Transforming the Future of Contact Centers with Artificial Intelligence

Imagine you’re calling your internet service provider for technical support. An IVR system greets you cheerfully, but it is not sophisticated enough to understand your problem, and you ultimately end up talking to multiple support agents, having to repeatedly explain your issue before anyone can help. This probably sounds all too familiar.

A recent survey by Vonage found that over half of those surveyed feel that IVR makes for a poor customer experience, and a survey from Sentiment.io reported that 89% of customers get frustrated because they need to repeat their issues to multiple agents.

In this post, the first in a two-part series, we will examine currently available AI technologies to help address the frustrations your customers have with contact centers. In the second post of the series, we will dive into what the future looks like for additional enhancements to improve your customer experience.

Current Use of AI in the Contact Center

While many organizations are still early in their AI transformation journey, the technologies to solve these problems are rapidly maturing and gaining adoption today. Modern contact centers have typically focused their AI technologies around three interconnected pillars: customer, agent, and supervisor. Let’s explore how each of these pillars can leverage AI technologies.

The Customer Pillar

According to a Zendesk survey, 51% of consumers prefer interacting with bots over humans when seeking immediate service. This aligns with how AI is primarily used in customer-facing environments today: through self-service tools designed to help people solve issues quickly or connect with the right agent. Virtual agents can handle frequently asked questions, book or change appointments, check order statuses, and update reservations in a natural conversational way.

Rather than using traditional touch-tone menus or even more modern natural language processing (NLP) solutions, virtual assistants can understand a broad range of requests and respond in human-like ways. Customers can simply say, “I need to move my appointment to next week, but I can’t schedule anything for Thursday,” or “Where’s my package?” and receive answers without having to work through a live agent or deal with the frustration of a restrictive IVR menu. All of this is enabled by integrating virtual assistants with back-end data sources like CRMs, scheduling platforms, and knowledge bases to provide callers with faster resolutions and shorter wait times.

However, a poorly trained or integrated virtual agent can be even more frustrating than a traditional IVR, leading customers to 'zero out' immediately.

The Agent Pillar

Agents can benefit from leveraging AI as well, which can lead to better outcomes for customers, deeper human connections, and a more rewarding work environment. One of the fastest-growing applications of AI for agents is agent assist, where AI can listen to a voice or chat conversation in real-time and provide proactive guidance to agents.  With agent assist, first call resolution and compliance are improved by providing proactive, real-time guidance based on outcomes from previous calls, defined rules, knowledge content, and more. Whether agents are new or experienced, they can add value to every client engagement.

AI can also reduce the amount of after-call work that agents need to do by automatically setting call dispositions and summarizing the call into notes. Rather than needing to write the summary of what happened on their own and potentially missing details, the agent can just review what was created by AI. This allows them to return to answering customer calls, which in turn helps reduce your organization’s average queue times.

The Supervisor Pillar

Supervisors and contact center leaders are also seeing the benefit of leveraging AI. The core focus for this pillar is providing additional insights and allowing supervisors to adjust to changing circumstances within the contact center. Three main areas where AI is leveraged include:

AI-Powered Workforce Management

For many years, workforce management solutions have leveraged machine learning to understand historical contact center volumes to try and predict the number of agents that need to be scheduled to meet demand. Leveraging historical patterns, seasonality, and bringing in external factors like marketing campaigns, weather, or even economic data, AI can automatically generate optimal schedules. By aligning staffing to forecasted peaks and recommending shift swaps, AI can help organizations have the right number and skilled agents available at the right time.

AI-Powered Quality Assurance

Traditionally, QA managers or supervisors relied on manual review of the calls in their contact center. This manual process means that only a small fraction of calls can actually be reviewed, and there is no understanding of the entire performance of agents. With AI-Powered Quality Assurance, every call can be analyzed using speech analytics and sentiment analysis. Rather than missing issues with agents because they reviewed a single good call, supervisors can now spot trends and flag issues like compliance risks, deviation from policy, sentiment issues, or even identify foul language being used. Additionally, AI can help identify top performers on the team to make sure that they receive the recognition they deserve, understand why they outperform their peers, and more effectively coach agents on the behaviors that yield meaningful performance improvement.

AI-Powered Analytics and Insights

Data that impacts the contact center comes from more locations than just your contact center platform. Leveraging AI, companies can take advantage of massive volumes of information to provide clear, meaningful insights that are distilled into easy-to-use dashboards. This enables supervisors to spot emerging trends and respond faster than ever before.

AI also allows supervisors to create custom reports without needing to know any bespoke query language. They can simply ask for the data they need to see using natural language and AI tools can analyze the data and present what was asked for. All without needing to remember how to do an inner join.

What’s Next for Contact Center Innovation?

Throughout this post, we’ve explored how customers, agents, and supervisors can benefit from leveraging AI in the contact center. While we covered many of the most common use cases, there are still countless innovative ways that contact centers can leverage AI, from accent neutralization to real-time translation and more.

In the next post in this series, we will take this discussion to the next step by exploring some of the ways that AI technologies for the contact center are changing into the rapidly approaching future.

There are many options to supercharge your contact center interactions with AI, but determining where and how to do so takes expertise.

As we've seen, AI offers powerful solutions to today's most common contact center frustrations. But these tools aren't magic. Their success depends on a clear strategy, deep integration with your existing systems, and a focus on the human experience for both customers and agents. Simply buying a new tool without a plan is the fastest path to an AI fail.

CXponent can help you choose the right path with the right tools so you deliver a delightful customer experience with confidence while saving valuable time and money. Connect with us to see how AI can improve your customer, agent, and supervisor experiences.