Artificial intelligence has become something of a monster ever since Stephen Hawking famously warned that it could spell the end of the human race. Specifically: “It would take off on its own, and redesign itself at an ever increasing rate. Humans, who are limited by slow biological evolution, couldn’t compete, and would be superseded.”
He is not alone. Elon Musk says it could be “our biggest existential threat,” and “we need to be very careful.”
Existential threats aside, of more immediate concern to the contact centre industry is the impact of AI on that industry, most often realised in the form of ‘bots’– software that automates the functions normally performed by contact centre operators.
According to a recent blog post from KomBea, a company that produces a range of products for contact centres, “In early 2016,The Economist predicted the death of call centres from the hands of rising technology.”
The Economist was not entirely unequivocal. The article was mainly about the Philippines call centre industry and it concluded: “The Philippines is also, probably, the end of the line. New technologies are poised to abolish many call-centre jobs and transform others.
Scary stuff, but such views tend to obscure more useful discussions about what exactly AI is in the context of the contact centre, what its realistic applications are today, and what the impact of those will be in the short term. For example, this blog post How Artificial Intelligence is Use…rience Automation lists no fewer than six types of AI-driven customer service, several of which it does not consider AI at all.
Such predictions of AI’s impact, however, are far from universal. Take this one from a blog post from Nearshore Americas, an organisation formed to promote understanding and engagement with Latin America and the Caribbean, and with a focus on business process outsourcing to those regions.
“The concept of full call centre automation through artificial intelligence is a non-existent Holy Grail that the industry continues to chase, pouring untold millions and countless hours into a dream that will never come to fruition.”
It argues: “Some automation goals that industry companies are seeking are reachable. But it is simply hard to make a cost-savings argument for many of the realistic options since the investment — on top of all the ongoing costs for data engineers, speech scientists, and AI gurus to maintain systems — are so much more expensive than phone reps.”
That’s the sort of argument that might hold good today, but not one that is likely to have a long life: as the software gets smarter it will ‘just work’, requiring less customisation and ongoing specialist support, and be more easily configurable by users.
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