A one-size-fits-all AI voice fails. For a Japanese healthcare client, ElevenLabs' agent used quick, short responses for younger callers but a calmer, slower style for older callers. This personalization of delivery, not just content, based on demographic context was critical for success.

An AI tool that prompts call center agents on conversational dynamics—when to listen, show excitement, or pause—dramatically reduces customer conflict. This shows that managing the non-verbal pattern of interaction is often more effective for de-escalation than focusing solely on the words in a script.

Unlike old 'if-then' chatbots, modern conversational AI can handle unexpected user queries and tangents. It's programmed to be conversational, allowing it to 'riff' and 'vibe' with the user, maintaining a natural flow even when a conversation goes off-script, making the interaction feel more human and authentic.

Don't worry if customers know they're talking to an AI. As long as the agent is helpful, provides value, and creates a smooth experience, people don't mind. In many cases, a responsive, value-adding AI is preferable to a slow or mediocre human interaction. The focus should be on quality of service, not on hiding the AI.

Instead of fully automating conversations and risking sounding robotic, use AI to provide real-time suggestions and prompts to a human sales rep. This scales expertise and consistency without sacrificing the human touch needed to close deals.

While most focus on human-to-computer interactions, Crisp.ai's founder argues that significant unsolved challenges and opportunities exist in using AI to improve human-to-human communication. This includes real-time enhancements like making a speaker's audio sound studio-quality with a single click, which directly boosts conversation productivity.

The magic of ChatGPT's voice mode in a car is that it feels like another person in the conversation. Conversely, Meta's AI glasses failed when translating a menu because they acted like a screen reader, ignoring the human context of how people actually read menus. Context is everything for voice.

The most significant near-term impact of voice AI will be in call centers. Rather than simply replacing agents, the technology will first elevate their effectiveness and productivity. Concurrently, voice bots will handle initial queries, solving the common pain point of long wait times and improving overall customer experience.

A common objection to voice AI is its robotic nature. However, current tools can clone voices, replicate human intonation, cadence, and even use slang. The speaker claims that 97% of people outside the AI industry cannot tell the difference, making it a viable front-line tool for customer interaction.