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Harnessing AI for CX: Meeting consumer expectations while optimizing costs
Exploring the intersection of consumer expectations, economic pressures, and the transformative power of AI in customer interactions.
In a world where technology evolves at lightning speed, consumers are now accustomed to the efficiency and sophistication of AI-driven interactions. As large language models like ChatGPT redefine communication norms, businesses face a dual challenge: meeting soaring customer expectations while ensuring operational efficiency.
Industry expert Quinn Agen from Omilia sat down with Tom Lewis from TTEC Digital during our last Experience Exchange to share his insights into the current state of AI, highlighting pivotal trends and considerations that are reshaping the industry landscape.
Consumer expectations drive AI advancements
The widespread exposure to AI technologies has set a new benchmark for customer expectations. As noted during the exchange:
“There's been a huge shift in the market over the last couple of years… principally driven by the exposure that the average consumer has had to these types of technologies. …I think what we're seeing in the market is really an effect of that in the enterprise, where enterprises are forced to take the next step from an AI perspective because their consumers are demanding it.”Quinn Agen, Omilia
Customers now demand AI that can mirror the human touch — understanding them fully and enabling seamless, productive conversations. For enterprises, this shift means not just adopting AI, but optimizing it to offer experiences that rival human interactions.
"[Consumers] know that there are technologies out there that can understand them and allow them to speak truly freely and get as much done as you would with a human agent or a human associate," says Agen. "And to do so in a way that is not cumbersome, that you don't have to repeat yourself."
Balancing economics and employee value
The integration of advanced AI isn't solely a response to consumer demand; it's also influenced by economic pressures. Rising operational costs, driven by inflation and increasing salaries, push companies to seek cost-effective solutions that don't compromise service quality. This dual focus was emphasized during the conversation:
“When we have these [AI] conversations, we talk a lot about the consumer and the customer and providing a great, delightful customer experience. But we also need to talk about the employees. It's not only necessarily about taking out the human resource costs, it's about repositioning those human resources to do different things that add more value to the company and to the customer. If you have a more advanced AI, then you're able to alleviate a lot of that redundant, repetitive cognitive load on human agents, making them more valuable resources inside the organization.”Quinn Agen, Omilia
And it’s not an all-or-nothing approach. Even when tasks aren't entirely contained — that is, handled exclusively by AI without any human intervention — AI still adds significant value,
"With the advances in speech-to-text and natural language understanding, we do have the power to take as much weight off the human agent upfront before that call ultimately gets transferred," says Agen. "Things like building a profile around a new user or collecting information like a change of address — more of the mundane types of questions that agents or humans normally need to collect around customers to service their requests. Even if we can collect 25, 50, or 75% of the information that ultimately the human agent is going to need to complete that fulfillment? That's cost savings right there."
By automating these routine tasks, AI lightens the load on human agents, allowing them to focus on more complex and meaningful customer interactions. This not only drives operational efficiency but also boosts innovation and employee satisfaction by giving them more impactful roles.
Standing behind your AI outputs
We all know that generative AI offers powerful, real-time capabilities, allowing for unprecedented advancements in business processes. However, these benefits come with critical requirements, especially in industries where precision and compliance are non-negotiable. During the talk, this was highlighted as a top priority:
“Many of the larger contact centers out there are in highly regulated industries. And even if they're not in a highly regulated industry, there is still a very hard requirement to make sure that what is being said to customers is exactly what the business and legal…have approved to be said. The main benefit of generative AI is that it generates things in real time, essentially from scratch. And that's great because it gives us a huge accelerator in terms of bringing not only conversational AI, but all ambits of business in general. It gives everybody a supercharged type of motor. But at the end of the day, you do need to have the ability to go to your auditors and go to your regulators and go to your InfoSec and cybersecurity partners and say, yep, this is exactly what the bot said. It was approved by the business.”Quinn Agen, Omilia
Ensuring that AI-generated content adheres to pre-approved guidelines helps mitigate risks related to misinformation and hallucinations — issues that can arise from real-time generation. Businesses must implement robust guardrails to maintain brand integrity and meet strict compliance standards. Additionally, data security and privacy remain pivotal.
As Agen notes: "You need to... report to your cyber partners that this is where our data is going — that it's not being used to train a conglomerate of models."
This transparency is vital for maintaining trust and protecting sensitive information, reinforcing the need for businesses to strike a balance between innovation and security.
Adapting to the new, uncertain AI frontier
AI’s potential to transform customer experiences is undeniable, but its deployment comes with complexities.
Consumer expectations are higher than ever, driven by direct interactions with advanced AI technologies. Companies must navigate economic pressures while strategically positioning human talent to maximize value.
Most importantly, achieving precision, auditability, and data security in AI implementations is crucial to maintaining compliance and trust. As the landscape evolves, enterprises that master these elements will be better positioned to lead in the new era of AI-driven experiences.
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