How are businesses using artificial intelligence? 13 enterprise uses for AI and machine learning
Many aspects of artificial intelligence such as neural networks and deep learning may not be entirely new. But the technology is now increasingly accessible for developers, with tech vendors offering a range of APIs and frameworks that allow businesses to create their own services.
Most businesses are at very early stages of adoption, however there are a growing number of examples where the technology is being used to optimise back office and consumer-facing systems and processes.
Here are just some of the enterprise use cases around machine learning and AI...
Ocado is building a computer vision system and network of 4G connected robots in an effort to replace barcode scanning in its warehouses.
The machine learning project is still in development but Daniel Nelson, head of data at Ocado's technology division, told Computerworld UK that they hope the technology will help both within its warehouse and delivery processes.
2. Fukoku Mutual Life Insurance
Japanese insurance firm Fukoku Mutual Life Insurance is replacing its 34-strong workforce with IBM’s Watson Explorer AI.
The replacement artificial intelligence system will calculate insurance policy payouts, which the firm believes will increase productivity by 30 percent and save around 140 million yen (£977,000) a year in salaries.
While the savings are significant, the initial cost of setting up IBM Watson is estimated to be 200 million yen (£1.4 million), and annual maintenance is expected to be about 15 million yen (£105 million).
The Watson-based system will be able to analyse medical certificates, surgery and procedure data and hospital stays and calculate the relevant payout.
The NHS is to trial an AI-powered chatbot on the 111 non-emergency helpline.
Being trialled in North London, its 1.2 million residents can opt for a chatbot rather than talking to a person on the 111 helpline.
The chatbot, created by Babylon Health, encourages people to enter their symptoms into the app, it will then consult a large medical database and users will receive tailored responses based on the information they've entered.
According to the Telegraph, this six-month trial aims to "reduce pressure on the NHS during the winter and beyond."
The car hailing service Uber has a core team providing pre-packaged machine learning algorithms 'as-a-service' to its team of mobile app developers, map experts and autonomous driving teams.
Head of machine learning at Uber, Danny Lange told Computerworld UK: "We have really had machine learning for a while but it is something that can be really hard for software engineers to get. So we have created machine learning-as-a-service inside the company as a cloud service.”
Uber uses these capabilities to better predict your travelling habits within its core mobile application, improves its maps using computer vision and create algorithms for its autonomous vehicles.
5. Auto Trader
The online car marketplace Auto Trader has a data science and insights team of thirty people, and is currently building a cluster with open-source database specialists MongoDB to store derivate data - for example, the year a specific model of car was manufactured. Having a database capable of recognising this ensures customers are being delivered accurate valuations.
Mohsin Patel, principal database administrator at Auto Trader told Computerworld UK: "We have to teach our systems depending on what features a car might have, or what derivate of a car the customer is viewing as the price could differ, and that's where the [machine] learning comes in."
Flight and hotel search and booking site Expedia told Computerworld UK that its core services were “built on machine learning”.
David Fleischman, VP of global product said delivering quality flight search results is an "unbounded computer science problem" because flight itineraries and schedules are constantly changing. This is why Expedia's proprietary 'best fare search' (BFS) has to 'learn' and adapt all the time.
Expedia also uses its significant in-house machine learning resource – 700 data scientists and counting – to create algorithms for detecting fraud. Next it wants to allow customers to make travel queries using natural language. “The main goal is to answer a traveller's question and we use machine learning to solve that discovery problem," Flesichman said.
7. Royal Bank of Scotland
Earlier this year, Royal Bank of Scotland announced the launch of Luvo - a natural language processing AI bot which will answer RBS, Natwest and Ulster bank customer questions and perform simple banking tasks like money transfers. If Luvo is unable to find the answer it will pass a customer over to a member of staff.
While RBS is the first retail bank in the UK to launch such a service, others such as Sweden's SwedBank and Spain's BBVA have created similar virtual assistants.
RBS’ head of digital, Chris Popple says that the aim is to “make digital customer support as powerful as face-to-face”.
8. Royal Free Hospital
The Royal Free Hospital in North London announced a partnership with Google’s DeepMind in February to build a mobile app that helps hospital staff monitor patients with acute kidney injuries.
According to Thomas Davies, Director of Northern, Eastern & Central Europe, Google for Work: “DeepMind is a general tool, we have just decided to go deeper into this one particular area. We hope to find some significant frontline benefits to the doctors and nurses.”
“It is very much around putting data content applications into the hands of frontline staff to do their job better.”
Expedia, which has been providing online travel booking for 20 years, is using machine learning algorithms to improve recommendations for customers.
According to Matthew Fryer, chief data science officer at Expedia: "Fundamentally AI is the core of why we exist: to find the right flight, holiday, experience for you. By far one of the biggest use cases on our site is mining search and user journeys to find the perfect product for you."
Marc Florette, chief digital officer at French multinational energy firm, Engie, says that the company is using a combination of drone and AI image processing technology to inspect its infrastructure.
"We have two or three main areas we can use AI and will focus on assets,” he says. “We have industry assets of high value like gas turbines or wind turbines and we have predictive maintenance, so you can increase the efficiency and profitability of the asset."
“For security we are using drones and image processing to inspect the high pressure network to avoid damages that can be very harmful.”
Like RBS, business card website Moo.com uses artificial intelligence software to improve customer interactions.
Director of customer services, Dan Moross, says: ”We have adopted a fairly basic AI and ML tool called AnswerDash.
"This is a contextual self service support tool which uses our data to give contextual support in that online journey. This gave us not just savings with the call centre but additional revenue with customer conversion.”
12. Government of Catalonia
Jordi Escale, CIO of the Government of Catalonia, says that while AI plans are at currently in their early stages - and is consulting with IBM on potential projects - there are a number of ways the technology can be used for public sector firms.
"We start thinking about the impact in the services in the government like traffic control and autonomous vehicles,” he says.
This includes real-time facial image recognition and number plate recognition for the police. "Then there is health, supporting the doctor for knowledge by tapping all of this unstructured data,” he adds.
13. Las Vegas Sands
Jonathan (Jon) Catling, director global data architecture at Las Vegas Sands Corporation, says the business - which owns hotels such as the Venetian and Palazzo - has designed a virtual assistant chatbot for guests.
“We came up with AI concierge," he says. "We started with a chatbot as a means of communication that they feel comfortable with.
"We don’t want to send an SMS or an email but 'chat' [with our guests]. So any time, anywhere you can take one step into the customer's comfort zone."
He adds that guests can engage with the chatbot through their Facebook account whenever they want. "We want you to get to the point where you can order room service faster. Not ringing down but using a tablet in the room, using your smartphone, anywhere.
"The conversation is the key to the customer, they’re not interested in the technology but the chat.”
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