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AI has started to feel like an old conversation. But the reality is that its only just off the starting blocks in many industries. In the last year, contact centres and organisations focused on customer engagement have moved beyond the AI hype into practical implementation. As such, businesses that want to stop talking and start doing should be following in the footsteps of these success stories.

There are tangible examples of AI applications already in full swing in the contact centre industry, ranging from Natural Language Processing (NLP) to image recognition.Research from industry-leading analyst Gartner suggests that in 2020, 80% of customer service interactions will be handled, at least partly, by AI. This is hardly surprising, as around a quarter of customer interactions are already handled through an automated chatbot, and the customer engagement technology sector is constantly expanding the very definition of what AI is and what it can do.

The driving force behind the AI revolution is customer experience. As this becomesthekey business differentiator, organisations that stay ahead of the curve are seeing happy, loyal and engaged customers and higher profits, by turning AI hype into tangible business success. Moving beyond the hype and towards result-driven applications of AI will be critical to the success of any company wanting to survive in this competitive landscape.

AI coupled with real-life human intelligence creates an augmented dual interface that is delivering a competitive advantage to companies wanting to offer a frictionless customer journey. An omni-channel contact centre that deploys AI working hand-in-hand with human agents is becoming critical for any organisation that doesnt want to be in the bottom quartile for customer satisfaction (CSAT).

Companies in the top quartile experience an impressive 77% less churn from their employees, and are 44% more profitable. Research has shown that the number one reason for customer service agent dissatisfaction is workload. Contact centres are eliminating the mundane tasks for their human agents through intelligent automation, and are supporting the agents ability to seamlessly handle calls with AI. This improves job satisfaction, thereby reducing the rate of attrition.

Evolving the role of human agents means less money is spent on training. In the past, data scientists who possess one of the most sought-after skill-sets would be required to process, analyse and derive insights from customer data. Now, AI-solutions are programmed to do this automatically, reducing organisations dependency on scarce and pricey skill-sets.

Not only is the contact centre industry demystifying practical uses for AI, it is also debunking the rumours about AI replacing humans. Contrary to popular belief, and as the hype may suggest, AI will not cost businesses their human face. Organisations can still leverage automation while maintaining the human touch, by providing intelligently augmented interactions.

This type of intelligent assistance means employees will no longer have to work like machines, but they will be more efficient and deliver better results. The fact is that no new technology in human history has ever created long-term, mass unemployment. There will be a period of adjustment and a need for a different skill-set. But overall, these developments will open up new opportunities for establishing long-term career prospects in customer engagement.

NLPis a form of AI that analyses natural dialogue to draw contextual meaning and understand language the way humans do. NLP registers, deciphers, understands, and makes sense of spoken language, and turns it into actionable data.This technology is a great example of both a tangible and current use of AI to achieve business success, as well as a strong argument against the idea that AI is replacing humans in the workplace.

Having information on the nature of an incoming customer call readily available means that human agents do not have to sift through huge volumes of data to answer the query. This enables them to provide a much faster and more personalised experience to the customer. NLP can also be used to help fully-automated Machine Agents to parse meaning from spoken language, enabling them to provide more accurate responses.

When a customer reaches a contact centre agent, NLP can work in the background and prompt the agent with automated information on-screen to assist them in resolving the query. Increased automation means companies will need to spend less money on training costs. NLP automatically provides a wrap summary of the conversation on completion of the call so the agent does not have to spend time at the end of the interaction completing this task. This reduces the administrative burden and frees up agents to answer more calls.

Many early adopters of this type of AI are organisations in the public sector. A combination of a tight budget and hefty workloads makes public sector organisations prepared to invest first, but many other industries are now seeing the value in NLP and rolling out the technology en masse.

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In the past, one of the biggest roadblocks of AI deployment was the limited computing resources available. But today, with hyperscale cloud platforms and vast computational power, the fully scalable AI solutions have become much more attainable. We have moved from scarcity, caused by high cost technology, to the abundance of cheap processing power.

The combination of extra computing and new AI-driven processes have really come together in the last few years. This means that organisations can easily and cost-effectively draw on extra computing horsepower to scale their contact centre capacity accordingly.

This new approach to the contact centre presents businesses across every industry with a scalable opportunity to future-proof their communications estate and keep up with customer expectations of a flawless, omni-channel customer experience. Using the latest cutting-edge tools to complement a companys existing offering should become second nature to any forward-thinking business. These are exciting times for AI, and, as we move into 2020, it is time to stop talking about AI, and start doing.

Read more: Chatbots in retail: nine companies using AI to improve customer experience

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AI in contact centres: It's time to stop talking about artificial intelligence - Verdict