Embracing AI in the modern contact center
In the contact center industry, it’s safe to say that the initial buzz around AI has quickly given way to a constant hum. Today, organizations everywhere are shifting their position, strategy, and investment decisions from viewing AI as a shiny new toy to one where they want to see tangible benefits.
But how does this play out in practice? For many contact centers, the big impact of AI is currently behind the scenes in a range of functions, from boosting productivity and improving scheduling and forecasting accuracy to monitoring customer performance or predicting customer behavior. Whatever the specific priorities, by implementing AI to enhance the capabilities and work lives of agents and leaders, customers see the benefits too through improved interactions and outcomes.
However, this widespread enthusiasm comes with some concerns. First, it’s essential to acknowledge that managers are concerned about the impact of AI on agents’ mental health and training needs. Furthermore, while AI’s current role is primarily that of a supportive companion rather than a job-killer, there is a lot of uncertainty about what the future holds. In the medium to long term, successfully integrating AI into the contact center landscape will require organizations to formulate a strong plan to address these challenges and ensure success.
Product Evangelist at Calabrio.
The pinnacle of inflated expectations
Anyone who works in the contact center industry knows that there is currently a machine-generated elephant in the room: what impact will AI have on the role of agents in contact centers around the world?
For example, according to Gartner, AI is “currently at the height of inflated expectations,” but by 2025, “80% of customer service and support organizations will adopt generative AI technology in some form to improve agent productivity and the customer experience.” They have also predicted that AI will reduce call center labor costs by $80 billion by 2026.
Elsewhere, industry research has shed more light on emerging trends. When asked how AI will help the call center workforce of the future, a quarter of respondents said that increasing agent and manager productivity was in their top three answers. This was closely followed by optimizing forecasting and scheduling, measuring and understanding call center productivity, predicting customer actions and behaviors, and offering a chatbot service to customers.
However, when you speak directly to contacts, you quickly come across a common thread: many believe that AI will replace jobs or at the very least play a significant role in supporting agents and managers so they can focus on more complex tasks.
This seems like a reasonable perspective to take. Examples of using AI in a call center augmentation role are already common. For example, the technology can be used to handle simple queries via self-service channels, allowing organizations to refocus agent resources on more complex tasks that require human expertise and experience.
The problem is that AI is far from a ‘plug and play’ technology. Many agents will be used to spending their time troubleshooting errors made by current-gen bots or taking control of customer interactions when they reach their limits. Without a significant improvement in performance, it’s likely that AI adoption will be patchy, especially if performance issues damage leadership’s confidence in the technology.
Harnessing the potential of AI
The obvious question we must now ask ourselves is what can organizations do to ensure that their AI strategy leverages the clear potential for improvement?
An ideal starting point is to ensure that agents have full visibility into the entire customer journey, including all interactions with bots. This will help ensure that they can analyze all relevant information when they take control of a conversation. While this may seem like an obvious requirement, many contact centers currently lack this capability, and agents are left working with an incomplete view of the customer journey. In some situations, agents may need to ask customers to repeat information they’ve already provided, which isn’t ideal for either party in the conversation.
However, with full visibility into conversations, contact centers are much better positioned to leverage the benefits of technologies like conversational analytics to monitor and improve the performance and quality of AI bots. It also allows teams managing the AI bot experience to replace guesswork with data-driven insights to make better decisions when assessing conversational performance and responsiveness.
With these foundations in place, organizations then have a range of options for where to apply AI technologies. At this point, many find that the obvious place to start is to use it to better handle routine customer interactions that often occur at scale. In this context, only more complex queries are escalated to human agents in a process that not only improves contact center productivity but also reduces customer call wait times.
Crucially, this isn’t just about adding an AI tool. Embracing this new technology works best when users carefully consider how AI can be integrated with existing processes. The goal should be to improve efficiency without disrupting workflow, while also including mechanisms to make improvements based on real-world experience and customer feedback.
The human touch
Despite AI’s potential to act as a catalyst for change in contact center environments, human skills, experiences, and the ability to empathize remain at the heart of any successful strategy. With this in mind, leaders must recognize that their teams need training and support to understand how AI technologies work, their operational role, and how they – as contact center professionals – can impact their development within the organization.
As the pace of AI innovation continues to accelerate, it’s becoming increasingly clear that ignoring the changes the technology is already bringing is not a viable option. With so many organizations leveraging their customer service capabilities as part of their messaging, contact centers that aren’t exploring how AI can improve their processes risk getting left behind. But, guided by these ideas, organizations have a good chance of creating a win-win situation where contact center efficiency and customer outcomes improve simultaneously.
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