Why Every Company Needs An Artificial Intelligence (AI) Strategy For 2019
There’s no doubt that artificial intelligence (AI) is a transformative technology – perhaps even the most transformative technology available today. But if you think the transformative nature of AI is limited to global tech giants and blue-chip companies, think again. AI is ultimately going to transform every business, in every industry.
That’s why every company needs an AI strategy.
Like any business transformation, if you want to get the most out of AI, it all starts with strategy. Your AI strategy will help you to focus on your core business objectives and prioritise ways that AI can help deliver those business goals.
In general, there are two ways businesses are using AI to drive success:
- Creating intelligent products and services
- Designing intelligent business processes
Let’s look at these two uses in a little more detail.
Intelligent products and services
AI is, at heart, about making machines smarter, so that they can think and act like humans (or even better). We need only look at the popularity of devices like smart phones, smart fitness trackers and smart thermostats to see how consumers wholeheartedly embrace products and services that can make their life easier, smarter, more streamlined, more connected.
So it’s no wonder that businesses are increasingly looking for ways to make their products and services more intelligent through AI. Google’s search algorithms are an obvious example of an AI-driven tool. Amazon’s Alexa is another. Social media platforms also rely heavily on AI.
Chinese company ByteDance is, at the time of writing, the world’s most valuable startup. If you haven’t heard of them yet, you soon will. ByteDance product TikTok was one of the most downloaded apps of 2018. (If you’re wondering, it lets users create and share short videos.)
Another ByteDance product is Toutiao, which, thanks to its combination of search engine, news and social media, is often referred to as ‘Buzzfeed with Brains’. Unlike Facebook and other social media platforms, Toutiao doesn’t generate news feed content for its users based on who they’re following; it uses AI to display a continuous stream of content that’s based on what the platform believes that user wants. In other words, it gets to know you as a user and recommends content based on what it believes you like and don’t like.
Setting aside these obviously techy examples, AI is also being used to produce smarter versions of far more traditional products. Vehicles, for example, are now much smarter than they were 10 years ago and can perform a range of tasks autonomously, from perfect parallel parking to alerting a driver who’s starting to nod off at the wheel. More and more vehicles can drive autonomously, as well.
Even Barbie has had a smart makeover. The Hello Barbie toy uses natural language processing and machine learning (both subsets of AI) to listen and respond to a child. Inside Barbie’s necklace is a microphone that records what the child says and transmits it to a server for analysis. Then, choosing from 8,000 dialogue options, the system chooses the most appropriate response for Barbie to say. All this happens in under a second.
What’s more, Barbie remembers useful information from conversations, such as the child’s favourite food or favourite pop star, to use in later conversations. In effect, Barbie learns what your child likes and dislikes, so she can hold more intelligent conversations. Creepy? A little, yes, to my mind. But it goes to show how even the most unexpected products are becoming smarter.
Intelligent business processes
AI is being used to help businesses across all sectors optimise and automate business processes. This can be as simple as automatically recommending product B to every customer who bought product A, based on the preferences of other customers. Or it can be as complicated as fully automating an entire production line. For most companies, the biggest AI opportunities lie somewhere in the middle.
For example, credit reference agency Experian is using AI to crunch through its masses of data and make quicker, smarter decisions on credit scores and so on. American Express is doing a similar thing by using AI to detect fraudulent transactions in pretty much real time.
Predictive maintenance is another example of AI-optimised processes. This involves using sensors to constantly monitor vehicles and machinery to predict when parts might fail. (The idea being that, if you know when something is likely to fail, you can replace it beforehand and minimise downtime.) Volvo is using this technology to predict part failure and provide more accurate information on when vehicles need servicing.
Thanks to natural language processing and generation, machines can also be used to communicate with customers. In fact, customer service chatbots and messaging chatbots are now pretty much mainstream. But did you know that AI can also be used to generate longer, more specialist content? In the UK, the Press Association has partnered with news automation company Urbs Media to get robots writing thousands of news articles each month.
Finding the right AI use for your company
The right use for you will depend on what your business is trying to achieve. That’s why your AI strategy (here is an AI strategy template) must be driven by your overarching business strategy. So before embarking on an AI strategy, it’s vital you review your business strategy first.
Then, when you’re crystal clear on the business’s organisational goals, you can start to look at ways AI can help you achieve those objectives. To help you define your AI use cases for your business, using an AI use case template.
Originally published March 21, 2019 by Bernard Marr in Forbes. Bernard Marr is an internationally best-selling author, popular keynote speaker, futurist, and a strategic business & technology advisor to governments and companies. He helps organisations improve their business performance, use data more intelligently, and understand the implications of new technologies such as artificial intelligence, big data, blockchains, and the Internet of Things.