FEATURE
Today, AI agents are utilized in contact centers to streamline routine tasks and enable faster response times. However, despite growing adoption, a consumer trust gap persists. According to our research, while 59 % of consumers are open to using AI chatbots for quicker resolutions, 30 % still question their accuracy.
And the margin for error is thin with more than a third of customers( 36 %) reporting that a single bad experience would deter them from using chatbots again.
To close this trust gap, brands must go beyond simply deploying automation: they must craft experiences that are reliable, intuitive, and human-centric. This means prioritizing accuracy, clear communication, and seamless handoffs to live support agents when needed. The success of automation hinges not just on functionality, but on engagement, design, and transparency.
Beyond trust, there’ s also growth potential in the scope of interactions automation can handle. AI today excels at routine service needs, including FAQs, password resets, and appointment scheduling, but the real opportunity lies in scaling up to more complex, higher-value engagements. Specifically, advanced troubleshooting, proactive issue resolution, intelligent upselling, and deeply personalized guidance.
However, what holds automation back from this next leap is a familiar challenge: the lack of emotional intelligence and contextual reasoning. These human qualities are still critical when dealing with sensitive or nuanced customer needs. Until Agentic AI advances to the point where it can mimic these capabilities reliably, human and AI collaboration will remain essential.
Moving forward, organizations must design AI not just to answer questions, but to understand people, their context, their preferences, and their emotions.
NV: There’ s tremendous potential for growth in AI and automation, but several key barriers are preventing organizations from fully realizing that promise.
One of the biggest challenges facing enterprises today is their existing infrastructure. Effective AI integration depends on robust APIs and real-time access to clean, connected data.
Yet many organizations are still operating with a patchwork of legacy systems and siloed solutions: a situation we often refer to as a“ frankenstack.” These fragmented environments limit AI’ s ability to deliver accurate, timely insights and actions.
This kind of disjointed architecture leads to operational inefficiencies, isolated data pools, and inconsistent CXs. Worse, layering AI or automation on top of these systems often magnifies the problems. Take chatbots, for example. Without access to unified customer data, they provide generic or inaccurate responses, which only frustrates customers rather than improving service.
As AI and automation continue to play a more central role in customer engagement, a unified AI platform becomes critical. It ensures smooth handoffs between automated and human-led interactions, streamlines workflows, and delivers the consistent, personalized experiences customers expect.
WHAT ARE YOUR RECOMMENDATIONS WHEN CHOOSING, DEPLOYING, AND USING INBOUND AND OUTBOUND CUSTOMER CONTACT APPLICATIONS?
KMN: The most important recommendation is to shift the mindset from choosing individual applications to selecting a platform: specifically, one designed for Agentic AI.
Traditional customer contact applications were built around static workflows and point solutions. But as AI becomes more capable, the future lies in dynamic, intelligent systems where AI Agents can reason, act, and collaborate to automate complex journeys. That requires a platform with multi-agent orchestration at its core.
That said, transformation doesn’ t need to happen all at once. Organizations should start by identifying high-value use cases where automation can deliver quick wins: whether that’ s automating outbound appointment reminders, assisting agents during after-call work, or improving identity verification. From there, AI agents can be added, refined, and scaled gradually based on performance and business need. Equally important is choosing a solution that makes it easy to manage and govern AI, with tools for testing, oversight, and human-in-the-loop controls. The right platform won’ t just support today’ s use cases; it will evolve with the business. The companies that succeed will be those that move with purpose, align around value, and build on a foundation designed for what’ s next.
SP: When choosing, deploying, and utilizing inbound and outbound customer contact applications, it’ s essential to go beyond simply choosing a platform that offers automation. Instead, I recommend companies take a more strategic approach, evaluating how their customers interact, what they expect, and where human connection still matters most. For example, organizations in high-trust, high-stakes industries like healthcare or financial services must prioritize solutions that enhance and empower human agents, rather than fully replace them. These interactions often involve emotional nuance, sensitivity, compliance considerations, and personalized problem solving that automation alone can’ t reliably deliver.
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