Try to imagine a company without the internet, without telephones... impossible, isn't it?
Now, project yourself 10 years into the future and imagine a company that does not exploit artificial intelligence. If you're a visionary, you know that's impossible..
But why?
Artificial Intelligence is THE technology of the future. And like all useful technologies, it is being widely exploited by businesses to accelerate and improve their activity(ies). If we were to compare what we know and can do with AI today, and what we know and can do with the Internet today, we could say that we are at stage (I)ARPANET
But the aim of this article is not to project us into the future by imagining the artificially intelligent world of tomorrow, but to take a look at the solutions offered by AI technology today.
During my visit to the AI trade fair in Paris on 6 and 7 June, I had the chance to meet around twenty companies offering solutions to businesses using artificial intelligence technologies. They all (or almost all) have one thing in common: they exploit data.
Data, an asset in its own right
Data is an increasingly important element in businesses, and is sometimes even considered to be an asset in its own right. The value of exploiting data becomes clear when we look at how artificial intelligence technologies work.
Most of the companies I've met use Machine Learning technologies. In short, these technologies are not thinking, but are capable of learning. In fact, with time and training, artificial assistants evolve and become more and more efficient. If the algorithm doesn't understand a given problem, it will use the experience it has had before to find an answer. So you can see the importance of data in this race for progress.
Chatbots and voice assistants
Areas of expertise :
- Social networks
- Pre-sales services
- After-sales services
- Customer Support
- F.A.Q
Usingsemantic analysisChatbots and voice assistants are becoming more and more widespread, and are now playing a major role in the projects of companies with important customer relations. For example, the major telecommunications group Orange has teamed up with DoYouDreamUp to develop its ChatBot, which is now in place on their customer service.
Knowing that we have 20% of questions which represent 80% of requests, most of these requests offer little added value to the company. This type of request, such as cancellations, access to invoices, etc., can therefore be handled by these bots, which redirect callers to advisers if necessary.
What's more, these chatbots are able to recognise a language and suggest solutions by guiding the enquirer through their requests.
So it's frightening that these 'intelligent' machines, which cost next to nothing to run, are unscrupulously taking over the work of advisers. But at the moment, that's not their job.
By enabling advisers to stop wasting time on low added-value tasks, they can devote themselves fully to more interesting projects that the machines can't yet handle. So for the time being, it's a good thing, because employees can invest more in the company and in development projects.
With a view to passing (or failing) the Turing test (if a human doesn't know he's talking to a machine, then the test is passed), companies are increasingly working on humanising conversations. Chatbots sometimes use humour and even emojis to make the exchange between man and machine as real as possible.
Predictive analysis
Predict when a customer is going to leave their bank or insurance company so that you can approach them and offer them your services. NeXXaian innovative start-up present at the show. Knowing the water consumption of African countries in order to adapt flows is a solution proposed by Invenis for the CityTaps.
Digitising networks and analysing flows, recognising images and predicting violent or suspicious behaviour... predictive analysis is the other major trend in the use of artificial intelligence technologies.
By analysing past data, the algorithms are able to predict consumer actions, equipment breakdowns or even risky or suspicious behaviour in crowded places (on a quay, for example) with an impressive degree of reliability (up to 99.5%).
This technology can be used in virtually every field. Take the SNCF, for example. By digitising its networks and interconnecting all the available information, what could predictive analysis bring to this rail transport giant? Predicting the number of passengers to adapt the number of trains to be deployed, predicting the breakdown of a train so that it can be sent for repair, or analysing suspicious behaviour using security cameras to help the railway police in their hunt for criminals... All these analyses, which are very complicated or even impossible for a human being, can be carried out by intelligent machines and their use of Big Data.
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