AI Voice Agents: What’s Possible Today (and What’s Not Yet)
What are AI voice agents really capable of today? Discover what they do best, where they still struggle, and what’s coming next. A complete guide to the capabilities and limitations of AI voice agents in 2025.
Jun 4, 2025
Jacques Lecat
Intro
AI voice agents are no longer science fiction.
Thanks to recent advances in language models (LLMs) and speech technologies, businesses can now deploy intelligent voice agents capable of handling phone calls — not only understanding natural language but also acting on it through connected systems.
But what exactly can these AI voice agents do today? Where do their current limitations lie? And why is this technology poised to revolutionize how companies manage phone interactions in the coming years?
In this article, we’ll explore:
what AI voice agents really are — and why they’re a game-changer
what they can already do very well in 2025
where they still struggle
and what’s coming next.
1️⃣ What Is an AI Voice Agent — and Why It’s a Revolution
An AI voice agent is much more than a chatbot with a voice. It is intelligent software that can autonomously manage phone conversations — from understanding what the caller says, to formulating responses, and even triggering actions via APIs and integrations.
Unlike traditional IVRs (“Press 1, press 2…”) or pre-scripted callbots, modern AI voice agents leverage advanced LLMs (Language Models) such as GPT-4, combined with state-of-the-art speech-to-text (STT) and text-to-speech (TTS) technologies.
This allows them to converse in natural, fluid language — and to handle real business processes.
Why it’s a revolution:
First, AI voice agents enable businesses to scale phone interactions massively:
A single agent can handle thousands of calls in parallel — something impossible with human agents alone.
They operate 24/7 — no scheduling, no breaks, no night shifts.
Second, AI voice agents can now act, not just talk:
They can trigger APIs, update a CRM, book appointments, send SMS, process payments — turning calls into actionable business workflows.
Finally, AI voice agents help drastically reduce costs:
Routine calls can now be automated at a fraction of the cost of human agents.
They enable companies to capture opportunities that were previously lost (missed calls, after-hours calls, overflow during peak times).
In short: AI voice agents are transforming phone calls into a scalable, automated, intelligent business channel — and that’s why it’s a revolution.
2️⃣ What AI Voice Agents Already Do Very Well
In 2025, AI voice agents are already mature enough to handle many high-value business tasks.
One of the major advantages of platforms like Rounded is that you can easily connect your own APIs to your agents.
This allows agents to go far beyond basic conversations: they can trigger actions, retrieve data, update systems — and essentially perform the same tasks a human would… but at scale.
In fact, with proper prompting and configuration, an agent can be tailored to adapt to virtually any situation.
It all depends on the quality of the initial design — but once well prepared, an AI voice agent can handle an impressive range of tasks.
Natural language understanding
Modern AI voice agents can understand a wide range of natural language inputs:
different accents
casual speech
interruptions, hesitations
paraphrasing
In other words, callers can speak naturally, without having to adapt to the machine.
Structured, high-volume use cases
When properly prompted and configured, an AI voice agent can adapt to many scenarios and perform tasks just like a human — but with the advantage of being able to do it at scale.
Some of the most common and effective use cases today include:
1. Appointment scheduling
The agent can offer available slots, confirm bookings, update calendars, handle rescheduling or cancellations — and write back to your scheduling systems.
2. FAQ and information delivery
For businesses receiving repetitive inbound queries (opening hours, product details, procedures…), AI voice agents can fully automate responses.
3. Outbound call campaigns
AI voice agents can run large-scale follow-up campaigns, including:
subscription renewals
post-sale follow-ups
abandoned cart calls
subscription recovery campaigns
4. Lead qualification
AI voice agents can call new leads, ask qualifying questions, update CRM fields, and automatically route hot leads to human sales teams.
5. CRM updates and workflow triggers
Thanks to API integrations, voice agents can:
update contact statuses
trigger emails or SMS
log structured data into business systems
Personalization and integration
Today’s best AI voice agents can personalize conversations dynamically:
using CRM data (name, subscription level, recent interactions)
adapting tone and phrasing
providing context-aware answers
And with Rounded, agents can be deeply integrated with:
CRM tools (HubSpot, Salesforce, etc.)
calendars
payment systems
ticketing and support tools
automation platforms (Make, Zapier, n8n, etc.)
