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TELUS International, in partnership with Statista, surveyed 250 enterprise leaders to explore where they plan to invest in digital customer experience (CX) technology in 2023. Uncover the results.

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Survey results: Digital customer experience priorities for leaders in 2023

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Generative AI is a type of AI that can be used to generate new content such as text, images, audio, video, code or synthetic data. Discover exactly how generative AI works and what you can do with it.

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Generative AI 101

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The future of content moderation: Strategies and tools for 2023 and beyond

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In this IDC Info Snapshot, learn about the three key pillars for any successful AI implementation and the advantages of partnering with a trusted advisor to create and deliver your AI vision.

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Delve into new insights about customer experience outsourcing from a survey of 712 enterprise executives with strategic decision-making authority.

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The Importance of Natural Language Processing for Non-English Languages

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Learn how a leading technology client leveraged TELUS International’s AI Data Solutions to build a multilingual dataset that helps researchers scale natural language understanding technology.

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"In the pursuit of creating truly remarkable customer experiences, we must embrace the power of generative AI," explains Alexander Grayson, founder and CEO of AI-led start-up, Quixl. "It allows us to think differently and break free from the constraints of conventional wisdom, propelling us into a realm of unimaginable possibilities."

Grayson makes a convincing case for the role of artificial intelligence (AI) in the future of digital customer experience (CX).

There's just one problem. Neither Alexander Grayson, nor Quixl, exist.

The Silicon Valley-based tech firm and its enigmatic founder are a construction of OpenAI's ChatGPT-4, one of many wildly popular generative AI applications on the market today, like Google's Bard and Amazon's Bedrock. With some prompt engineering, the technology swiftly took up the role of a successful founder of a start-up with an ambiguous name. Alexander Grayson even has a favorite food (sushi) and a reason for loving it so much ("it combines simplicity with artistry").

Fake though he may be, Grayson's belief in the power of generative AI (or "GenAI") is shared by many real people at very real organizations. Take AWS' Vice President of Generative AI, Vasi Philomin, who, in a recent interview with TechCrunch, said, "We think every application out there can be reimagined with generative AI."

Researchers are aligned too. In fact, Grand View Research projects that generative AI's market size will reach over $109 billion by 2030 thanks to an expected compound annual growth rate (CAGR) of 35.6%.

The market growth and pace of innovation is making artificial intelligence and bot technology impossible to ignore for digital customer experience decision-makers.

Tip: If you're looking to learn more about the underlying technology, give our Generative AI 101 article a read.

Generative AI and the customer experience

There's no question that generative AI is capturing the collective imagination.

But brands aren't daydreaming. There are real, powerful digital customer experience applications being explored, deployed and iterated upon in the here and now. Let's look at some of those applications and their benefits.

The frustration that comes from finding the boundaries of a chatbot's knowledge may soon be a thing of the past. Chatbots that are powered by generative AI aren't just trained on expansive datasets — they learn from every customer interaction, always improving in their ability to understand prompts and respond appropriately.

Through TELUS International iLabs, our R&D initiative to design and build disruptive solutions for customer interactions, we have long been developing proprietary chatbot solutions leveraging Natural Language Processing (NLP) and its other utilitarian tools, including speech recognition and semantic understanding, for our clients. Generative AI technologies represent a huge, exciting step forward in this ongoing evolution to develop even better bots that are more conversational, can answer follow-up questions, admit mistakes and even reject inappropriate requests. These technologies are being built into our award-winning customer-facing bot — intelligent TELUS International Assistant.

With all that said, there will always be customers who want to speak to a human being out of preference, or because they struggle with traditional self-service methods for one reason or another. A smart approach involves getting help to deliver the best chatbot experience possible, but to have an empathetic team of human agents ready to step in and support when necessary.

According to a recent report from CB Insights, social media and marketing content is the top category for investment across the generative AI landscape.

Importantly for digital CX, this isn't just about generating content. It's about generating personalized content at scale.

Personalization can have a strong, positive influence on customer loyalty. In fact, research from Deloitte demonstrated that those who effectively deliver personalization improved customer loyalty at a rate 1.5 times faster than those at a nascent stage with personalization.

In terms of generative AI, personalization can be about both specific product recommendations and messaging. No noise, no fluff, but rather, recommendations and responses tailored to your unique needs and interests. Per a recent Customer Service Manager article, generative AI can create "intelligent, creative solutions adapted precisely to an individual or group's needs with an accuracy that was never before possible."

