AI has been one of the most talked-about innovations in the marketing world in 2023, and that talk is only going to get louder in 2024. To look at where we are now and what's ahead, Emplifi CMO Zarnaz Arlia sat down with Keith Dawson, Director of Research, CX at Ventana Research, in a conversation that spanned from how AI is impacting CX and marketing teams to examining the questions that lie ahead.
Here are some key takeaways from their discussion, along with some of the specific insights they offered based upon their years of experience.
Also, be sure to watch the full webinar, "Generative AI: Surfacing the Power and Potholes in CX" to help inform your decisions around using AI with your team in 2024.
Takeaway 1: Generative AI's implications in CX and marketing are far-reaching and transformative
The use of generative AI in customer experience (CX) and marketing has been identified as a game changer. The speakers discussed the various use cases of AI, from enhancing self-service to providing agents with guidance and carrying out sentiment analysis in marketing.
"There are many potential use cases that are cropping up in customer service, in marketing, and in broad interdepartmental CX generally," Dawson said. "AI is now able to help the agent as well, providing guidance about what steps to take during an interaction or highlighting something the agent may not pick up on, like emotion or sentiment."
They went on to highlight the potential of generative AI in customer experience and marketing and how it can help brands to achieve their goals. AI can be used to analyze customer sentiment, make product recommendations, and provide agents with guidance during customer interactions. They also discussed the value of using AI to amplify marketing efforts, such as creating personalized content for customers.
Takeaway 2: The ethical and governance challenges around generative AI cannot be overlooked
While the benefits of generative AI are immense, they stressed that the ethical and governance issues concerning its implementation should not be overlooked. The technology's black-box nature and the potential for bias embedded in data used for training AI models were cited as significant concerns.
"First, I think there's the question of innate bias. Your AI is only as good as the data that you feed into it, that you train it on. And if you're not using domain-specific information, I think that that's going to be a bit of a handicap," Dawson said. "There are ethical issues that surround decision-making by automated systems… how do you know that your data set of customer information and conversations that may be used to train a model doesn't necessarily unfairly discriminate against a set of people or create inequities that don't show up until long after? Those kinds of things are important to be aware of."
He suggested there's a real need to understand the data you're working with and the implications of your decisions, as that's the key to using AI responsibly and ethically.
"AI is a powerful tool," he said, "but it's important to understand the human implications of the decisions it makes, and to act with integrity when using AI technology."
Takeaway 3: The future of generative AI in CX is promising but also filled with uncertainty
As they looked to the future, it was clear that the potential for generative AI in CX is promising, yet filled with uncertainties. The pace of adoption will be gradual, and the technology's cost and impact on jobs remain unknown factors. However, they agreed that the right approach would be to leverage the technology strategically and align it with overall business goals.
"I think we're going to move more slowly than people would like at first, for the next year or so, to where people have a good understanding of the use cases and how to derive the value," Dawson said. "I think we're going to enter the realm of the unknowable. And by that, I mean once we get to looking at how customer-facing processes integrate with processes that happen in the back office or somewhere else in the enterprise, we're going to see AI for CX transform into a broad sort of operating system for moving work around."
It's going to have to be part of a broader strategic approach, and finding a way generative AI can fit into future plans.
"It's about strategic integration," Arlia said. "So companies must align Gen AI with their overall CX strategy, ensuring it complements, rather than complicates the customer journey."