What is Conversational AI?

It almost seems too good to be true. A technology that can recognise speech and text, understand intent, decipher different languages and respond in a way that mimics human conversation. Best of all, it saves money and improves efficiency for the businesses that employ it. 
Probe Blog | What is Conversational AI?

Welcome to the world of Conversational AI, a concept that once belonged in science-fiction novels but has cemented itself as a must-have technology for organisations wanting to deliver exceptional customer service, enhance staff satisfaction and keep pace with competitors.

The days of people fearing ‘the rise of the machines’ are gone, with HubSpot finding 40% of shoppers do not care if they are helped by an AI tool or a human – just as long as their question is answered accurately. Conversational AI not only does that seamlessly and efficiently but, at its best, does so in a manner where it is indistinguishable from the same service being delivered by a human.

Of course, as a relatively new technology, not everyone is across the Conversational AI conversation. Late adopters are a fact of tech life and that is why we have decided to answer a few basic questions on the subject.

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What is Conversational AI?

Conversational AI is the set of technologies that enables computers to simulate real conversations. Where traditional chatbots rely on pre-written scripts to respond to a limited set of simple queries, virtual agents or AI chatbots are powered by a ‘synthetic brain’ made up of different technologies working in unison to enable a machine to understand, process and respond to human language.

Like all great digital innovations, the actual transaction is exceedingly simple for users. For example, a customer asks a virtual agent a question and receives an accurate response in minimal time. However, little do they know just how many different technologies are working below the surface to deliver the seamless experience. We do though – and we want to share that knowledge by revealing how Conversational AI works.

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What Powers Conversational AI?

Before getting too far ahead of ourselves, there are a couple of aspects of Conversational AI that should be clearly defined. They are:

  • Machine Learning (ML): this is a subfield of artificial intelligence that sees software with algorithms, features and data sets that automatically improve themselves through repeated use. Essentially, the more a Conversational AI platform is used, the better it gets at recognising patterns and using them to make predictions.

  • Natural Language Processing (NLP): this is the method used by a Conversational AI platform, with the help of machine learning, to analyse and interpret language so that it can effectively engage with humans.

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How Does Conversational AI Work?

One of Conversational AI’s greatest attributes is it uses technology to not only respond to queries promptly and accurately but continually improves its ability to do so. The process involves four general steps:

  1. Input Generation: The first step requires the Conversational AI software to receive information from the user. This can be written text or spoken phrases, with the latter being translated into a machine-readable format via Automatic Speech Recognition (ASR). This process includes spelling being corrected, synonyms identified and requests broken into words and sentences that make it easier for the virtual agent to understand.

  2. Input Analysis: It is now time to decipher what the text means. Using Natural Language Understanding (NLU) – a key component of NLP – the software identifies the intent of the request or comment and extracts other important details that can be used to help determine actions.

  3. Dialogue Management: With the request now properly understood, the focus turns to formulating a response for the user. This is done using Dialogue Management, with the response then converted into human language via Natural Language Generation (NLG), another feature of NLP. This is where Conversational AI outperforms traditional chatbots as it allows the user to receive a personalised response that feels more like conversing with a human than a machine.

  4. Reinforcement Learning: While the user may have left the interaction, machine learning now comes to the fore and analyses inputs, accepts corrections and learns from the experience to deliver a better response in the future. Essentially, as the virtual agent answers more questions, Conversational AI allows it to grow smarter and improve its responses.

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What are the Benefits of Conversational AI?

While there are multiple reasons Conversational AI is a proven winner for customers and businesses alike, there are several key drivers for organisations looking to embrace the technology.

  • Timeliness: easily one of the biggest benefits of Conversational AI is the instant response rate. The ability to answer more queries in a shorter amount of time – and 24/7 without needing to recruit more staff – is good business in anyone’s language.

  • Customer Experience: while some people may still prefer to chat with a human, the reality is direct messaging and automated responses is the preferred interaction for most modern consumers, particularly Millennials and younger generations. It’s fast, simple and ultimately what customers want.

  • Scalability: few things send a shiver down a contact centre manager’s spine more than the thought of an unexpected spike in user queries, especially when they are relying on a small team of human agents. Conversational AI mitigates this risk as it can instantly and easily negotiate a large volume of calls or messages without requiring additional staff.

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Summary

We are not alone in believing in the power of Conversational AI. IBM released a report that revealed the technology can address up to 80% of commonly asked Tier 1 support questions, while Gartner has estimated 70% of white-collar workers are now interacting with Conversational AI platforms every day. The time for debating the merits of the technology is over for companies that want to lead the way in customer experience rather than risk playing catch-up.

As further evidence of how digital innovation is a must for all organisations, discover in this case study how a transport company with more than 7 million users across the globe overhauled its technology architecture to maintain pace with growth.