Prioritizing your AI investments: Augment agents or automate customer interactions?
Automation? Or augmentation?
As AI capabilities for customer service proliferate, it gets harder to decide which ones are worth the investment for your contact center. Broadly speaking, AI solutions for the contact center fall into one of two categories – those that support human agents in real time (augmentation) and those that engage directly with customers (automation).
The question of which category to emphasize in your contact center has shifted significantly since AI first emerged as a practical tool for customer service. Early on, the excitement around automation drove chatbot adoption, which soon yielded to disappointment when the bots frequently failed and frustrated customers.
In the past couple of years, the focus has shifted to augmentation, as CX tech providers added a variety of copilot capabilities to their platforms. The results with these agent augmentation offerings have been far more favorable, if modest. Most enterprises that have adopted them report at least small efficiency gains.
And now, the pendulum is swinging back toward automation as autonomous AI agents have rapidly emerged as viable additions to the contact center ecosystem.
That leaves customer service leaders with a tough decision about how to spend their technology budgets. Is it time to switch gears and prioritize automation over agent augmentation with your AI investment dollars? There’s no single choice that’s right for every enterprise. But your decision depends on several factors, including the mix of interaction types your contact center handles, the kinds of customers you serve, and the expected ROI of each investment.
The modest but reliable gains of agent augmentation
Until recently, investing in agent augmentation has been the much easier and far more reliable option. The market is awash in solutions, most of which are tailored to address specific tasks in agent workflows, like retrieving context-driven information from the knowledge base, suggesting greetings or closings for a live chat, or generating a post-interaction summary.
An AI capability that automates one of these tasks is sure to save agents a little time, without disrupting the rest of the workflow. That drives quick efficiency gains, which offset the cost of the technology when aggregated over thousands of agents.
The narrow focus of augmentation capabilities also makes them relatively easy to incorporate into your processes and technology ecosystem. Required integrations are limited. And for the most part, your agents can keep doing what they’ve always done, just faster. With a lower burden on your team, augmentation solutions can be deployed quickly, which means you start realizing value right away.
In the past few years, agent copilots have allowed contact centers to get the benefits of AI in a controlled internal environment. Agents act as a safety net to ensure that any inaccurate or misleading output from the AI doesn’t reach your customers. That’s given customer service leaders time to get comfortable with the growing presence of AI in their operations.
The limitations of augmentation
There are limitations with agent augmentation, though. The benefits of agent copilots are reliable, but the overall impact on the contact center’s operations is typically small. Automated greetings, for example, save agents a few seconds per chat. That creates a small bump in productivity, but does not significantly increase the contact center’s capacity to serve customers.
Given the relative maturity of real-time agent assistance, some tech providers have pushed the boundaries of these capabilities to significantly expand their impact. Instead of automating just standard greetings and closings, these innovators now also automate the complex middle of the conversation. That’s a much bigger time saver. And in addition to consistent free-text summaries of each interaction, some more advanced solutions also capture a range of custom data fields that drive downstream automation. With that in mind, it’s becoming increasingly important to take extra care in choosing agent augmentation solutions. The best-of-breed options deliver much bigger returns.
Even so, there’s a ceiling on those returns. Because augmentation keeps your customer service delivery highly dependent on human agents, its potential productivity gains are constrained by what those humans can do. The simple truth is that humans aren’t easily scaled. That limits both contact center capacity and the returns on your investment.
Overcoming these limitations requires automation.
Why AI agents deliver much bigger returns
The broad disappointment with traditional bots among both customers and enterprises made automation investments less appealing for a long time. Contact centers continue to use simple automation like IVRs and chatbots, but customer service leaders have come to recognize that they can only handle simple interactions. Once they’ve hit the ceiling on the interactions those automation solutions can contain, the need for agent augmentation grows more urgent.
But the possibilities for automation have changed with the rapid growth of generative AI. Today, AI agents are far more capable than deterministic bots. Some can already handle a wide range of customer issues on their own. And they’ll only get better as innovation and development continue.
