AI Agent Assist Will Be Replaced With AI Voice Agents. Which Technology Is Worth Investing In?

In recent years, many contact centers have implemented or are considering implementing AI-powered Agent Assist technology to help customer service representatives resolve customer issues more quickly and accurately. Agent Assist has become a de-facto standard technology that companies are increasingly investing in.

However, recent advancements in Generative AI and speech processing have paved the way for a groundbreaking new solution: Voice AI Agents. This emerging technology poses a realistic threat to the current dominance of Agent Assist tools.

In this article, I will explore the current use cases for the Agent Assist technology, compare them to the capabilities of Voice AI Agents, and share my predictions on whether Agent Assist is still worth investing in—or if you should skip it altogether and focus on Voice AI Agents instead. By the end of this article, you will have a clearer understanding of which technology is the right fit for your contact center.

Types of AI Agent Assist Technologies Available

As with many contact center AI capabilities, AI Agent Assist refers to several distinct tools bundled together under one umbrella term. Before exploring which are here to stay and which you might want to skip, let's define AI Agent Assist technology and its various flavors.

Definition: AI Agent Assist refers to Artificial Intelligence (AI) systems designed to support customer service and other contact center agents by providing real-time assistance during customer interactions.

The primary goal of AI Agent Assist is to increase the efficiency and consistency of customer service. It enables agents to focus on complex customer needs, improving the overall customer experience. Depending on the specific technology, AI Agent Assist can:

• Automate routine tasks
• Offer suggested responses
• Provide instant access to information
• Guide agents in handling customer inquiries

Let's take a closer look at the different types of real-time AI Agent Assist tools:

Use Case 1. AI Agent Assist Tools for Faster Knowledge Access Without Listening to The Conversation

While this might be one of the least complex AI Agent Assist capabilities, it is very useful. It enables agents to access relevant knowledge faster through a ChatGPT-like interface. Agents can pose questions to the internal knowledge base, and the Generative AI generates a concise answer with links to the original sources. 

Instead of sifting through lengthy articles, agents receive a direct, AI-generated response. This significantly speeds up knowledge retrieval, improving response times.

Use Case 2. AI Agent Assist Tools for Contextual Knowledge Access by Listening to The Conversation

Here, the AI Agent Assist tool actively listens to the conversation and automatically retrieves relevant information from the internal knowledge base. 

For example, if a customer asks how many days they have to return the product, the AI automatically surfaces the specific return policy terms and presents them on the agent’s screen. Unlike the previous use case, this requires no manual queries from the agent, streamlining the process further.

Use Case 3. AI Agent Assist Tools For Real-Time Coaching During Conversation

Some AI Agent Assist solutions provide real-time coaching by monitoring conversations. For instance, the system may hint agents to slow down if they are speaking too fast, prompt them to say something if they are pausing too long, and more. 

While potentially helpful, this often causes distractions and disrupts the agent’s focus. A more effective alternative might be conducting post-call analysis to provide actionable feedback and coaching insights.

Use Case 4. Advanced Real-Time AI Agent Assist Tools

Advanced AI tools go a step further by analyzing the conversation in real-time and guiding agents of what to say or do. For example, if a customer mentions canceling a subscription, the AI may prompt the agent to ask the reason and offer a discount to retain the customer. 

However, the constant bombardment of the agent with next steps, coaching suggestions, and sound bites makes it hard to concentrate on what the customer is saying. Not to mention the inherent latency in such a system, where the suggestion from the AI comes too late. In the worst-case scenario, agents may feel like “voice bots,” mechanically reading out AI-suggested responses, which can disrupt the natural flow of conversations and annoy the customer, who expects a human touch.

Which AI Agent Assist Technology Is Worth the Investment In 2025 and Beyond?

Here at MiaRec, we have been developing cutting-edge contact center AI solutions for over a decade. 

In my opinion, it is not worth investing in real-time live coaching or advanced AI Agent Assist technology because AI Voice Agents will mature and scale before these tools become refined enough to be truly impactful.  AI Voice Agents are quickly reaching a point where they can effectively take over lower-level support tasks.

On the other hand, AI Agent Assist tools for improving knowledge access are already mature and worth investing in. These solutions can deliver significant efficiency gains for your contact center.

The Benefits of AI Voice Agents Will Quickly Exceed Those of AI Agent Assist

Rather than turning human agents into "bots" that mechanically follow AI suggestions, the focus should shift to empowering agents to provide higher-level support. Rather than analyzing the individual calls in real-time, AI tools can process all the available call data to deliver personalized coaching and detect trends and opportunities for improvement. 

AI Voice Agents will emerge as the preferred solution for lower-level customer support inquiries. The multiple benefits of AI support this prediction. 

For one, AI is consistent. Once trained to a satisfactory level, AI Voice Agents deliver guaranteed service quality. AI doesn’t have bad days, get sick, or face issues that impact performance. 

Another advantage is its unlimited scalability. AI Voice Agents can scale up or down instantly, making them cost-efficient. They work 24/7, including nights, weekends, and holidays, and handle seasonal peaks. You cannot achieve the same flexibility with human agents. With human agents, you need to plan your load ahead of time and pay for times when agents are not busy.

Prediction: In 2025, early adopters will switch to Voice Agents, at least for lower levels of customer support.

This switch will happen relatively soon, with the first organizations already switching lower-level support to AI-based Voice Agents now. After an initial period of technology adoption, the AI Voice Agents will be as common as the phrase “This call may be recorded for quality assurance purposes” at the beginning of every conversation in the contact centers.

Exact time predictions are hard to make when it comes to the development of AI. This is for a few reasons:

• For one, in the past, the pace of technological advancement depended on how fast the companies were creating software applications. Now, we rely on how fast the researchers invent new AI algorithms to pass the next roadblock. As with any research, predicting when new inventions happen is impossible.
• In addition, cost will be a major factor. At the moment, AI-powered solutions remain relatively expensive. As Peter Gostev, Head of AI at Moonpig, pointed out the other day, a GPT-4o-Realtime audio model-based agent costs approximately $0.15 per minute. While this is lower than the per-minute cost of human agents in the US or UK, it remains higher than in the Philippines or India. However, this comparison excludes additional costs tied to human agents, such as training, idle time, and overtime pay for weekends or night shifts. As AI costs continue to drop, AI Voice Agents will become more affordable than human agents globally.

Customer Adoption: From Reluctance to Acceptance

Many customers remain wary of AI due to their experiences with clunky IVR systems. However, this resistance will fade as customers recognize the benefits of AI Voice Agents, particularly when faced with the choice of waiting 10-15 minutes for a human agent or receiving an immediate resolution via AI.

Your Thoughts?

Next year will be pivotal. Major players like Cisco, Five9, OpenAI, and others are actively developing AI Voice Agent applications. 

What do you think? Is it worth investing in AI Agent Assist technology today, knowing that Voice Agents will soon deliver superior capabilities, greater scalability, and more versatile use cases? Or will you continue to prioritize your human agents?