3️⃣ Current Limitations of AI Voice Agents
Despite these strengths, AI voice agents still have limitations — and it’s important to be aware of them.
Challenging audio environments
AI transcription remains sensitive to:
background noise
poor line quality
multiple speakers talking over each other
In noisy or chaotic environments, error rates can still increase.
Complex, human-sensitive interactions
AI voice agents are not ready to replace humans in delicate or emotional conversations, such as:
healthcare calls with sensitive news
complex negotiations or conflict resolution
More generally, AI voice agents still struggle to recognize certain human behaviors:
irritation or frustration
a voice choked with tears
subtle shifts in tone or intention
They may also handle silences awkwardly, following the script too rigidly.
Niche domain knowledge
Because AI voice agents are built on LLMs, they inherently share the limitations of LLMs:
even when they lack the right information, they will produce an answer anyway — which may be inaccurate.
This phenomenon is known as "hallucination."
In highly technical domains, if the prompting and knowledge injection are insufficient, there is a real risk of hallucinations.
User perception
While AI voice agents are increasingly high quality and harder to detect, some people still view them negatively.
Society is not yet fully accustomed to AI-driven voice interactions.
For some callers, realizing they are speaking to an AI can trigger distrust — even if the quality of the conversation is excellent.
That said, this perception is likely to evolve rapidly over the coming years, as the use of voice AI becomes more widespread.
Multi-language capabilities
AI voice agents still struggle with multi-language conversations:
Current voices tend to be optimized for a specific language.
If the agent is asked to switch languages dynamically (without explicit preparation), the result can be degraded.
If the script was not designed for multi-language scenarios, the agent will typically handle it poorly.
This is an area that should improve significantly in the near future — but today, multi-language fluency is still a limitation.
4️⃣ The Massive Potential of AI Voice Agents (What’s Coming Next)
Looking ahead, the pace of progress in voice AI is extraordinary. Several key trends are shaping the future of this technology:
More advanced real-time reasoning
LLMs are improving rapidly in multi-turn reasoning — enabling voice agents to handle more complex, layered conversations.
More expressive, human-like voices
TTS technologies are evolving to deliver:
more natural rhythm and prosody
emotional nuance
dynamic pacing
better multilingual fluency
This will make voice agents sound even more human-like.
Multi-language and seamless switching
Next-gen voice agents will:
handle multi-language conversations more naturally
switch between languages (ex: English/French/Spanish) without degradation
Smarter process handling
Agents will be able to manage:
multi-step business processes
context retention across long interactions
adaptive personalization based on real-time data
Continuous learning and adaptation
Future agents will:
learn from each interaction
improve performance continuously
adjust tone and style based on the customer
Agent-to-agent interaction
A promising new frontier: AI voice agents interacting with each other.
As we explored in a previous article, agents are now capable of:
conducting agent-to-agent conversations
coordinating tasks
exchanging data verbally
This opens up exciting potential for fully automated workflows, where one agent can trigger or collaborate with another.
Speech-to-speech interaction
Another exciting frontier is speech-to-speech interaction.
Today, AI voice agents rely on an intermediate text layer to process and generate responses. In the future, speech-to-speech models will enable agents to:
process speech directly, capturing not just words but tone, emotion, and prosody in real time
generate responses as speech, with more natural flow and expressiveness
This evolution will allow for:
faster, more fluid interactions
more human-like conversations, with tone and rhythm that adapt naturally to the caller
In short: speech-to-speech will help AI voice agents move closer to true real-time human conversation — making phone interactions with AI feel even more seamless and natural.
Conclusion
AI voice agents are no longer experimental — they are already delivering real, measurable value for businesses.
In 2025, forward-thinking companies are using them to:
automate high-volume calls
reduce operational costs
improve customer experience
scale outbound campaigns
At the same time, understanding their current limitations ensures they are used intelligently and responsibly — with humans still playing a key role where needed.
The future looks bright: with continued advances in LLMs, speech technologies, and integrations, AI voice agents will become:
more capable
more natural
more valuable for businesses.
And with platforms like Rounded, companies can already deploy AI voice agents that act, not just talk — today, not in five years.