So what is AI?
Artificial intelligence (AI) might sound intimidating, with images of the Terminator, Hal 9000, and R2D2 coming to mind, but in reality, AI is more common than you might think. It powers your Facebook newsfeed, Google search results, product recommendations on Amazon, self-driving cars, and sales forecasting, to name a few. The term AI, coined in 1954 by Professor John McCarthy of Dartmouth, refers to technology which displays any sense of human intelligence. This is done through a method known as machine learning, which is an algorithm that allows for technology to learn from examples and be able to predict future behaviour.
Your GPS is a common example of how AI can help save you time and make your life easier. By predicting which route you should take on your way home from work, based on road conditions and typical volumes of traffic at a given time, it can get you home in the shortest amount of time possible. In order to do this, it collects a large amount of data and then uses that data to train the AI, using machine learning. Machine learning trains the AI to be able to accurately predict future traffic conditions to help you reach your destination faster.
Another popular application of AI are chatbots or virtual assistants, which allow us to chat or speak to a computer. Chatbots rely on a subset of AI called natural language processing (NLP). The difficulty that AI has when chatting with a human is that what we say isn’t always what we mean. Humans have the ability to read between the lines, and understand the tone, emotion and context of a conversation. To AI, a conversation is unstructured data. NLP tries to take that conversation and analyze and interpret what the user is saying, and find meaning in that unstructured data. This data helps the AI decided how it will respond. When users say “I hit a car”, a human would automatically understand that the user’s car collided with another vehicle, whereas a computer might interpret that as the person physically hitting the car with their hand.
Virtual assistants can now connect to smart speakers, and can work with voice tech. To be able to handle voice inquiries, NLP must take the message and transcribe it into text. During this process, it breaks the message down into the smallest unit of speech. Once it does this, the computer is able to analyze and understand what the user is asking. By going through this process, it creates manageable sections of the message that the computer is then able to understand, leading to a 90% accuracy rate, matching that of an average human. Dialogue management understands how conversations flow and can change topics with the drop of a hat. With more than 1 billion people using voice tech daily, this can be an essential part of creating a flowing omni-channel experience.
Why are people in the insurance industry getting excited about AI?
There is a huge opportunity for AI to help insurance agents and carriers grow their business. Deloitte predicts that US insurance industry alone could potentially free up between 54 million and 285 million hours of their workforce time annually by implementing AI. This is done by cutting down repetitive tasks and allowing teams to focus on what is most important to their business.
Let’s talk about what’s in it for you. And your customers of course.
It’s always there. Consumer expectations have changed, with many now expecting instant responses when and where is convenient to them. Providing 24/7 support isn’t practical for most companies, but an AI assistant can handle the conversations taking place at the customer’s convenience. This allows you to connect with the customers who contact businesses outside of normal operating hours – something that is becoming a norm with the evolving customer expectations.
Scaling up? No problem. What happens when a big storm hits an area? It is difficult and costly to have enough people on call to handle a sudden influx of inbound requests. However, an AI chatbot can handle hundreds of interactions at the same time, whether your company is getting larger or there is a CAT incident.
AI can get smarter over time. For example, when you watch YouTube, the AI learns what type of content you like and will recommend more videos that are similar. It is constantly learning more about you and your viewing habits over time. An insurance AI platform can do the same thing for your business; learning how your customers talk about insurance and then being able to respond in a conversational way. When the AI is not able to respond to a question, it can ping your team to switch to a live agent while using their answer to help respond to similar questions in the future.
Empowering your team. How often have you had a phone call come in from someone with a simple question? You want to answer their question but with many incoming requests, it can be hard to triage effectively. The cost of a call is rising to around $20 per call, and an AI assistant can be a huge benefit of lowering your expenses. Let the simple questions be answered quickly and efficiently so you can focus on other tasks
Don’t get siloed. Did you know that 75% of consumers are expecting a seamless, multichannel experience, with 73% willing to switch brands if they don’t get it? Consumers are now expecting a variety of platforms that are able to transition from web to mobile. In a study done by Forrester, 90% of people switch between an average of 3 devices a day, meaning the interface is constantly changing. Additionally, more than 50% of online users also use two devices at the same time!
Time is money. By implementing AI, the US insurance industry can save up to $8.9 billion annually. Give your clients fast customer service they can trust and spend those extra hours on high value issues.
Is AI taking over the insurance industry?
While it may not be taking over the world, it’s definitely part of the future and companies are now seeing the value implementing AI technology. IDC predicts that it will be worth $43 billion by 2020, and by 2021, more than 50% of enterprises will spend more per annum on bots and chatbot creation than traditional mobile app development. Customer service in particular will be a big area for incorporating AI, with 8 out of 10 businesses adopting some sort of it by 2020. The development of autonomous customer service makes it difficult to compete with, meaning it’s no longer good enough to stick with the status quo.
Additionally, according to EY, millennials will account for 75% of the workforce population by 2025, and the famous technologically advanced generation is more prone to look for convenience and multi-platform approaches. Subsequently, in a survey done by Arise, nearly two-thirds of all participants claimed that they would only be willing to wait two minutes or less before hanging up. With the fast-paced consumer environment that we live in, people are now searching for instant gratification in their purchases, as seen with the rise in Uber (and Uber-Eats) and Amazon. Jump ahead of your competitors and reach the 56% of people that seeking to buy from the most innovative companies.
How can Insurance Companies utilize AI today?
Insurers should look to deploy AI into their operations so that they are able to use their capital and talent towards more complex tasks. Companies should leverage the available technology to further improve their top and bottom lines, and keep up with the evolving industry. Developing your own chatbot for your company may not be a feasible option but ProNavigator, an 100% insurance-based AI company, can make that an achievable part of your 2019 digital strategy.
If you want to empower your team, save time and money, and provide a predictably great service for your customers, then think about adding an AI-powered assistant. The easy, predictable, and smart way of improving your business.
Deloitte. (2018). 2018 Insurance Outlook – Shifting strategies to compete in a cutting-edge future. Retrieved on January 10, 2019 from https://www2.deloitte.com/content/dam/Deloitte/us/Documents/financial-services/us-fsi-insurance-2018-outlook.pdf
Gartner. (October 3, 2017). Gartner Top Strategic Predictions for 2018 and Beyond. Retrieved on January 7, 2019 from https://www.gartner.com/smarterwithgartner/gartner-top-strategic-predictions-for-2018-and-beyond/
Kelnar, D. (December 2, 2016). The Fourth Industrial Revolution: a Primer on Artificial Intelligence (AI). Retrieved on January 7, 2019 from https://medium.com/mmc-writes/the-fourth-industrial-revolution-a-primer-on-artificial-intelligence-ai-ff5e7fffcae1
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Mills, T. ( July 2, 2018). What is Natural Language Processing and What is it Used For?. Retrieved on January 7, 2019 from https://www.forbes.com/sites/forbestechcouncil/2018/07/02/what-is-natural-language-processing-and-what-is-it-used-for/#1c36498b5d71
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