<p>It is clear the pandemic dramatically accelerated the digital transformation of many organizations. However, we now know a digital-first approach is here to stay — an <a rel="noopener noreferrer" href="https://www.ibm.com/thought-leadership/institute-business-value/report/covid-19-future-business" target="_blank" title="IBM report">IBM report</a> found that 55% of companies have made permanent changes to their organizational strategy due to the pandemic. </p>

<p>Customer experience has been no exception, as brands also increased their digital investments to support online activity while in-person interactions were limited.</p>

<p>To support this uptick in online activity, enterprises have turned to technology like artificial intelligence (AI). In fact, <a rel="noopener noreferrer" href="https://www.ibm.com/thought-leadership/institute-business-value/report/ai-customer-experience" target="_blank" title="execs say AI has fundamentally changed how they approach CX">74% of executives</a> say AI has fundamentally changed how they approach CX, with only 13% reporting they are not considering AI within their CX strategy at this time. Clearly, we’re in the next generation of customer service, so what’s next? Will companies scale back, increase or leave their tech investments as is while we settle into the “new normal”?</p>

<h2>Innovation Is Just Beginning</h2>

<p>We’ve seen a lot of innovation in the CX industry over the past few years due in great part to the advancement of AI support for chatbots and automation that have led to frictionless and more personalized customer experiences. The pandemic also showcased the immense value of leveraging AI to automate certain aspects of the customer journey, as those brands that did so have seen an increase <a rel="noopener noreferrer" href="https://www.logmein.com/newsroom/press-release/2019/new-study-finds-ai-widens-the-success-gap-between-cx-leaders--laggards" target="_blank" title="increase in business success">in business success</a>. </p><div class="article-body-ad-placeholder">{"gptAdId":"testId"}</div>

<p>With such clear benefits, brands should keep their foot on the gas by reinvesting a portion of the efficiencies gained into technologies that drive further innovation and even greater efficiencies. In turn, these innovations will continue to elevate the customer experience and improve the bottom line.</p>

<p><strong>Related Article: <a rel="noopener noreferrer" href="https://www.cmswire.com/customer-experience/4-tips-for-taming-the-bias-in-artificial-intelligence/" target="_blank" title="4 Tips for Taming the Bias in Artificial Intelligence">4 Tips for Taming the Bias in Artificial Intelligence</a></strong></p>

<h2>Increased Investment in AI to Support Customer Interactions</h2>

<p>AI has evolved to become a focal point of the customer experience thanks to measurable improvements throughout the customer journey. Nearly <a rel="noopener noreferrer" href="https://www.technologyreview.com/2018/11/14/239924/humans-bots-tension-and-opportunity/" target="_blank" title="executives report improvements in the speed of complaint resolution">90% of executives</a> report improvements in the speed of complaint resolution, and 80% report improvements in customer satisfaction after integrating AI to support customer interactions. </p>

<p>Today’s bots are being developed with AI and machine learning (ML) capabilities, meaning every customer interaction provides more data that supports the customization and personalization of a bot’s responses to be more like a human agent. In particular, investments in data labeling and data annotation are being made to improve the technology's self-learning capabilities, providing companies with a plethora of capabilities like removing human bias from interactions.</p>

<p>Data labeling is an intrinsically “human” element of ML as it relies on humans to label the text, images and videos that teach AI how to function. For example, data labeling can help chatbots understand language, tone and sentiment when interacting with a customer, enabling it to determine when a customer should be transferred to a live agent if it detects frustration. </p>

<p>Additionally, bots will be more widely used to overcome language barriers between brands and their customers. With real-time language translation capabilities, which allow bots to instantly translate the customer’s language, both customers and agents can converse in their preferred language. This allows an agent to service any customer, no matter what language they speak, effectively and efficiently.</p>

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<h2>Tips for Getting Started With AI in CX&nbsp;</h2>

<p>It is clear AI is changing the way we design, build and deliver customer experiences and that will continue to be a key capability for years to come. So, what should brands keep top of mind when integrating AI in their CX operations?</p><div class="article-body-webinars-placeholder">null</div>

<h3>Upskill Your Teams</h3>

<p>A key foundational element for companies to achieve successful AI implementations today and into the future is having digitally-literate employees across its entire organization —&nbsp;not only those who directly "touch" AI projects. The outcome of these learning opportunities shouldn’t be to train the entire organization to become digital architects or UX designers, but to ensure they know what AI can do, and show them the "art of the possible." </p>

<p>This in turn creates a company-wide virtuous circle of innovation and disruption as individuals can proactively identify more ways to use and implement AI in their areas of the business. Offering these courses as self-paced online learning opportunities with a variety of levels for different roles within the organization, with an annual refresher offering updates, can help keep employees’ skills and knowledge current.&nbsp;</p>

<h3>Reduce Bias in AI</h3>

<p>As brands gather more and more insights about their customers and their online habits, AI can help transform these disparate data points into more personalized customer experiences, such as enhancing search functionality and further "humanizing" chatbot interactions. The ability to do so, however, is dependent upon a brand’s ability to source trusted and representative datasets to power the machine learning algorithms behind these applications, otherwise they are at risk of perpetuating societal biases. </p>

<p>Brands can ensure they are mitigating bias in their AI by collecting and labeling the right quantity of data, using a diverse team to do the data annotation and having embedded quality assurance workflows.&nbsp;</p>

<h3>Focus on Continuous Improvement</h3>

<p>How well brands know their customers directly impacts the quality of the experiences they design and deliver, making data a critical element of their success. Just as customer expectations and behaviors are constantly evolving, brands must simultaneously and continuously be updating the datasets they use to train their AI/ML systems to ensure they stay relevant and keep pace. By doing so, brands can create a flywheel effect that generates strong momentum to build upon customer loyalty.</p>

<h2>Outcome of Tech-Forward CX</h2>

<p>The metaverse, Web 3.0, 5G networks and other technological advances are all having distinct impacts on customer experience, and this type of innovation is not going to slow down. Brands will have to keep pace and continually identify new areas of opportunity if they are to remain relevant and competitive. </p>

<p>While many of these concepts may have been a far reach as recently as a year ago, many companies have already incorporated these new capabilities. With our ever-evolving digital-first world, it’s nearly impossible to predict what customer experience will look like five years from now, but one thing that will remain constant over time is the importance of data and the ability to quickly adapt and incorporate new technologies into CX strategies.</p>

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