AI for Cost Savings? Beware the Service Recovery Paradox
By Rob McDougall, CEO, Upstream Works
The Fast Mode (July 2023)
In May, British Telecom (BT) became cannon fodder for headline writers when, during an earnings call, it sharedthat it would “unequivocally…be a beneficiary of AI.” Company leaders went on to reveal that because of advancements in automation up to 55,000 jobs at BT, one world’s largest telecom companies, would lay off approximately 42% of its workforce by the end of the decade.
They weren’t alone. Weeks earlier, IBM announced that it anticipated that nearly 8,000 of its employees would be replaced by AI. Similarly, Vodafone revealed that it would shed up to 11,000 jobs due in part to advancements in AI.
For those not in the know, this news may seem rather sobering. Those in the world of business and information technology knew it was only a matter of time. Realists accept the credo that “you won’t be replaced by AI, you’ll be replaced by someone using AI.”
In the end, AI is essentially complex information processing. Like countless transformational moments that have proceeded it, AI’s maturity has followed a familiar pattern:
- Technology (AI) advances and breaks new ground in what is possible.
- It’s proven to be repeatable, reliable, useful, and cost-effective.
- Where possible, it replaces more costly human capital resources.
- Over time, new, unforeseen jobs emerge to drive the success of the new technology.
Technology breakthroughs like AI are very exciting but can also cause a great deal of uncertainty for those negatively impacted. The best way to navigate these doubts is by educating the leaders who are making decisions on behalf of the employees, shareholders, and customers of their company and brand because rash decisions can affect all negatively.
Automation’s long tail effect on contact centers and customers
Back in the 1990s, call centers focused on how to provide increasingly good service via voice. It was an era when agents learned how to better handle phone calls. As a result, customer satisfaction numbers across the board began to improve.
By the 2000s, new channels such as chat and email were being added to the contact center process as now ‘contact centers’ endeavored to “meet customers where they were.” Each new channel brought on significant, new integration complexities that caused information about customer queries to be siloed and often incorrect. With different channels working at crossed purposes, customer satisfaction dropped.
A decade later, the industry solved this problem through the advent of omnichannel capabilities, which offered customers a seamless and unified brand experience, regardless of the channel they used. Omnichannel has been the driving force for contact centers ever since – until advancements in AI offered a new and seemingly better option.
The service recovery paradox. Customers get it, do you?
In lots of ways, AI has proved its worth. Its development has evolved to deliver reliable and useful business value. This maturity comes at an opportune time for companies seeking better and more cost-effective self-service options to help them compete.
As history has taught us, the challenge comes in its implementation.
Because AI functions vary so widely, selecting what to use, how it’s deployed, and how it works with your contact center agents requires careful consideration. Without proper planning, AI can have unintended consequences that create more complexity for the agents. It can cause increased calls, more errors, agent burnout, and ultimately customer dissatisfaction.
A customer’s impression of a brand is significantly affected by something called the ‘Service Recovery Paradox.’ It’s a phenomenon where a customer’s brand impression is improved after a service failure has been properly and promptly corrected. Indeed, contact centers play an outsized role in engendering a positive brand experience with customers.
Another important industry phrase is ‘Time to Competency,’ which refers to the time it takes an agent to both be trained on contact center systems and processes and become a high, intermediate or expert user. AI can reduce ‘time to competency’ by giving agents intelligent assistance during customer interactions. It’s a situation where the customer benefits from the integration of AI with human agents. The downside is that it can add additional AI application silos to the agent’s desktop, which offsets some of the gains made from AI.
For decision makers seeking to create a better customer experience through the use of AI within its contact center, I would recommend following these steps:
- Identify the critical importance agents bring to your brand’s customer experience, acknowledge how automation is changing the role of agents and promote its benefits.
- Consider that the brand experience is best served by using AI visibly to improve self-service options, and invisibly to improve agent abilities. Both uses will improve brand appeal by giving the customer choice along with more accurate and faster service.
- View AI as an augmentation to the agent, or as a way to provide better self-service. Customers who want to use self-service for routine inquiries will benefit from credible and well-operationalized AI applications. Agents powered by AI will be able to provide better, more consistent service. Identify mundane tasks where AI makes sense and tasks that are better performed by humans.
Contact center agents, powered (not replaced) by AI
Headlines about AI rarely reflect the context behind the situation. Yesterday, generative and conversational AI in chatbots were big news. Today, it’s how AI is proving more empathetic than humans, and tomorrow it will be something else.
While AI has become reliable for having a conversation, the act of providing an actual service still relies on proper operationalization to supply the answers that are known. Consider that regulated industries may begin requiring details about ‘why’ certain decisions were made – that’s something today’s generative AI models aren’t prepared to offer.
While it’s understandable for BT and other companies to make proclamations about staff reductions and cost efficiencies for its shareholders they must also consider the impact these decisions will have to the customer and brand.
While it is true that contact centers are an excellent place to take full advantage of AI advances, the agents that staff them remain the backbone of the customer experience. These teams most definitely need AI to quickly and accurately process vast amounts of complex information, but for the health of your brand, history tells us to proceed carefully and with customer experience in mind.
Learn how Upstream Works enterprise-ready omnichannel contact center desktop solutions help improve agent engagement and customer experience here.