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What Enterprise AI Is Changing for CX and What It’s Not
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As AI technology evolves, it can be confusing to keep track of what it is, what it can do, and (perhaps most importantly) what it can’t do. Generative AI and enterprise AI are both applications of artificial intelligence, but with a different focus. While generative AI is focused on consuming and creating content—summarizing and enhancing text or creating images and video—enterprise AI is focused on using data from business systems to identify patterns and optimize and automate processes.
It’s enterprise AI that is quietly transforming the customer experience (CX) by streamlining interactions, personalizing services, and integrating intelligent algorithms into customer management systems. There’s immense potential there, but recognizing what enterprise AI is changing and what it cannot is critical for businesses looking to maximize their technology investments.
Replace the Human Touch? No.
Despite its capabilities, AI can’t replicate the empathy, creativity, and emotional intelligence aspects of a customer interaction. Customers still value the kind of authentic connections and personalized attention that only human interactions can provide, making it critical for businesses to balance AI usage with human touchpoints. While AI systems are getting better at simulating human-like interactions, they still struggle with things like sarcasm, and many situations require nuanced judgment and emotional understanding that only humans can provide. Complex or highly emotional issues and complaints often demand human intervention to ensure satisfactory resolution, maintaining a balance between technology and human oversight.
Enhance Customer Interactions? Yes.
One of the most significant transformations that enterprise AI has brought to CX is the enhancement of customer interactions. With AI-driven chatbots and virtual assistants, businesses can offer round-the-clock support, giving customers immediate responses to their inquiries—but the shift from generative AI to enterprise AI means being able to do more. Enterprise applications of these tools can analyze customer data to provide personalized recommendations, predict issues, and even resolve simple complaints efficiently. This not only improves customer satisfaction, but also drives engagement by creating seamless, intuitive experiences. What’s more, when developed and integrated intelligently, chatbots and virtual assistants can even be proactive, reaching out to customers before they know there’s a problem.
Achieve Behavioral Equity? No.
While older generations may approach new technologies and data with a degree of trust, expecting accuracy and transparency, younger generations are inherently more skeptical and adept at identifying biases and manipulations. This discrepancy leads to very different paths in how AI technologies are embraced and utilized. Furthermore, younger individuals are often more agile in adapting to the rapid changes in digital communication environments, employing social platforms and AI-driven tools tactically to sift through and counter biases. AI can’t yet understand these generational perspectives, and while serving just one path is certain to alienate one group, trying to find a middle ground or compromise risks alienating both.
Provide Data-Driven Insights? Yes.
Enterprise AI empowers companies with data-driven insights, enabling more informed decision-making. By processing vast amounts of data, AI systems identify patterns and trends, helping businesses fine-tune their strategies. This capability allows companies to understand the diversity of customer preferences and behaviors, providing personalized experiences that resonate with individual users. Furthermore, predictive analytics can forecast future trends, allowing businesses to stay ahead of market demands.
Eliminate or Overcome Bias? No.
AI systems are powerful, but they’re susceptible to the biases present in their underlying data. This includes things like:
- Sampling bias: AI facial recognition models trained on images of people with lighter skin tones struggle to accurately recognize dark or olive tones.
- Label bias: AI sentiment analysis perpetuates the tendency of users to label content from certain groups negatively, regardless of the content.
- Confirmation bias: AI models used to predict customer buying patterns based on data from certain demographics disproportionately target those groups.
- Cultural bias: AI models trained primarily on the customs of one culture are more prone to making incorrect or unfair decisions with other cultures.
Businesses must acknowledge that enterprise AI can’t wholly resolve for issues related to algorithmic bias and privacy concerns. Maintaining fairness and transparency in AI-driven processes is an ongoing concern that organizations must address to foster trust and credibility among customers.
Reduce Operational Costs? Yes.
Implementing AI in CX also leads to significant cost reductions. Automating routine tasks and processes minimizes the need for extensive human intervention, freeing up resources and reducing operational expenses. For example, AI-powered IT solutions can handle multiple customer queries simultaneously, revolutionizing traditional contact centers by reducing wait times and lowering labor costs. As a result, companies can allocate their resources more efficiently, focusing their personnel on strategic initiatives that drive growth.
Balance Innovation with Simplicity? No.
When pursuing cutting-edge AI solutions, organizations must remain grounded in what truly impacts customer satisfaction. Overcomplicating the user experience with too many AI features can overwhelm customers, detracting from the overall service quality. Just because you put a technology out there doesn’t necessarily mean that it’s going to make the CX journey easier or more satisfying. Striking the right balance between leveraging innovation and maintaining a simple, enjoyable customer journey is crucial—and it’s entirely a human judgment call that AI can’t (and shouldn’t) control.
Looking Ahead
As enterprise AI continues to evolve, its impact on CX will undoubtedly grow. Businesses striving to benefit from AI’s potential must remain agile, embracing opportunities for improvement while acknowledging the limitations. By focusing on delivering pure, unbiased data and fostering innovation with conscience, companies like Concentrix—with its growing catalog of pre-trained enterprise AI assistants available in iX Hello—can offer meaningful solutions that genuinely enhance the customer experience. Those companies who invest in partnerships built on an understanding of the dynamic interplay between technology and human needs are the ones who will navigate the evolving CX ecosystem with confidence, ensuring that innovation serves as a force for good in the digital age.
Sumit Tamhane
Director, Project Management Office
Robert McMillan
Lead Program Manager, Project Management Office
