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\nRight now, generative artificial intelligence (AI) tools like ChatGPT are making headlines \u2014 and in some cases, being used to write those headlines \u2014 leading to excitement and speculation about what the future holds. <\/strong><\/p>\n Some articles focus on uncertainty and anxiety: that AI is not yet sophisticated enough to be trusted with important decisions or inputs, or that even a small human error in input could result in major harm. Others fall closer to the opposite end of the spectrum, and the alarming concern that AI may soon evolve past our understanding into existentially threatening territory.<\/p>\n These fears are understandable. Watching fully formed sentences appear in real-time before your eyes can feel uncanny. But these fears are misplaced. AI remains a reflection of us, trained by large language models to react in limited ways to specific situations using human knowledge that humans programmed.<\/p>\n By and large, it\u2019s still humanity at the center. And while it may be less exciting than some of the sci-fi situations being concocted, the human aspect is really where we should be focusing the bulk of our concern.<\/p>\n What is Generative AI?<\/strong><\/p>\n Artificial Intelligence is a nebulous term, but generally speaking, AI is a type of tool that recognizes patterns in a vast pool of data and then responds to or draws conclusions from those patterns. Generative Artificial Intelligence<\/em> is a term for algorithms that can be used to generate new content. Generative AI can recognize and classify those same similarities in a vast pool of data, and then generate content like text, audio, code, images, simulations, and even videos based on those patterns \u2014 faster, more efficiently, and at scale.<\/p>\n AI doesn\u2019t absorb information and make \u2018decisions\u2019 in the same way that a human does; the conclusions it is capable of drawing have to be pre-programmed or inferred through multiple examples. This means that it is exceptional at recognizing patterns in a vast pool of data, one that would be too massive and complex for a human to do in the same amount of time, but less gifted at improvising, or reading in between the lines.<\/p>\n How AI Can Improve Customer Experience<\/strong><\/p>\n The expectation customers have today is hyperresponsiveness: being known, valued, and helped in the right way at the right time. Contact centers are where a lot of these customer interactions take place. Often, these contact centers are the main point of contact that customers have with a brand, and the frontline for trying to solve a problem.<\/p>\n Agents in these centers are often expected to juggle up to eight different channels to provide service on the customer\u2019s channel of choice, and tie together a story from disparate sources of data. Many of these processes are manual and time-consuming. Between the attrition rates at contact centers, long wait times, the great resignation, and other challenges in the industry, a tool that can recognize patterns in disparate sources of data and respond faster and more efficiently seems like a dream come true.<\/p>\n AI is great at tasks that are repetitive or mundane, like answering simple questions or compiling information into a digestible format. Generative AI can be foundational technology for convenient self-serve options. By automating some parts of the customer journey, you can reduce the number of calls that live humans have to take \u2013 calls that are costly, time-consuming, and easy to automate. Additionally, AI tools can empower live agents with information they need to perform better \u2013 like anticipating why a customer might be calling based on previous call patterns, or quickly providing background information gathered from across different channels to help the agent piece together what might be happening in a customer\u2019s account. This can help your employees become more efficient and more effective and narrow their focus on the part that AI can\u2019t replicate: the human connection.<\/p>\n AI is a powerful CX-enhancing tool, but it\u2019s still a tool, best used as an assist to human workers. By using AI to automate tasks on the front end (repetitive questions) and tasks on the back end like (mundane paperwork) you can save time, save money, and simultaneously improve both the customer and employee experience.<\/p>\n What AI Can\u2019t Replace<\/strong><\/p>\n When it comes to traditional customer experience with human agents, most brands have an extremely high standard. In every experience and every interaction, brands are aiming for perfection. Obviously, consistent perfection is unattainable, but having an ideal to aim for and a baseline to measure by makes it possible to continually iterate processes, retrain and encourage employees, and continually learn how and where to improve.<\/p>\n This is one thing that AI won\u2019t change. While it\u2019s new and exciting and endlessly promising, generative AI isn\u2019t a magic cure or shortcut for solving your CX woes \u2013 in fact, applying it thoughtlessly can make some processes worse.<\/p>\n If you\u2019re considering adding AI to your CX toolkit, you first need to answer two questions:<\/p>\n The first principle of Google\u2019s Recommended AI Practices is around using a human-centered design approach: The way actual users experience your system is essential to assessing the true impact of its predictions, recommendations, and decisions. The same could be said about your CX. It doesn\u2019t matter how sophisticated your technology solutions are if you don\u2019t first understand what your customers want and where the gaps are. For now, this remains one area where artificial intelligence can\u2019t replace human understanding.<\/p>\n\n