In the contact center industry, it’s safe to say that the initial excitement around AI has quickly given way to a constant buzz. Today, organizations around the world are shifting their posture, strategy, and investment decisions, no longer seeing AI as a shiny new toy but instead seeing it in an area where they want to see tangible benefits.
But how is this being applied in practice? In many contact centers, the big impact of AI is currently happening behind the scenes in a variety of functions, from increasing productivity and improving scheduling and forecasting accuracy to tracking customer performance or predicting customer behavior. Regardless of specific priorities, by deploying AI to improve the capabilities and work lives of agents and leaders, customers are also seeing the benefits through improved interactions and outcomes.
However, to counter this widespread enthusiasm, there are some concerns. Firstly, it is essential to recognise that managers are concerned about the influence of AI on the mental health and training needs of agents. Furthermore, while the current role of AI is primarily that of a supportive companion rather than a job stealer, there is a great deal of uncertainty about what the future may hold. In the medium to long term, successfully integrating AI into the contact centre landscape will require organisations to formulate a solid game plan to address these challenges and ensure success.
Product evangelist in Calabrio.
The peak of inflated expectations
As anyone in the contact center industry knows, there is currently a machine-generated elephant in the room: how will AI impact the role of contact center agents around the world?
According to Gartner, for example, AI is “currently at the height of inflated expectations,” but by 2025, “80% of customer service and support organizations will apply generative AI technology in some form to improve agent productivity and customer experience.” They’ve also predicted that by 2026, AI will have reduced contact center labor costs by $80 billion.
Elsewhere, industry research has shed further light on emerging trends. When asked how AI will help the contact centre workforce of the future, a quarter of respondents said that increasing agent and manager productivity was among their top three answers. This was closely followed by optimising forecasting and scheduling, measuring and understanding contact centre productivity, predicting customer actions and behaviours, and providing chatbot service to customers.
However, when speaking directly to contact professionals, a common thread quickly emerges: many believe AI will replace jobs or at least play a major role in supporting agents and management so they can focus on more complex tasks.
This seems like a reasonable prospect. Examples of AI being used in a contact center extension role are already common. For example, the technology can be used to handle simple queries through 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 becoming a plug-and-play technology. Many agents will be used to spending their time fixing mistakes made by the current generation of bots or taking over customer interactions when they reach their limits. Without significant performance improvement, AI deployment is likely to be piecemeal, particularly if performance issues damage leaders’ confidence in the technology.
Harnessing the potential of AI
The obvious question to ask at this point is what can organizations do to ensure their AI strategy takes advantage of 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 analyse all relevant information when they take over a conversation. While this may seem like an obvious requirement, many contact centres currently do not have this capability and agents are left working with an incomplete picture of the customer journey. In some situations, agents may need to ask customers to repeat information they have already provided, which is not ideal for both parties in the conversation.
However, with full visibility into conversations, contact centers are in a much better position to leverage the benefits of technologies like conversational analytics to monitor and improve AI bot performance and quality. It also ensures that teams managing the AI bot experience can replace guesswork with data-driven insights to make better decisions when reviewing conversation performance and responsiveness.
With this foundation in place, organisations have a number of options for where to apply AI technologies. Today, many are finding that the obvious place to start is to use AI to better manage routine customer interactions that often occur at scale. In this context, only the most complex queries are escalated to human agents in a process that not only improves contact centre productivity but also reduces customer call wait times.
Fundamentally, it’s not just about incorporating an AI tool. Adopting 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 and also include mechanisms so that improvements can be made in light of real-world experience and customer feedback.
The human touch
Despite AI’s potential to act as a catalyst for change in contact centre environments, people’s skills, experiences and ability to empathise remain critical to the success of any strategy. With this in mind, leaders must recognise that their teams will need training and support to understand how AI technologies work, their operational role and how they, as contact centre professionals, can influence its development within the organisation.
As the pace of AI innovation continues to accelerate, it’s becoming increasingly clear that ignoring the changes the technology is already driving is not a viable option. With so many organizations using their customer service capabilities as part of their messaging, contact centers that don’t examine how AI can improve their processes run a real risk of falling behind. Guided by these insights, however, organizations have a good chance of delivering a win-win situation where contact center efficiency and customer outcomes simultaneously improve.
We list the best UCaaS providers.
This article was produced as part of TechRadarPro's Expert Insights channel, where we showcase the brightest and brightest minds in the tech industry today. The views expressed here are those of the author, and not necessarily those of TechRadarPro or Future plc. If you're interested in contributing, find out more here:
