We’ve spent decades perfecting how to train human agents to be the trusted face of our brands. But what happens when your most powerful brand ambassador isn’t human?
Service-intensive brands have always built loyalty and trust with their customers through carefully crafted experiences driven in part by human care agents. Now, generative AI (gen AI) is ushering in a new era—the agentic era—where AI agents autonomously perform tasks, make decisions, and interact with customers on behalf of brands, seamlessly shapeshifting to every customer, every time.
With this, the branding paradigm is changing, which is significant for industries that encompass communications service providers (CSPs), financial services, and many others. In this era, AI agents will not only serve as tools but as brand representatives—communicating in the brand’s voice, reflecting its values, and shaping customer relationships. Companies must consider how these agents’ personalities impact interactions, ensuring they deliver meaningful, personalized experiences while upholding the brand’s unique identity.
Indeed, each brand interaction with a customer via AI agents should be seen through the paradigm of brand, context, and customer: What is the brand persona, the context of the customer interaction, and who is the customer? In the agentic era, these possibilities are infinite. Is it always the same AI agent persona, or does each customer meet another persona depending on the context of the interaction? It’s a question every brand must address, because as AI agents evolve, this will fundamentally redefine how businesses interact with their customers and workforce across all channels. The path forward begins with AI agents that can deliver on today’s high consumer expectations—enhancing experiences and building the trust needed to thrive in the agentic era.
Understanding the expectations gap
As the industry makes this shift, understanding consumer expectations compared to CSP assumptions is essential. However, research by Amdocs highlights a surprising disconnect.
CSPs overestimate the overall concern level of consumers interacting with AI agents, believing 57% are hesitant about AI-enabled customer care, while only 45% of consumers share the same concerns. Further, CSPs believe 58% of consumers would feel uncomfortable interacting with AI, but only 34% of consumers highlighted this as a concern.
In fact, 61% of consumers said they would switch to a CSP that offered a personalized AI agent that could match their expectations, and 45% already prefer personalized AI agents over human ones. This suggests that customers are more open to AI sales and care than most CSPs expect.
However, it’s important to note that consumers’ expectations for AI agents are high. For example, 80% of consumers expect AI agents to act empathetically, compared with just 43% of CSPs who believe this is necessary. Similar gaps exist for professionalism (85% vs. 44%), quick issue resolution (87% vs. 51%), and achieving first-time resolution (74% vs. 27%).
To meet these expectations, CSPs must adjust their mindset and develop AI solutions with telecom-specific expertise, building a knowledge database of customer needs, solutions, and more that can be used by these AI agents. Unlike general-purpose gen AI, these agents need access to telecom data and industry knowledge to provide accurate, context-driven interactions.
Personalization: A key to customer satisfaction
Consumers also want AI agents that are tailored to their personal preferences and reflect a brand’s identity. Nearly half (49%) want to select their AI agent’s characteristics, such as gender (45%), age (35%), and empathetic demeanor compared with a more formal one.
This presents an opportunity for CSPs to evolve their brands by creating AI agents that embody brand personality while catering to customer preferences. Rather than replacing human interaction, AI should seamlessly extend the brand, offering efficient service with a personal touch where requested.
Where to begin
As the landscape shifts, a gradual approach for integrating gen AI into customer care will be important. Brands should focus on high-impact use cases where AI is likely to be well-received, ensuring a smooth handoff to human agents for complex or sensitive issues like complaints.
Additionally, a hybrid model—where AI agents learn from human counterparts—allows brands to pilot internal use cases before scaling gen AI for customer-facing interactions. By prioritizing trust and adaptability, CSPs can introduce AI in ways that resonate with customers and build confidence.
Building trust for the agentic era
As we approach the agentic era, CSPs have a unique opportunity to set the standard for AI-driven sales and care. By addressing the expectation gap and creating AI agents that go beyond functionality to represent the brand’s voice, CSPs can deliver personalized, impactful experiences.
As consumers’ comfort with AI grows, so will their expectations. Brands that rise to meet these demands will build trust and loyalty in this new era of customer engagement.
Learn more about Amdocs’ Rethinking Brand & Customer Experience in the Agentic Era research.
