In business, we often trot out the same set of innovation leaders over and over to illustrate where the world is going. Elon. Mark. Sergei. But there’s one name you might not have heard of – Sophia.
Heard of her? She’s been in the insurance industry for only a year so far, but has already made a big impression. She reckons she can do things better and faster than her peers. She shouldn’t be confused with Sofia, a knowledgeable Portuguese beauty who works for TAP Airlines.
What about Dom? He works at a pizza restaurant, but spends most of his time on social media. Despite this, he’s good at his job – send him a Facebook message and he can have a pizza delivered just the way you like it.
And then there’s Alexa. But you probably already know her. She’s got a rivalry going on with Siri as to who can run the best household.
Yes, chatbots and virtual assistants are on everyone’s mind. But are they all they’re cracked up to be? Can AI and machine learning really live up to the hype? You could ask Alexa or Siri themselves, but they seem more interested in deferring to the top search results than giving their own opinion on the matter. Point against?
The bot in the back
Siri may not yet be able to answer the tough questions, but I can certainly take a stab at it. Before we get into the good stuff – robot Mickey Mouse and DeepMind fighting cancer – let’s get one thing straight. 2017 is not the year of AI, at least not in the business world. Machine learning and smart analytics have been a mainstay of the back office for years.
So much so that if you don’t already have back-end automation, I’m sorry to say you’re looking suspiciously like a VCR owner in the age of Netflix. Overseas, they’re exploring cognitive analytics, and rolling out technologies like Salesforce’s Einstein, that can take inventory using visual recognition.
Here at home, all of the major players are in the midst of deep automation. Barclays Africa, for example, has digitised over 100 of its back office processes, while Momentum has been similarly dedicated to automating its back-end processes. And it’s been paying off big time – McKinsey has found back-office digitisation more profitable than multichannel integration.
But let’s be honest – you’re probably not reading this article to learn about how Company X has automated its financial systems. The real fun stuff is the front-end, because now they’re not just working in the background of big corporates as the world’s most tireless office workers, they’re serving us food, helping us plan our outfits, making us dinner, booking flight reservations, and running our home.
Machines in our everyday lives
Deloitte predicts that by the end of this year, 300 million smartphones (a full fifth of all units sold) will have some form of network machine learning capabilities. And of course, you can’t throw a stone without hitting a company that’s rolled out some sort of chatbot.
What about applications beyond a Facebook chatbot taking your pizza orders? As machine learning capabilities continue to expand, the limitations to what we can do will only be bound by our creativity.
At TransUnion, we have technology that uses artificial intelligence to detect loan fraud in real time. Such technologies are only set to become more commonplace in the financial services industry. Could the scenario of an ATM scammer grabbing half your cash before you have a chance to do anything be a thing of the past?
Discovery meanwhile has a sensor you can install into your car that automatically alerts emergency services when you’ve been in an accident. The insurance and healthcare industries are likely to look radically different in the next decade thanks to advances in AI.
Rwanda already has its own drone delivery service to deliver blood to remote areas of the country, and is planning on building the world’s first drone airport. Now imagine if this ‘droneport’ used AI to automatically dispatch drones to fight poachers or bring disaster relief.
Are you ready for robots?
Alright, so now that you have a small taste of what AI can do, you need to ask yourself how you can bring it to your own brand. The most important thing is to get your systems in place to be able to implement automation in your business. Secondly, you need to nurture the right skills among your employees – or find alternative ways of sourcing those specialties. Finally, there’s the challenge of data – making sure you can manage and standardise it, so you can use it across different systems.
And while chatbots might not quite be able to answer life’s most probing questions just quite yet, they make for a good complement to your existing digital strategy. Facebook has recently opened up its Messenger Chat Bot to developers, so there’s no excuse not to pilot a chatbot for your own brand – cutesy name optional.
What do you think about chatbots and AI? How closely has machine learning touched your industry?