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Artificial intelligence (AI) has steadily worked its way into everyday use over the years, but in just a handful of months, the possibilities have exploded.
The development of generative AI tools such as OpenAI’s ChatGPT are fundamentally changing how we conceive AI, and its capabilities will completely overhaul how consumers look for and consume information. Where traditional iterations of AI fell short, generative AI is excelling: creating human-like interactions, quickly searching through all kinds of data and producing outputs on par with those of humans.
More importantly, by taking these models and training them with industry-specific data based on millions of customer interactions, solutions like Enlighten stand to revolutionize customer experience and supercharge contact center operations, if leaders can stay informed and move forward with intention.
The Journey to AI Today
While the buzz around generative AI formed relatively recently, the tools are actually the result of more core technologies such as deep neural networks and large language models that solution providers have been fine tuning for decades.
What has changed is that these tools are more accessible to the everyday user, thanks to conversational interfaces and improvements in semantics. Traditional chatbots and virtual assistants varied in quality and were limited in their capabilities and ability to converse naturally with human users. Generative AI tools today can now quickly and more accurately interpret prompts to deliver a relevant, actionable answer to users.
Furthermore, this new wave of AI will ultimately change how we interact with the vast amounts of unstructured data we now possess as customers, employees and businesses. Thanks to its ability to quickly digest data, detect trends and categorize information, it can unlock new opportunities for enterprises.
How Can CX Get in the Game?
Customer experience leaders today are racing to become early adopters of generative AI and for good reason. As the market has changed, demands on contact centers have risen, and technology will need to fill in the gap that increased hiring cannot.
Much of AI’s promise stems from its ability to scan both structured and unstructured data, which results in chatbots that can provide a more human-like experience that is respectful of the customer’s time. Better AI models understand context and intent, which allows for more human-like conversations (as opposed to only recognizing specific keywords).
As their daily workflow grows more complex, AI can also empower contact center agents by generating automated call summaries and providing quick access to knowledge and other relevant information needed to resolve customer inquiries and issues.
Furthermore, by sharing data across other departments such as marketing, sales and product development through an AI interface, companies can ultimately build an even more holistic customer journey.
However, companies can’t capture any of these benefits through AI use alone. Without giving these technologies the right data and context, they’re no more useful than the chatbots and automation features of yore. To thoughtfully make AI a part of the customer experience strategy, leaders will need to either build or invest in technology specific to this goal.
Anticipating Failures
Although AI can offer incredible benefits to contact centers, much like humans, it isn’t 100% accurate all the time. Furthermore, it comes with a number of risks, from hallucinations and copyright infringement to data privacy concerns.
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As mentioned previously, proper training of an AI solution is critical to prevent and solve these issues. The right solution provider won’t bring in technology blindly – they’ll need to ensure the semantic layer is consistent with your brand values and messaging, and that its curation of knowledge is brand-specific.
Companies will also need to train employees on how to effectively prompt AI to get the best, most relevant outcomes. In addition, employees will also need to be able to monitor and detect inaccuracies, non-compliance and other mistakes within AI results.
AI and Your Cloud Strategy
Cloud migration has been a business goal across industries for a while now, with even larger enterprises ditching on-premise solutions for the cloud: according to one report, 94% of enterprise companies were reportedly using cloud services as of 2022. One aim companies had for this strategy was to eliminate data silos between different business functions and offices. Multi-channel support adoption has also led to a significant increase in the amount of data contact centers are trying to integrate and analyze through a cloud platform.
Having conversational AI infused into the the front-end of these platforms allows agents and other users to get the greatest benefit from having all this data in one place, multiplying the benefits of cloud adoption.
As a result, it’s critical that companies looking to make AI a competitive advantage within their contact center consider moving towards a cloud strategy.
Conclusion
Ultimately, while these tools have compelling use cases across organizations, contact centers may be one of the best business units in which to build an AI strategy. Because of the iterative nature of AI, it may take time to see the full return on investment, meaning that leaders will need to adjust their thinking. However, one of the quickest ways customer experience teams can unlock the power of AI is by finding a solution that is built around their unique needs.
Learn how Enlighten can help your organization drive extraordinary customer experiences at nice.com.
