Talk is cheap - why making AI deliver is a necessary New Year's resolution

Why enterprises need to stop talking about AI and start doing it

This is a contributed article by Martin Taylor, Deputy CEO at Content Guru.

AI has seen more than its fair share of hype and, in many industries, it's still at a stage of relative infancy. But, for organisations focused on customer engagement, AI hype has given way to practical implementation in the contact centre. The technology is now at a stage where it's making a real difference - and for the contact centre industry as a whole, it's charging towards widescale adoption. This momentum - turning AI talk into real action - is something all businesses in the technology landscape should be waking up to, plotting this into 2020 roadmaps and beyond.

Across the contact centre industry, there are a range of AI applications already being adopted, from Natural Language Processing (NLP) to image recognition. Its impact should not be underestimated - according to research from Gartner, in 2020, 80% of customer service interactions will be handled, at least in part, by AI. Given around a quarter of customer interactions are currently handled through automated chatbots, adoption of AI is high up the list of 2020 priorities for many organisations across the industry. 

The key driver for this is customer experience, which is fast becoming the key business differentiator. Organisations are turning to AI to build stronger relationships with their customers, which - in a modern business landscape where customer loyalty is vital - translates into tangible business success.

Blending AI with human intelligence 

While it's important to focus on result-driven applications of AI as part of a wider customer-focused strategy, it's not just about focusing on technology to the exclusion of everything else. AI needs to be blended with real-life human intelligence to create an augmented dual interface as part of an omni-channel approach. This is becoming critical for any organisation that doesn't want to end up at the bottom of the pile for customer satisfaction (CSAT).

The benefits of this approach are profound. Companies in the top CSAT quartile report a 77% less churn from their employees and are 44% more profitable. A primary reason for employee dissatisfaction across all industries is workload. Organisations that are able to eliminate the mundane tasks for their employees through intelligent automation can improve job satisfaction and minimise staff turnover, all while delivering a better service for their customers.

The benefits also extend to wider savings on areas such as training. Data scientists, for example, who possess one of the most sought-after skill sets have historically been required to process, analyse and derive insights from customer data. In the burgeoning AI era, automation helps reduce organisations' dependency on scarce and expensive skill-sets and allows expertise to be applied to more strategic tasks.

Busting AI's biggest myth

The contact centre industry is also helping to address AI's ‘elephant in the room', which is the persistent fear that AI will replace humans. Contrary to popular belief, organisations can still leverage automation while maintaining the human touch, by providing intelligently augmented interactions.

In practical terms, what's likely to play out across the commercial landscape is that employees will no longer have to work like machines. Aided by automation and AI augmentation, they will instead be more efficient and deliver better results. We should also look to history as a guide - no new technology has ever created long-term, mass unemployment. Even though there will be a period of adjustment and a need for different skill sets, overall, the adoption of AI will actually open up new opportunities to establish long-term careers.

Speaking our language

The growing adoption of NLP is a great example of how AI is helping - not replacing - humans in the workplace.

By analysing natural dialogue to draw contextual meaning and understand language the way humans do, NLP turns spoken conversations into actionable data. Having information on the nature of an incoming customer call readily available, for example, means human agents don't need to manually analyse large volumes of data to answer a specific query. As a result, they can provide a much faster and more personalised experience to the customer. In addition, NLP can also be used to help fully automated ‘Machine Agents', or chatbots, derive meaning from spoken language, enabling them to provide more accurate responses.

For instance, when a customer reaches a contact centre agent, NLP can work in the background to prompt the agent with additional information to assist in helping the customer and improving the experience. NLP systems can also provide a summary of the conversation on completion of the call, saving agent time and reducing admin burden, so they are free to spend time adding greater value on customer calls.

Moving confidently into the future

Until relatively recently, limited computing resources have put a barrier in front of wider AI adoption. However, the ubiquitous availability of hyperscale cloud platforms and vast computational power, means fully scalable AI solutions have become much more practical. We have moved from a position of scarcity, caused by high cost technology, to the abundance of cheap infrastructure, ideally suited to deliver AI. The result is that organisations can easily and cost-effectively draw on extra computing horsepower to scale their AI-powered capacity.

The bottom line is that AI presents businesses across every industry with a scalable opportunity to future-proof their communications processes and provide a flawless, omni-channel customer experience. But talk is cheap. Those organisations that act now to build AI into their contact centre strategies in 2020 and beyond will be far better placed to compete in this exciting new era.

Martin Taylor is one of the co-founders of Content Guru, responsible for strategic market development and the company's public sector practice. A pioneer in real-time billing, Taylor's early work with deregulated telecommunications operators led directly to the multi-tenanted, multi-level, multimedia accounting platform that underpins Content Guru's cloud services. He also devised a number of important interactive media and payment applications that are today commonplace around the world.