AI Phone Agents vs. AI Copilots for Human Agents – Which AI Future Should You Bet On Right Now?

Contact center leaders face an important decision when allocating AI budgets: Should they invest in AI Copilots to augment their human agents or fully-autonomous AI Phone Agents? The obvious answer might seem to be both—each has its advantages depending on the use case. However, the underlying tooling, processes, team composition, and business models for these two strategies are quite different. This makes it difficult to “hedge” by investing equally in both without diluting the potential impact.

Let’s explore the case AI Phone Agents vs. AI Copilots.

Human Agents Augmented by AI Copilots

We’re already a couple of decades into the “digital transformation” from in-store shopping to online shopping and self-serve checkout. Yet, despite promises that digital channels would reduce the need for human interaction in B2C sales and service, contact centers today employ more agents than they did 10 years ago. According to McKinsey, only 20% of digital contacts are fully “unassisted” by a human agent.

Why is this the case? While online systems, self-service flows, and chatbots have been improving, they still face challenges such as usability issues, unintegrated systems, sensitive transactions, or high-stakes scenarios that require human oversight for regulatory or fraud prevention reasons.

Rather than assuming humans can be replaced entirely, the smarter strategy is to pair them with AI copilots, creating “superhuman agents” who are more efficient and accurate. The job of AI in this model is to take every piece of a human agent’s interaction and figure out how to make it faster, easier and more accurate. Here’s how AI copilots can help:

• Real-time suggestions: AI copilots can listen in on conversations, pulling up relevant knowledge articles or suggesting responses to customer queries.
• Automated summaries: AI copilots can generate call summaries and suggest disposition codes, reducing post-call work and improving reporting accuracy.
• Automated coaching: AI copilots can review past calls, identifying patterns and insights that can be used to coach agents on performance.

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The business case for AI-assisted human agents revolves around two key metrics:

• Faster interactions: By reducing the manual effort to look up information or take call notes, interactions might drop from e.g., 4 minutes to 3 minutes on average.
• Improved first-contact resolution: With AI-driven insights, human agents can resolve issues more accurately the first time, increasing first-contact resolution from, say, 70% to 80%.

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Combined, this could make your contact center roughly 35% more efficient—assuming agents adapt their processes and behaviors to fully leverage AI copilots (which is a big “if”). But this raises the question: How far can productivity gains be pushed with this approach?

AI Phone Agents

The case for AI Phone Agents builds on this very question: Why make human agents 35% more efficient when you can start replacing them entirely for specific tasks?

As AI technology advances, the range of use cases AI Agents can handle end-to-end will continue to grow, allowing more interaction volume to be displaced by AI. The upside potential here is much greater than augmenting human agents.

The business case for AI Phone Agents is that they can handle repetitive interactions at a fraction of the cost of human agents – potentially 50% of the per-minute cost of an outsourced agent in the Philippines or India. Moreover, AI agents improve over time as LLM providers release more advanced, lower-latency models at potentially lower cost. 

AI Phone Agents also come with other advantages that no amount of investment in AI-assisted humans will ever accomplish – 24/7 availability, infinite scalability with demand (up or down), zero ramp time, and zero churn.

There’s no question that today’s AI technology has limitations. While AI Agents excel at handling repetitive, straightforward tasks, they still struggle with complex interactions requiring nuanced emotions, negotiation, or creative problem-solving. Moreover, customers may hesitate to engage with AI when they feel their issue is critical or sensitive.

But the argument for investing in AI Phone Agents now is not that they can replace 100% of human interactions today. It’s that there’s a ceiling on the efficiency gains possible with AI-assisted agents, especially as simpler use cases are increasingly handled by fully autonomous AI Phone Agents.

Our Take on AI Phone Agents vs. AI Copilots

We believe generative AI (and AI voice technology, in particular) has crossed the threshold where it can handle 5–15% of interactions autonomously in any diversified contact center (e.g., where there’s a mix of sales, customer support, collections, etc. interactions). And based on the exponential growth of LLMs, we think this will grow like an S-curve to where 90% of contact center interactions can be AI-led over the next 10 years, with the 10% long-tail of less predictable, more complex interactions being handled by the best human agents.

More importantly, we believe that humans and AI Phone Agents excel in different areas rather than assume humans are better at all interactions and AI Voice Agents are just a more cost efficient, but “less good” way of handling a subset of those interactions. The race to AI Agents should not be "a race to the bottom" to deliver the lowest cost service (like outsourcing was), but rather an opportunity to deliver a better customer experience at a much lower cost. Therefore, it’s better to leverage what each – AI Agents and Humans – is best at (at any point in time) rather than trying to create “AI Super Humans” who have diminishing returns and may not even be best suited to some of the interactions. For example, even “AI Super Human” agents get exhausted and demoralized by repeating rote interactions.  

In addition to the set of interactions AI Phone Agents can handle end-to-end today, consider breaking up interactions and using a dynamic handoff between AI Phone Agents and human agents. For example:

• AI Phone Agents could handle the initial part of an interaction, answering basic questions or gathering information, before seamlessly transferring the customer to a human when the complexity escalates.
• Conversely, human agents could manage the bulk of a conversation, then hand off to an AI Agent for transactional tasks like confirming a purchase or setting up an appointment.

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Over time, the balance between what AI and human agents handle will shift as AI Agent capabilities improve.

Waiting on the sidelines to adopt AI Phone Agents – even for the narrower set of interactions they can handle autonomously today – puts you at risk of falling behind competitors who, with a leaner cost structure from adopting AI Agents earlier, can outspend you on growth or lower prices. Realizing the full benefits of AI Phone Agents requires changes to every dimension of your contact center: tooling, processes, reporting, team structure, business model, and customer experience. It’s time to start investing now.

Getting Started

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