I am sure we are all familiar with the Intel slogan, “Intel inside.” This has been a very powerful tagline and one that has helped Intel become the dominant PC chip supplier. (I know I was very influenced by the slogan and very rarely bought a non-Intel PC as a consequence.)
But I believe that this slogan will be rapidly replaced by “AI inside” because I believe we are almost at the point when ALL future apps will include elements of AI. I also believe there is a very good chance that Amazon’s Alexa might become the de facto automatic speech recognition platform that will sit in front of (outside) every single app in the future. (My rationale is here.)
Why do I say this?
First, you need to recognize that AI is not one singular, all-embracing technology. Rather, it is a set of technologies that hope to emulate the way a human interprets and acts upon information — albeit at the speed of light and (we hope) without error, on a 24/7 basis. As such, AI includes technologies such as natural language (voice) processing (NLP), semantic analysis and cognitive processing.
Second, these technologies have become pervasive. The CEO of IBM recently announced at Davos that Watson (a supercomputer and a collection of AI APIs) is now having a (positive) impact on the lives of some billion people (about 1/7th of the world’s population). I don’t know how many Echo and Dot units have been sold by Amazon (it must be tens of millions, at least) but each unit gives you access to Alexa, which uses both voice recognition and processing.
See also: 10 Questions That Reveal AI’s Limits
Third — and most important — you don’t need to have a degree in AI (any more) to deploy AI.
AI was notionally conceived by Alan Turing in 1936 (but, in one sense, you can trace the origins of AI all the way back to Archimedes!). I was taught elements of AI at university in the early 1970s, but I didn’t have a chance to develop an AI app until the mid-1990s when I was a consultant for the Nationwide Building Society. We had just finished a ground-breaking piece of work that involved the development and deployment of the world’s first touch-screen-driven, customer self-service system. This system was a huge success on all measures, so the client I was working for at the time asked me:
“How far can you take this idea? Could you, for example, develop a system that’s as good as — or even better than — our best sales person?”
Without knowing it at the time, he was asking me to develop our first AI system. Fortunately for me (because I am certainly not an AI expert), Accenture had just hired an authority on the subject. He was swiftly assigned to my project team, and we stepped once more into the unknown world of innovation.
We started by gathering a team of the client’s top sales people. We then sat them down with our AI expert, who had been carefully briefed on the rules governing the sale of regulated products. We also called in the services of a user experience designer to obtain a better understanding of people’s risk appetites and option requirements. Last, but certainly not least, we asked a group of customers to help us develop the system that would be designed for their stand-alone use.
The result blew everyone away.
It even won the support of the U.K. Financial Services Authority (FSA), which agreed to assess the system for compliance. The FSA tested and analyzed every aspect of the new application — and then signed off. It was the first time the FSA had ever approved a sales platform that removed the need for a sales person.
Remember, this happened in the early ’90s — long before Java, Windows 95 and the first PlayStation were launched. Our system is a tribute to a client who not only had the vision to see the possibilities but also had the courage to take on the challenge — as well as the very real risk of failure.
However, there is a sad but rather revealing postscript to this story.
What happened to this ground-breaking system? Well, it was lauded, feted and widely acclaimed — and then quietly shelved. The building society decided to focus on building its Systems of Record (SoR) rather than its Systems of Engagement (SoE). And, sad to say, that was not an uncommon fate back then. Real innovation is often too radical for most risk-averse management to stomach. Sometimes it takes time to build an appetite for the truly ground-breaking. And maybe — just maybe — 20 years later, that time has come.
There was another problem: I only had one AI programmer at my disposal, and there weren’t that many more in the U.K. at the time. Given this, it would have taken a considerable amount of time to build an industrial-strength application that could have been put into the hands of any customer. But now we don’t have that problem.
One of the firms we at Clustre represent is an AI consultancy that is AI-technology-agnostic. It conceives, designs and builds AI-driven customer and employee apps that use a variety of AI technologies — as appropriate. It was recently asked by a loyalty card operator to show how AI could be used to allow a card holder to get an answer to a query without talking to a human or having to scour through FAQs (which I think are generally pretty useless). The firm created a web-based chat bot that used Watson to help recognize and understand the question and used another product to drive the Q&A process and, ultimately, answer the question.
So clever is the bot that it can easily handle misspellings and allow the questions to be phrased in a variety of ways and still operate properly. I would hazard a guess that this tool could handle at least 50% of all customer queries (the rest would be handed off to a human to resolve). That’s a lot fewer calls that need to be routed through to a human.
See also: Why 2017 Is the Year of the Bot
So, you may ask, how many days did it take our AI consultancy to design and build this AI-driven chat bot? Just five.
Five days to design and build a tool that could potentially reduce call center volumes by around 50%!!!
AI has truly arrived, and everyone should be looking at how you are going to deploy it NOW!