Tom Allen: Chatbots – where automation and humanity intersect
By Tom Allen, Founder, The AI Journal
Historically, the term automation refers to the notion of work typically done by humans instead being conducted by machines operating within a self-governing system. In many industries, automation is not just commonplace, it’s a necessity – there’s no way that sectors such as manufacturing, automotive and medicine would be able keep up with demand without automated systems that perform tasks at a rate that would be impossible for human workforces.
But today, automation can apply just as much to the services industry, allowing businesses to hand control of business processes over to bots. And that’s largely thanks to the growth of Robotic Process Automation (RPA), something we revealed in a recent report published by The AI Journal.
While RPA on its own continues to enhance corporate process management, taking on monotonous tasks and freeing up people for higher-value work, it is its integration with AI that makes it an exciting prospect looking into the future. Chatbot technology, conversational AI and Natural Language Processing (NLP) are three terms that are spearheading this evolution.
RPA is markedly the deployment of rules-based bots which follow specific instructions, whereas Chatbot tech is cognitive and introduces intelligence into the RPA equation.
Through the application of NLP and other AI systems, RPA systems can effectively learn through experience, allowing them to become adept at customer-facing processes, such as customer service, sales and marketing; but also proficient at managing back-office jobs.
Let’s talk Chatbots and NLP
Chatbots are defined by a number of characteristics: they are applied to customer- or user-based conversations that take place by voice or text, be that phone, voice-activated interfaces, email or online chat; they are put in place to react, rather than merely automate, adapting to changes as knowledge is gleaned from data and experience; and they are intended to simulate less structured (or robotic) human conversation.
If robots had a heart, then the beating heart of Chatbots would be Natural Language Processing (NLP), the AI that governs how computer systems analyse natural language data and identify and extract meaning from contextual nuance, upon which it can then base decisions.
From a consumer point of view, NLP is already manifest in many aspects of our lives. The digital assistants that reside on our smartphones, such as Siri or Google Assistant; the auto-correction that kicks in when we tap out messages; the sifting that enables spam filters to decide what is unsolicited and unwanted email and then chuck it out; and the ability of the web to determine the intention behind our internet searches… so many elements of our digital lives are handled by NLP.
From a business perspective, the different natures of RPAs and Chatbots can complement one another to a powerful degree: conversational AI can interpret customer intent, for example, and pass on data to inform more rigid RPA-driven process. RPAs can help Chatbots tap into complex, data-driven requests, while Chatbots can make the user experience a more natural, human experience.
For example, if an employee wanted to search for specific items within an RPA system that matches purchase order to receipts, they could use a voice-activated Chatbot interface to search for information. Or let’s say a business customer wanted to book an appointment with a company but found that they cannot get through on the phone. Instead of waiting on hold, they could call or text a Chatbot, which would then activate an RPA, which schedules an appointment based on the appropriate management system.
A marriage made in heaven
The business case for employing Chatbot technology and marrying it with your RPA systems is a no-brainer, but firms can find their first chatbot hard to implement. Companies can use Chatbots to transform user interfaces by using text-based, social media-style interfaces that allow staff to engage with ERP (enterprise resource planning) systems by simply stating their request. They can foster customer loyalty by using conversational AI to bypass call centre comms and handle customer service communications in a consistent manner, 24-7 and via an array of channels or platforms (such as Google Assistant, Apple’s Siri or Facebook Messenger).
While RPAs eliminate the need for staff to do tedious administrative tasks, Chatbots can talk to and understand a person using NLP. Both are powerful forms of AI in isolation. But it is the combination of the two, the ability to build conversational process automation into a business’s data-rich systems and processes that makes it such a powerful proposition.