Will job cuts at the likes of BT and Vodafone clear the way for the adoption of artificial intelligence (AI) tools and techniques to enable these cuts?
Phil Kitchen, Director & Founder
We’re all told that necessity is the mother of invention, but today it’s probably equally true to say that headcount reduction commitments are the mother of innovation.
Over the past couple of weeks, both BT and Vodafone have announced plans for massive job cuts – 10% of the workforce for Vodafone and a whopping 40% (55,000 jobs) for BT. These cuts will take place over years, not months, and many will be on the back of natural attrition, will include the non-retention of contractors and will no doubt be eased by some attractive voluntary redundancy terms.
It won’t come as a bit surprise that both the firms themselves and the media has made much of claims that the adoption of artificial intelligence (AI) tools and techniques will be a big enabler of falls in headcount. For some, this has been a very positive illustration of the game-changing benefits AI can bring. For others, it’s a chilling harbinger of an AI-driven jobs cull.
There’s no part of the economy in which the mass adoption of AI won’t have massive potential impacts and even the true AI experts don’t pretend to know what these impacts might be; what roles and processes will be changed, upended – or just ended.
The contact centre world is far from unique in the impact that new technologies has and will have on people, but it’s way ahead most because so many AI solutions (or solutions that claim to use AI) have been deployed in the customer service and customer experience world. Bots – whether they rely on defined logical rules or have genuine AI, self-learning capabilities – have already had a massive impact on contact centres and their customers. Ultimately, the applications of AI techniques and insights in contact centres will go far wider than assisting and automating interactions with customers, but for many struggling centres they can be a great start. When applied correctly.
One of the real world examples that has contributed to the recent – understandable – clamour of concern and excitement over the impact of AI on work and jobs comes from Octopus CEO, Greg Jackson. He has gleefully revealed that that AI solutions are saving the work of 250 customer service advisors, while delivering better quality scores than humans (though head to LinkedIn and you’ll find that not all customers agree).
Ofgem figures have revealed that energy customer contact volumes have increased up to 300% through the energy price crisis. So Octopus – like all energy providers – will have had a compelling reason to seize the benefits of technology, especially in customer service.
What is maybe of note, though, is that Octopus has started with the automation of emails. A relatively low-risk, text-based, asynchronous communication channel. To do so is sensible and shows a degree of understandable caution, allowing a controlled roll-out of new technology through which quality and customer impacts can be monitored and assessed. No doubt if the achievements Mr Jackson describes are sustained then Octopus will embrace AI still further, but it seems to be doing so in the way you would hope it would any new solution; in a managed and measured way.
We’re all told that necessity is the mother of invention, but today it’s probably equally true to say that headcount reduction commitments are the mother of innovation. If you want to see an organisation rapidly seeking the productivity benefits promised by AI, then find one whose executive team has already committed to reduce headcount. Then the real organisational challenge is how they go about realising those opportunities.
The profound business and employment changes that BT and Vodafone anticipate over the next few years will obviously stretch far beyond customer service and bots. But, at its best, the contact centre world can potentially prove a useful example of how AI can be implemented in a measured, balanced way – ideally with customers and colleagues at the centre of use cases and decision making.