Introducing an ever-expanding list of applications

Thinking back to the words of AWS' Philomin, it is evident that generative AI is likely to introduce a seemingly endless list of use cases. In the context of digital CX, the future looks bright. A few of the possible applications might include:

Optimizing agent onboarding: With generative AI, learning could be customized at the individual team member level based on the monitoring of an agent's signals as well as predictive analytics.

Predicting customer retention risks: By analyzing customer signals and related patterns, generative AI could identify customers with declining engagement and use that information to prompt a proactive, corrective course of action.

Improving call routing and prioritization: The goal here is to get calls to the right person more quickly, and to prep agents with the information they need to support. In this case, generative AI would be used to detect customer sentiment and act accordingly.

As was the case with the agent-facing automation that preceded it, generative AI looks poised to reduce agent effort and make other significant improvements for digital CX delivery.

AI-powered chatbots aren't just for customers. Brands looking to evolve their customer experience operations with generative AI can empower their team members with effort-saving, agent-facing bots.

With adequate internal training data and a thoughtful strategy, these technologies can comb through your knowledge bases, customer data and more in order to help agents in answering specific, contextual questions. Better still, generative AI can be used to write new external knowledge base content to equip your customers with the answers they were looking for right from the off.

In both the short- and long-term, these capabilities will only grow in significance as improvements in customer-facing self-service tools alter the types of queries that get sent to customer service teams. The questions sent on will have a higher degree of specificity and complexity, and there will be an expectation that human agents will bring clarity. And when those agents need clarity themselves, they'll turn to agent-facing bots.

"We have the first early results on productivity from these tools," shared Ethan Mollick, an associate professor of management at the Wharton School of the University of Pennsylvania on a recent episode of the HBR IdeaCast podcast in which he spoke about generative AI experimentation.

Mollick went on to reference two controlled studies, one focused on business writing and another focused on coding. Both studies found that even though the test subjects were not trained on the systems, their use of generative AI tools resulted in "30 to 50% improvements of productivity." Adding context, Mollick supplemented that an American manufacturing plant adding steam power in the 1800s had realized a 25% increase in productivity.

There's one additional sound bite from Mollick that helps to focus the application in the CX context: "You basically gained a teammate, everybody did."

For support agents, that help can be deployed in a number of ways to save serious time, including automating: the drafting of scripts based on different personas and use cases to present up-sell and cross-sell opportunities; the creation of post-interaction transcripts and the summarizing of those transcripts to identify essential elements; and the publishing of knowledge base content to effortlessly maintain and add to your knowledge management system.

Thanks to its efficiency-boosting qualities, the strategic deployment of automation can have a positive effect on agent engagement. With GenAI tools capable of handling time-consuming and repetitive tasks, agents can focus on the aspects of their roles that bring out their best human qualities.

There are already signs that this is the case. In his podcast interview, Mollick explained that the aforementioned studies showed that the test subjects were "happier because they offload the worst parts of their job and get to do the interesting, creative stuff."

Speaking on the positive collaboration between humans and generative AI tools in an interview with ZDNET, Michael Maoz, Senior Vice President of Innovation at Salesforce explained, "The first step is to make it clear that AI, like automation and analytics, is meant to make the lives of people easier," and later added that "the only way to turn AI into a net-positive is to make it work as a support tool that makes the life of the employee more productive and rewarding."

For agents, the technology is poised not only to cut out tedious tasks, but to maximize their ability to deliver authentic, empathetic and personalized help to the customers who need it.

Partner with a digital CX leader to navigate risks

Don't be fooled by the likes of Alexander Grayson or Quixl. Generative AI has immeasurable potential for improving the digital customer experience, but it is not without risks.

For one thing, you don't want to leave the entirety of your digital CX on autopilot. There are already public instances where generative AI tools have responded with false, misleading or unsettling information. In the CX arena, that can have a costly impact on customer trust and brand reputation.

There have also been headlines circulating about companies inadvertently leaking confidential information through the use of publicly available generative AI tools. Missteps like these pose immense reputational, security, data privacy and business risks, underlining the importance of understanding the technologies you are interacting with.

With the pace of AI innovation, keeping up can be a challenge. To grasp and account for the associated risks, put your trust in partners with earned expertise.

To learn more about how TELUS International can help you take your digital CX to the next level with AI-powered technology, reach out today.

Generative AI has seemingly limitless potential for brands who lead with their digital CX. Investigate the benefits of AI customer service.

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