Sophisticated natural language processing is revolutionizing the way we do business yielding smarter machines with human-like conversational skills. In short, chatbots and push notifications with smiling emojis are no longer your average machine conversationalists. Mainstream understanding of AI is akin to blockchain technology and SpaceX Starship, meaning only the experts get it. However, truth be told AI and natural language generation is actually much more human than you think.
Sound interesting? It certainly is, so let’s take some time to explore How AI and natural language are changing the way we communicate in business.
What do we mean by natural language
So, what is natural language. In computing, natural language is the antithesis of an artificial language. It is a human language that has naturally evolved over time. Simple enough right? Let’s take this a step further by delving into how computers use or process natural language otherwise known as NLP.
What is Natural Language Processing or NLP
Natural Language Processing or NLP is the bridge between the Natural Language and Computers. More specifically, NLP is the AI that allows computers to understand natural language. Let’s recap to ensure we are on the same page.
Thus far, we understand the following:
- Natural Language is human as opposed to artificial.
- We also know that NLP is the AI that allows computers to understand human language.
Taking this concept a step further we now get into the area of translation.
Neural Machine Translation
Neural Machine Translation or NMT is a modern technique for natural language processing. Older methods used keyword relationships to associate correct AI responses with certain questions or phrases. NMT relies on example sentence scripts. Older methods of machine translation took months and a motherload of computing power. Today, these systems only take a few hours when connected to data centers. In short, this means that our fancy web crawlers will become dinosaurs very shortly.
How Natural Language Helps Your Business
The advantages of talking machines are arguably limitless. This allows computers to process a lot of the busy work we currently pay humans to do. The simplest recognizable examples showcasing AI and NLP’s revolutionary impact include:
- Google Home
These simple machines have changed how we interact in today’s world. While technical specs behind each machine may differ they each solve a common problem we were previously unable to overcome, which is communicating with technology using our everyday voice with the goal of a specific output in mind. With AI & NLP we can now ask Siri things like, “Hey Siri, Schedule a meeting!”, and she recognizes what action should take place then performs that process. In the past based on keyword matching a great deal of conditional programming would be required for a similar process to prove successful.
Today, once the input “schedule” is requested Siri will begin by asking you for calendar dates and times. However, if you tell Siri to schedule a meeting and then a few seconds later say “nevermind” Siri will smartly recognize your human communication and say something like, “Okay I won’t schedule the meeting.” The app has the ability to perform smartly understand our natural language patterns because of NLP and AI. If the inputs we ask Siri are not in her database she can make assessments by using information stored in 3rd party databases to determine the appropriate response.
The example outlined above illustrates a similar process used by many of your current smart business applications, databases, and communication tools.
Conversational AI and consumer success
AI that uses natural language processing tools is called conversational AI. Gartner reports that 40% of business-to-customer interactions will have moved to chat channels by 2020. The purpose of conversational AI is to empower customer self-service in our human temporary absence. That way, if they can’t hear back from our communication center teams posthaste, they won’t feel as if they are being ignored.
Some other interesting points include
- Gartner suggests conversational AI can manage up to 85% of customer interaction in the future.
- Conversation AI is dynamic in recent customer experience research. Customer Think calls it “supercharging”
At the current juncture, data is still at a stage of infancy as with all new tech only the future will tell.
How has Conversational AI performed in 2019?
Conversational AI has certainly been a trending topic in 2019 from the popularization of messenger bots to IoT. We’ve seen really big strides in media. However, all hype aside let’s look at a few available studies since we all know data tells no lies.
Summer 2019 performance trends
In August, NLP systems advanced from chatbots to more integrated conversational AI systems. Recent studies by Nividia forecasted an increase of AI and NLP in mainstream applications by up to 15 %, making it a four-fold increase in just 2 years. In 2019, some NLP models exceeded human accuracy levels. This translates into a greater likelihood of NLP and AI use in our everyday lives.
Why hybrid human interaction channels are optimal
How close are we to seeing truly natural machination? The truth is there is no one size fits all answer. Yes, we have sophisticated robots and communications programs as well. However, replacing humans is not currently within grasp. It’s true, some previously human-driven tasks can now be executed by machines but human operators are still required. Yes, NLP and Conversational AI are undeniably valuable tools. However, it should not be the only tool in your business communication stack. Instead, focus on smartly applying these components into operations while continuing to prioritize the human touch.