise the outcomes. Testing AI tools in the wild is essential to fully understanding expectations vs. reality. In our organization, we tested chatbots over the holidays when we knew call volume and inquiries would be low. Ultimately, we found the technology wasn't as polished as we had hoped, and thus opted to wait for it to mature further to meet our needs.
In summary, it's important to remember that AI tools geared toward call centers are not a one-size-fits-all solution and their effectiveness varies by specific needs and contexts.
Organizations can successfully implement effective AI solutions by carefully evaluating AI capabilities, testing them in real-world scenarios, and ensuring they align with business goals. This strategy allows human agents to remain central to delivering exceptional customer service while enhancing operational efficiency.
Victor Obando is vice president of customer solutions at ActivTrak. He brings nearly two decades of leadership and technical skills across enterprise software, cloud, networking, and information security to ActivTrak, with a successful track record in building and running a team of solutions architects and systems engineers to support global customers and partners.