I recently finished reading Garry Kasparov’s book ‘Deep Thinking – Where Artificial Intelligence Ends and Human Creativity Begins’. It tells the story of how one of the world’s greatest ever chess players was defeated for the first time by Deep Blue, an IBM supercomputer in 1987. Kasparov went on to become a leading light in man’s fight against the machines.

It inspired me to write this post, which is also a collection of my own beliefs and learnings that I have gained from various sources this year. Incidentally, if you are interested in AI and/ or chess then it’s a must read.

I’ve been working in around the AI space for 2 years. And I do believe that we are on the cusp of an era that will see a fundamental change in the way we live, work and relate to one another. Some academics are calling this ‘the 4th Industrial Revolution’. The previous industrial revolution was about bringing digital to billions of people. This Fourth Industrial Revolution is, however, very different. It is characterized by a range of new technologies that are fusing the physical, digital and biological worlds, impacting all disciplines, economies and industries, and even challenging ideas about what it means to be human.

But how much of the hype is true and are we really going to see machines taking over our lives? I believe its a combination of 3 things that will drive this fundamental change in the way we live, work and relate to one another and the businesses that provide us with goods and services. In a talk I gave at IBM’s Think 18 Conference earlier this year I presented this formula:

Conversational Interface + AI + Human Intelligence > Human Intelligence or Machines.

Lets delve a bit deeper.

People have been using conversation to drive sales and make customers happy since we first began trading. it follows then that conversation as an interface is the most natural way for humans to interact with technology.

According to data from BI Intelligence, global monthly active users of the top four messaging apps overtook social networks in 2014, so this isn’t really new news. Using messaging interfaces is becoming the norm when we want to communicate with each other. Why? Because its so simple and intuitive. And on top of messaging apps, over 40 million people worldwide currently own a smart speaker (such as Amazon Alexa or Google Home). This figure is likely to double in the next 12 months as we invite the technology into our homes and embed them in our lives. This clearly highlights a trend and desire from people to use conversational interfaces to engage with not just each other, but machines as well in order to get a job done.

History would suggest that technology is mainly used to reduce cost – essentially doing stuff faster and cheaper. And when stuff becomes cheaper and more efficient we do more of it. Think about the Internet and the impact its had on gaming and music for example. So what is AI reducing the cost of? In basic terms it’s reducing the cost of prediction. Using information you do have to predict information you don’t have. We will start to use it more, expanding the range of use, even for problems that we didn’t think of as prediction problems, autonomous vehicles for example. Prediction is valuable as its a key input into decision making.

Decision making is everywhere. In the world of Customer Service in particular, AI powered service and agent assisted service will grow massively. We can use AI to create Virtual Assistants that can provide accurate answers, speedy resolution and round the clock support to our customers and colleagues. In the case of agent assisted service, AI will be able to understand in real time a conversation between the customer and the service agent and be able to predict what information would be helpful for the agent to relay back to the customer.

Thanks to the computational power at our finger tips we can use Machine Learning to analyse vast amounts of data to spot patterns and predict likely events such as erroneous spending or gambling patterns, peak staffing levels, even analysing people’s spending patterns in order to proactively prevent them from getting into possible financial difficulty in the future.

Yet we should not fear AI. Yes, we should be impressed by what IBM Watson and Alpha Go have achieved – but they are machines achieving certain tasks. They cannot operate outside of what they have been trained to do.

“Carpenters are more important than hammers” – Hans van Dam Founder of Robocopy.io

People will not be spectators, instead we will be actors playing a different role in the future. People will always have common sense and an understanding of the world that can’t (yet) be coded. AI systems have limitations. They are capable of overcoming their limitations because humans exist. That’s why we have human in the loop systems. A symbiotic autonomy that helps the machine to learn. Take Virtual Assistants for example. They need intents, entities, context and variables in order to function. What people add are helpfulness, empathy and encouragement. And there are examples where the human touch is absolutely necessary – helping a customer close the bank account for a deceased relative requires empathy, compassion – traits that only people can provide.

Yes, AI reduces the cost of prediction and prediction is key to decision making. But we aren’t ready for machines to make decisions – they need to augment, support and inform the decisions we make. New roles are being and will continue to be created as AI becomes embedded in our organisations.

“By 2020 direct voice based conversation will drop from 41% to 12% of overall customer service interactions but a human will be involved in 44% of them.” – Brian Manusama – Gartner

By combining the simplicity of conversational interfaces with the power of AI to drive understanding and prediction and having humans in the loop to help with more complex tasks and to use data driven insight to make better informed decisions will be how enterprises drive step changes in both Customer Experience and Customer Experience Management (also known as the Colleague Experience).

As Kasparov says “Don’t fear intelligent machines. Work with them and dream big”

Terry Cordeiro is the Head of Product Management – Applied Science and Intelligent Products at 
Lloyds Banking Group and is a founding Steering Committee member of AITECHTalents.