Artificial intelligence has been in our lives for years. Our Facebook timelines, our Spotify recommendations and the virtual assistants we entrust simple tasks to every day are all AI driven. Of course, these examples are little more than just playing with artificial intelligence, but in the coming years, the evolution of AI will see companies use it to offer significant added value to their customers. This will happen in six steps, each with increasing impact.
1. Curation of information
The current Google interface was developed in the previous century. For each search we get dozens of pages with hundreds of links, but of course, nobody bothers to search through all those pages. Information overload is something that we all try to avoid, and while Google keeps developing to help us, it is still essentially an old interface that gives its visitors far too much irrelevant information.
Artificial intelligence helps to curate content. Facebook is an excellent example. Instead of us making the choice, computers make the choice of what we get to see and what is blocked out. For retail platforms this is a major opportunity – a really good AI interface will use data to only suggest clothes that it knows match your taste.
2. Provision of customised information
When your smartphone lets you know it's time for you to set off for your next meeting, taking into account the current situation on the roads, this is a good example of how AI can provide customised information. It uses different data sources to offer content that is tailored to your personal needs.
Today, simple questions can be answered almost instantly by smart interfaces like Siri or Alexa. In the future, much more complex questions will also be possible. Before long, our virtual assistant will become our main source of help for all our daily queries and problems. This application has huge potential for governments – thousands of us have questions about taxes, opening hours and hundreds of other things, and this level of AI could give you a concrete (and correct) answer straight away.
This has already been part of most e-commerce sites for years, but the quality of these recommendations will improve. The more data that is available about an individual user, the more targeted the resulting recommendations will be – Blackrock has been getting recommendations from its AI interface about the buying and selling of shares since March 2017.
Prediction is at the very heart of artificial intelligence. Self-driving cars need to predict what other drivers are going to do, banks wants to know in advance if a customer is likely to repay their loan, but as the quality of AI predictions increases, the products that are dependent on the predictions will fall in price. Decisions will be taken more quickly, fewer mistakes will be made and the quality of the end product will improve correspondingly.
The same process will also be seen at company level. Looking at the elements in your business process that can benefit from more accurate predictions will become a standard part of most companies' AI strategy. Every company has activities that can benefit from accurate predictions.
In a first phase, many clearly defined steps in the customer journey will be mechanised. Chatbots can take over customer service, self-driving vehicles can take over transport, even the basic output of the accounts and legal departments can be automated.
The second phase involves the full automation of many aspects of our daily lives. Our cars will drive us, instead of us driving them. Our basic daily necessities (washing powder, coffee, corn flakes, etc.) will be ordered and delivered automatically, on the basis of input from a machine. We are moving from e-commerce to a-commerce: automated commerce. It might sound futuristic, but the building blocks are already in place to make this happen.
6. Contextual analysis
In this final phase, AI will be able to perfectly understand the context of the consumer. At the moment, your Netflix account can only take your past viewing preferences and that of similar customers into account. Once the context can be analysed properly, the level of the recommendations – and the level of automation – will improve dramatically to even reflect your mood at that moment.
To make contextual analysis possible, the AI interface will not only search for data in a well-defined silo, but will scan all available data. The complexity of such an analysis is huge – you can best compare it to the way people converse with each other. At the moment, this is a form of empathy that is only possible between people, as we have the ability to take account of all the different parameters when they talk to someone else. The day that a computer or robot is capable of making the same analysis, that will be the day when one of the most important distinctions between humans and machines falls away.
Steven van Belleghem is an entrepreneur, marketing professor at Vlerick Business School and author of Customers The Day After Tomorrow.
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