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          Beyond ChatGPT: The future of CX AI and why brands should care

          by Elizabeth Tobey
          September 11, 2024
          Share

          Customer experience (CX) is evolving rapidly, with AI playing a transformative role. In a recent webinar, I discussed the heart of this transformation with Christina McAllister, senior analyst at Forrester. Generative AI has the potential to revolutionize how brands interact with customers.

          In this blog, we’ll delve into the future of CX AI, explore key trends and discuss why brands should care.

          Setting the stage: Choreographing generative AI

          Every year, Forrester publishes a report outlining the trends in the contact center space. This year, the focus is overwhelmingly on generative AI. The question isn’t just how to deploy it, but what foundational changes are necessary to support it. Just like a dance performance requires rigorous rehearsals and perfect coordination, integrating AI into CX demands meticulous planning and precise execution. Let's explore three major themes emerging in the CX AI landscape and understand why brands should care.

          1. Generative AI igniting overhaul in contact centers

          Generative AI is prompting a significant overhaul in long-neglected areas of contact centers. Enterprises are caught between the fear of missing out (FOMO) and the fear of messing up, leading to a renewed focus on strengthening shaky foundations.

          Key points:

          • Employee productivity: AI is being used to enhance productivity, particularly for contact center agents who are heavily measured and monitored. Generative AI can streamline workflows, reduce response times, and improve overall efficiency.
          • AI readiness: Companies must invest in training their employees to work alongside AI systems, understanding when to question AI results and how to use these systems ethically.
          • Strong knowledge practice: AI needs to be anchored in trusted knowledge. Without solid foundations, AI can produce inaccurate or misleading information.

          2. Leaders charting course for an AI-augmented era

          Leaders must navigate the complexities of integrating AI into customer-facing roles. Forrester predicts that 50% of large global firms will experiment with customer-facing generative AI in 2024. While many companies start with internal applications, expanding to customer-facing scenarios offers significant opportunities.

          Key Considerations:

          • Human-in-the-loop: Maintaining a human presence in the loop ensures AI can be effectively managed and refined. This coaching helps with the AI performance by correcting errors and ensuring synchronization.
          • Customer interaction: The limited frequency of customer interactions (2-3 times a year) highlights the importance of making each interaction meaningful. Automating customer conversations without losing the personal touch is crucial.
          • AI strategies: Companies can embed AI in three main ways:
          • Analytics for insights: Gaining deep insights into customer behaviors and preferences.
          • Automation for efficiency: Handling high-volume, low-complexity tasks to free up human resources.
          • Augmentation for quality: Enhancing human capabilities in complex scenarios where personal touch adds significant value.

          3. Reimagining the contact center

          AI offers a unique opportunity to reimagine the contact center, balancing the roles of AI and human agents for maximum impact. This involves reassessing workflows, tools, and metrics to better equip agents for collaboration with AI.

          Important Steps:

          • Evolving agent workspaces: Modernizing agent tools to facilitate human-AI collaboration.
          • Understanding workflows: Identifying and streamlining workflows where agents spend excessive time on non-value-adding tasks.
          • Fostering new skills: Investing in emotional intelligence (EQ) and AI knowledge (AIQ) to prepare agents for future roles.

          Reevaluating metrics: Considering how AI integration changes traditional metrics like average handle time, focusing on customer experience and agent efficiency.

          Why brands should care

          The integration of AI into CX is not just about technology; it's about fundamentally reshaping how brands interact with their customers. Brands need to care because:

          • Competitive advantage: Early adopters of AI will have a significant advantage in efficiency, customer satisfaction, and loyalty. They will be able to offer more personalized and responsive customer experiences, setting themselves apart from competitors.
          • Customer expectations: As AI becomes more prevalent, customers will expect seamless, intelligent interactions. Brands that fail to meet these expectations risk falling behind.
          • Operational efficiency: Properly implemented AI can drastically reduce costs and improve operational efficiency, freeing up human agents for more complex, value-adding tasks.

          Food for thought: A framework for AI integration

          There is no single answer to where AI should be implemented; it varies across industries and even companies within those industries. Here’s a framework for weighing decisions about where AI is best suited, where AI self-service excels, and where enhancing the human connection is paramount.

          Strategic context

          Consider the macro view—opportunities and constraints influencing what you can do:

          • Business model: How you make money and retain customers.
          • Regulatory compliance: Data handling capabilities and limitations.
          • Competitive landscape: Direct and indirect competitors shaping customer expectations.

          Contact center dynamics

          Different organizations will have varying mixes of:

          • Interaction volume and frequency: How often and how many interactions occur.
          • Complexity of interactions: How challenging interactions are to resolve.

          For instance, a company with high volume, frequent interactions, and low complexity may prioritize automation. Conversely, a company with low volume, infrequent, but complex interactions may focus on human augmentation with AI.

          Practical applications and considerations

          Implementing AI in the contact center is a complex process that requires thoughtful planning and execution. Here are some practical applications and considerations:

          AI for self-service

          • Chatbots and virtual assistants: Use AI to handle routine inquiries and provide quick responses to common questions. This reduces the workload on human agents and provides customers with instant support.
          • Interactive voice response (IVR): Implement AI-driven IVR systems to guide customers through troubleshooting processes or direct them to the appropriate department.

          AI for agent assistance

          • Real-time assistance: Provide agents with AI-driven suggestions and information during customer interactions. This can help agents resolve issues more quickly and accurately.
          • Automated summarization: Use AI to generate summaries of customer interactions, reducing the time agents spend on post-call documentation.

          AI for analytics and insights

          • Customer sentiment analysis: Use AI to analyze customer interactions and gauge sentiment. This can help identify areas for improvement and tailor responses to better meet customer needs.
          • Predictive analytics: Implement AI to predict customer behavior and anticipate issues before they arise, allowing for proactive support.

          Future trends in CX AI

          As AI technology continues to evolve, new trends will emerge in the CX space. Here are a few to watch:

          Hyper-personalization

          AI will enable hyper-personalized customer experiences by leveraging vast amounts of data to tailor interactions to individual preferences and behaviors. This will create more meaningful and satisfying customer experiences.

          Advanced emotion AI

          Emotion AI, which can detect and respond to customer emotions, will become more sophisticated. This will allow for more empathetic interactions and better customer support.

          Seamless omnichannel experiences

          AI will facilitate seamless omnichannel experiences by integrating customer data across various touchpoints. This will ensure consistent and cohesive interactions regardless of the channel.

          AI-driven knowledge management

          Advanced AI systems will enhance knowledge management by continuously learning from interactions and updating knowledge bases in real time. This will ensure that both AI and human agents have access to the most current and accurate information.

          beyond-chatgpt

          Embrace future of CX AI

          Mastering the integration of AI in CX is essential for brands aiming to differentiate themselves. Those who successfully blend human touchpoints with AI-driven efficiency will lead in customer satisfaction and loyalty. Embrace the future of CX AI to create exceptional customer experiences that stand out in a competitive market.

          Listen to the full webinar and the complete series on-demand here!

          About the Author

          Elizabeth Tobey

          Elizabeth Tobey is the Vice President of Marketing at NiCE. Previously, she held leadership roles spanning marketing, communications, community, and CX departments at video game, social media, and cloud platform technology companies in both the B2C and B2B spaces. Over the course of her career, she has focused on identifying new and effective ways to create meaningful dialogue between a brand and its customers, and on developing products and programs that are built on relationships, outcomes, and impact.

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