The return on investment with a fully autonomous AI agent is many times greater than what you can achieve with agent augmentation. The reason is simple – it scales. When inbound volume rises, the agent scales to meet the demand. And if your business expands, your AI agent expands with it. That dramatically increases your contact center capacity without requiring additional headcount.
Already, AI agents are automating a wide range of interactions, from booking travel with complicated itineraries, investigating fraudulent transactions, and helping customers upgrade services. The best AI agents successfully resolve much more complex issues than traditional automation can handle, which drives containment higher while keeping costs down.
The technology is maturing rapidly. The best-of-breed solutions have successfully addressed early safety concerns and are continuing to simplify deployment with improved integration options, no-code tooling, and human-in-the-loop workflows that expand the AI agent’s capabilities and ensure human judgment where needed. A growing number of enterprises have moved past proof of concept to launch AI agents within their contact centers. They’re already realizing extraordinary value.
As AI solution providers continue to innovate, the potential use cases for AI agents will multiply and their performance will improve. Over time, AI agents will be capable of handling increasingly complex issues. This innovation is occurring at a blistering pace, so understanding the scope of automation that will be possible in the very near future can serve as a powerful guide for where to invest your AI budget today.
The challenges with deploying AI agents
While the returns on investments in AI agents are far greater than what you’ll gain with augmentation capabilities, it’s important to be realistic about the challenges of implementing them. Autonomous AI agents have far-reaching implications for your internal processes, staffing, and organizational structure. They’re the first step in upending the human-dependent model of customer service.
But that doesn’t mean humans are no longer needed. The most impactful AI agent deployments occur in enterprises that successfully reshape the human-AI relationship into a collaborative model. That requires redefining the role the humans play. Working directly with an AI agent as the human in the loop is a brand-new job function that demands a different skillset and modified workflows. You’ll need to be prepared to adapt quickly to the ripple effects of this shift.
There are challenges with data and technology, as well. Autonomous AI agents need access to the same systems that human agents use to resolve customer issues. That includes your knowledge base, CRM, and other systems of record. And while human agents can often work around inaccuracies or gaps in your knowledge base, an AI agent can easily be limited by them. That elevates the importance of knowledge base management, and the AI solution’s ability to handle such situations to “unblock” the AI. For other systems, such as those used to manage customer accounts, the AI agent will need APIs to access the tools and data it needs. That means your team, your technology provider, or an implementation partner will need to create the necessary APIs.
The implications for evaluating AI agent solutions are clear.
The vendor’s ability to simplify the deployment process and provide technical guidance are just as important as their solution’s capabilities. Equally important is how the AI system is designed to handle roadblocks—whether through UI features that allow human agents to step in and assist when needed or mechanisms that enable AI to learn and adapt from human input.
Striking the right strategic balance for your business
The precise balance of AI investments you should be making now depends on the industry you serve, the types of interactions your contact center handles, the expectations of your customers, and your overall vision for CX strategy.
For highly regulated industries, some types of interactions might require a human agent, so you’ll need to restrict your use of AI agents for compliance. But even in such industries as banking and insurance, many interactions can be automated safely with an autonomous AI agent. And with a solution that effectively incorporates a human in the loop for oversight and approvals, you can still gain the benefits of automation with an AI agent.
In general, if your contact center handles a high volume of transactional interactions, you’ll want to lean heavily on automation investments. On the other hand, if relationship-building is a large central component of your customer service, you’ll want to be choosier about which types of interactions you fully automate, and emphasize augmentation a bit more.
While there’s no one-size-fits-all decision on how to balance your AI investments, it is time to start shifting some of your dollars toward automation. Agent augmentation should still be in the mix. It provides reliable efficiency gains. But long term, automation clearly offers a much bigger payoff. With the technology rapidly improving and delivering growing returns, waiting too long to explore AI agent solutions could leave your organization playing catch-up.
Starting small, and starting early, will allow you to refine your approach, work through operational challenges, and position yourself ahead of competitors who delay adoption.