Learning through adversity: how Covid-19 reprogrammed the role of AI

Martin Taylor, deputy CEO at Content Guru, discusses how the events of 2020 have reshaped the contact centre.

In the spring of 2020, reacting to the onrush of the coronavirus pandemic was the number one priority for all organisations. Adapting operations to the ‘new normal’ was non-negotiable, backed by force of law. Few sectors saw greater impact than the contact centre, which experienced immediate and profound changes both in customer behaviour and in demands from government as to how and where its staff should work.

While the future remains an unknown, one thing businesses can take from the experience of 2020 is knowledge – crisis as learning opportunity. While many businesses struggled to maintain operations in face of international lockdowns, many of the changes that emerged will shape the contact centre industry for years to come.

Stretching beyond inelasticity

One factor that became apparent early on in the pandemic was the danger of solely relying on humans to staff operations when they are so susceptible to illness. Humans now have their movements restricted at short notice, making them effectively unavailable when needed. In the contact centre industry, the inelasticity of human headcount when trying to cope with exponentially-increased demand took an immediate toll on customer experience. In many cases, artificial intelligence (AI) was advanced from the drawing board to the front line at unprecedented speed to deal with the unmet demand.

Additional volumes of enquiries and periods of limited employee supply must now be baked into future planning. Real-life examples make this crystal clear: the NHS 111 service was not possible to match the 500 per cent increase in call volumes due to Covid-19 with more call handlers. Instead, the urgent care system needed to deploy smart technology to analyse and queue calls, servicing some with automated signposting and digital information sources to curb demand.

Going the distance: social distancing

Groups congregating in large numbers is now a highly contentious idea. People are wary of being too close together and want to distance from one other wherever possible, to protect themselves from the virus. In hospitals, contact-centre-like technology has been introduced to help achieve this. Video consultations between doctors and patients have become vastly more popular since the beginning of the pandemic, to prevent busy waiting-room areas from becoming infection hotspots and enable elderly or vulnerable clinicians to keep working.

Moreover, hospital emergency departments must now deploy booking systems to avoid mixing those with the virus and those without. Patients are divided into ‘lanes’ depending on the severity of their symptoms, and are permitted to enter the hospital at the appropriate time, and not before. Just as in a contact centre queue, estimated times to clear each lane are continually recalculated and updated, then communicated to the patients, who can now arrive moments before they will be seen, maximising both safety and convenience.

These are just a couple of examples of how tools, techniques and technologies perfected by the contact centre are now seeping into more ‘everyday’ settings and interactions.

The sentiment around AI 

Practically speaking, AI encompasses three general purpose technologies: image recognition, Natural Language Processing (NLP) and sifting large amounts of data. The latter part is now in-play, yet there has been an historical reluctance to work with peoples’ data, often expressed through privacy concerns. At the same time, consumers expect and demand personalised services. As the latter gains the upper hand over the former, with data responsibly and securely managed, AI will flourish further even than they are already.

A large majority of the world’s population are actually already using AI without realising it. For instance, Google Search knows what a user searches for, as well as their locations and preferences. Soon, virtually all of us will be interacting with AI when dealing with many organisations as customers, citizens or patients.

AI offers a network of technologies that make us as efficient as we would be working in an office, sometimes more so. It can support the successful remote on-boarding of new staff by providing reliable mechanisms for continuing to work from home and collaborate more effectively. The next step is to develop new ways to measure that other management shibboleth, ‘productivity’.

And the moral of the story is…

AI now makes sense in the majority of operations – and nowhere more so than in the front-line of mass human interaction: the contact centre industry. One size has never fitted all. Now is the time for businesses seeking competitive advantage, and public sector organisations needing to become dynamic, to seize the possibility that AI technology offers to take consumers and citizens to the promised land of mass-personalisation.

 

 

 

 

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