'Personality Engineering' Puts a Human Face on Telco AI Agents

Amdocs and Nvidia are pioneering "personality engineering" to design AI customer service agents that embody brand identity and adapt to customer needs. This approach aims to improve interactions by making AI agents more empathetic and context-aware, reflecting the nuances of human conversation. AI customer service agents, sometimes called "clankers" in popular culture, often struggle with reputation issues. Amdocs seeks to change that by tuning these AI agents to represent the brand’s language, visual identity, and values effectively.

"Your agent is your brand representative, just like a human agent in the call center would be," said Hillel Geiger, Amdocs global VP of corporate marketing. AI agents must consider the context of the conversation and the customer’s profile to create meaningful interactions.

Consumer Preferences for AI Agents

Amdocs conducted a study involving 7,000 respondents across 14 markets and 130 telecom executives to understand consumer preferences for AI agents. Key findings include:

• 45% of respondents preferred female-presenting AI agents, 25% male, and 30% had no preference.
• Among female respondents, 67% preferred female-presenting agents.
• Age preference was varied: 39% had no preference, 35% preferred agents their own age, 14% younger, and 12% older.
• 58% favored an empathetic tone in AI agents, highlighting a desire to humanize machine interactions despite knowing they are speaking with software.
Chris Penrose, Nvidia global VP of business development, noted that users often use polite language like "please" and "thank you" even when interacting with AI.

Customization and Guardrails

Customers can customize AI agents’ gender, age, and tone, creating countless permutations. However, guardrails are crucial to ensure agents respond appropriately and avoid off-topic or sensitive subjects such as politics.

"How do you ensure that your agent is answering questions the way you want them to answer, and not talking about politics?" said Chris Penrose.

Proof-of-Concept Success

In trials with a large North American operator, Amdocs reported:
• 63% reduction in call handling time
• 50% improvement in first-call resolution
• 50% increase in Net Promoter Score (NPS)
These results demonstrate significant efficiency and customer satisfaction gains.

Collaboration Between Amdocs and Nvidia

The companies are developing specialized AI agents for telco functions such as care, sales, marketing, and network optimization using the Amdocs amAIz platform. Each agent acts as an expert in its domain, leveraging deep telco operational knowledge. They are also working on orchestrating AI agents to handle multiple intents within a single interaction, akin to a boardroom of experts collaborating to provide the best outcomes.

Emerging Standards for AI Agent Interoperability

Several standards aim to enable seamless orchestration between AI agents, including:
• Cisco’s AGNTCY foundation (donated to the Linux Foundation)
• Agent2Agent (A2A) protocol
• Anthropic’s Model Context Protocol (MCP)
Nvidia’s Riva and NeMo platforms support real-time multilingual speech recognition, transcription, translation, and scalable AI voice agents.

Large Telco Models (LTMs) and AI Avatars

At Nvidia's GTC 2025, the focus included large language models specialized for telcos (LTMs) capable of rapid network reconfiguration. A demo showed AI agents improving wireless network performance by 30% during a major event. Humanlike AI avatars, or "digital humans," are emerging as superior interfaces compared to traditional chatbots, offering higher customer satisfaction and purchase likelihood.

Challenges: Hallucinations and Customer Trust

AI hallucinations—where agents provide incorrect information—pose risks. Examples include:
• Air Canada ordered to compensate a customer after a chatbot incorrectly promised a refund.
• McDonald's removed AI ordering tech after bizarre order errors went viral.
Such errors can damage trust, especially in sensitive situations. Mitigation strategies include grounding AI in real data via retrieval-augmented generation (RAG), integrating company knowledge bases, and maintaining human oversight.

Final Thoughts

Amdocs and Nvidia’s "personality engineering" could transform telco customer service by making AI agents more relatable and effective. The key challenges will be scaling deployments, maintaining trust, and managing AI risks. Interestingly, while many consumers prefer empathetic AI agents, some users, including the article’s author, prefer AI to remain neutral and machine-like to avoid uncomfortable interactions.

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Frequently Asked Questions (FAQ)

What is "personality engineering" in AI agents?

Personality engineering refers to the process of designing AI agents to have specific characteristics, a brand-aligned voice, and the ability to adapt their tone and demeanor based on the context of the conversation and the customer's profile. The goal is to make AI interactions more human-like, empathetic, and effective.

What are some key consumer preferences for AI customer service agents?

Studies show that a significant portion of consumers prefer female-presenting AI agents. Additionally, a notable preference exists for AI agents to adopt an empathetic tone, even when users are aware they are interacting with software. Age preference for AI agents varies, with many having no specific preference, while others prefer agents closer to their own age.

What are the main challenges in developing AI customer service agents with personality?

Key challenges include ensuring appropriate and safe responses by implementing "guardrails" to prevent off-topic or sensitive subject discussions. Another significant challenge is maintaining customer trust, which can be eroded by AI "hallucinations" or the provision of incorrect information.

How can AI agents be customized?

Customers can typically customize AI agents' gender, age, and tone to create a more personalized experience. These customizations allow the agents to better align with brand identity and individual user preferences.

What are the benefits of successful AI agent implementation in customer service?

Successful implementation can lead to significant improvements in efficiency and customer satisfaction. Examples include reductions in call handling time, improvements in first-call resolution rates, and increases in Net Promoter Score (NPS).

Crypto Market AI's Take

The development of "personality engineering" for AI agents, as pioneered by Amdocs and Nvidia, aligns with the broader trend of making AI more accessible and relatable. In the financial and cryptocurrency sectors, similar principles are being applied to create AI-powered trading assistants and market analysis tools that users can trust and interact with more naturally. Our platform leverages advanced AI for precise market analysis and automated trading strategies, aiming to provide a seamless and intelligent user experience. Just as telcos are seeking to humanize their AI interactions, we strive to demystify complex market data and trading processes through sophisticated AI. You can explore our AI-driven market intelligence and trading tools at AI Crypto Market Platform.

More to Read:

• AI Agents: The Future of Business Automation and Customer Engagement
• The Power of AI in Personal Finance
• Navigating the Crypto Market: A Comprehensive Guide

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Source: Originally published at Fierce Network on August 7, 2025.