If 2024 was the year of AI hype, surely 2025 is set to be the year of measurable value.
The separation of promise from reality, if you will.
The pragmatic deployment of the right AI-powered tools, in the right place; backed by the right evaluation processes and the right level of investment.
AI will continue to shape the future of the workplace, of course. However, next year’s phase of that evolution can be likened to the great Gold Rush: an event that occurred almost 180 years ago. Now, just as was the case then, having the right tools is essential, but they are worthless unless you know where to dig.
Today, when it comes to contact center technology, businesses of all types and sizes (and their service providers) must take the same balanced and pragmatic approach to the deployment of AI and partner with a vendor capable of ensuring success.
“The successful gold miners analyzed data, studied maps, followed streams, and searched methodically. The moral of the story? Tools are critical, but they only create real value when applied to solving meaningful problems,” says Matt Yates, Vice President of Engineering at MaxContact, which has developed Spokn AI, a speech analytics platform designed to help its customers make the right decisions.
“2024 was the year of AI hype with some analysts suggesting it could fuel a 90%+ increase in productivity and other estimates pitched at more like 25%.
The reality is that we see a lot of potential for AI to automate a lot of the things that contact center workers do on a day-to-day basis. That means saving a lot of time and generating large productivity gains.”
Indeed, research carried out by MaxContact suggests a 20-30% increase has occurred in the efficiency of AI-assisted humans, despite 93% of contact centers reporting that they use AI in some capacity or another. Tellingly, 76% of contact centers questioned say they plan to invest further in AI in the coming year.
No wonder, too. Rising operational costs, an increase in the UK minimum wage, and a rise in employers’ National Insurance Contributions mean agents are becoming a more expensive resource, and businesses’ bottom lines are being squeezed.
And yet, although AI-powered automation of simple tasks can help increase efficiency and reduce costs, it also brings challenges in the form of implementation costs, staff training and a pressure to prove a return on investment (ROI).