Back in 2016, when we first started talking about them, we used to say that chatbots – programmes equipped with artificial intelligence that were capable of interacting with users just as human beings do – would soon supplant not only the majority of mobile applications, but also call centres and other customer service functions. We can now safely say that the revolution has begun – and a great many companies are using these chatbots for myriad different purposes. One day, perhaps, they might even replace e-commerce itself. Because while apps took a few years to take off, the road was clear from the start for the bots, which use the same chat technology that many of us use on a daily basis. The first company to open the door was Facebook, who permitted companies to embed the technology necessary for bots into their Messenger profiles. According to Oracle’s Can Virtual Experiences Replace Reality? report, 80% of companies will be using chatbot services within the next two years. In fact, it’s not beyond the realms of possibility that robotic chats will have been rendered out of date by that time, probably by other artificial intelligence and machine learning applications based on voice recognition.

Artificial intelligence: the future

According to a recent study by Accenture, companies risk missing out on significant growth opportunities if they are unable to remodel their workforce and supply all staff with the tools they need to take advantage of intelligent technology. The Reworking the Revolution: Are you ready to compete as intelligent technology meets human ingenuity to create the future workforce? study by Accenture Strategy estimates that company revenues could increase by 38% by 2020 provided that they invest in artificial intelligence and effective man-machine cooperation to at least the same extent as the leading companies are. Under these circumstances, employment levels could rise by up to 10%, while the global economy would receive a boost in profits of around $4.8 trillion.

However, there is still a gaping divide between the willingness of workers to embrace artificial intelligence and the concrete initiatives launched to retrain staff. This puts growth at risk. In fact, while 54% of company directors consider man-machine collaboration crucial for business, only 3% have significantly increased investment to retrain their staff within the next three years.

Machine learning

Machine learning is the part of artificial intelligence that describes rules and recognises patterns in large quantities of data, allowing it to predict the future. Machine learning is already part of the modern-day set-up in many companies, making an active contribution to everyday life, according to a recent study commission by ServiceNow from Oxford Economics. The study, named The Global CIO Point of View, focused on 500 CIOs around the world.

According to the results, 48% of European CIOs state that they have already moved beyond the automation of routine activities – such as security alerts – and are now looking to use automation to tackle more complex decisions (e.g. how to respond to security incidents). A full 85% of the participants state that they have chosen machine learning in order to obtain value, bring about change or take more accurate decisions, while 65% state that decisions taken through machine learning are more accurate than those taken by humans.

Tangible examples of artificial intelligence: chatbots

Flights price comparison website Kayak began using a chatbot to find better flight options for its customers, who are able to type in requests such as “I need a flight from Milan to Miami” and the bot will then ask questions about their preferred dates, times and airlines. Italian company Travel Appeal developed a chatbot for hotel chain Best Western which helps customers to design their stay down to the smallest detail. The chat will also give customers a hand in terms of purchasing clothed, food, books and more.

In the USA, big companies from a range of sectors, including Burger King, H&M and Burberry, are using chatbots to offer their customers products and online sales. In these cases, the chatbot sends messages with a range of options or encourages the user to take a specific action – whether than means paying with PayPal or a credit card or redirecting them to the brand’s online store.

More and more companies are using artificial intelligence for marketing, too. Lieviti Paneangeli has developed the first chatbot for recipes, while Fissan’s version gives advice to new mothers.

Tangible examples of artificial intelligence: machine learning

Expedia, whose site allows customers to search and book flights and hotels, features services developed using machine learning. Providing quality search results is a great challenge, given that itineraries and flight times are constantly changing. That why the machine learning tool responsible for searching out the best price has to constantly be autonomously learning and adapting. Expedia uses machine learning as part of algorithms to detect fraud. The next step is to allow customers to make travel searches using speech.

Mastercard used machine learning to automate repetitive, manual tasks, freeing up human beings to complete jobs that increase productivity. But Mastercard also using machine learning tools to boost change management throughout its range of products and services. For example, machine learning tools help the company to identify the least risky changes and flag up which require further checks. Last but not least, the company also uses the technology to identify anomalies suggesting attempts by hackers to infiltrate their systems.