Artificial intelligence (AI) is starting to reshape many industries, from manufacturing to retail, from the stock market to entertainment. But new artificial technologies have already been implemented in quite unexpected areas. According to the Financial Times, many companies from the energy sector are using drones to cut their costs. Such giants as the Centrica and Royal Dutch Shell are using them to check their equipment. But this example is only a drop in a bucket how new technologies may be utilized by companies that want to improve their operation. Among others – natural language generation, machine learning platforms, deep learning platforms, robotic process automation, virtual assistants or chatbots, natural language processing and text analytics.
According to the report “Artificial intelligence for business,” almost 38% of enterprises today use AI technologies and 80% of companies that do not use it directly, still, use technologies that rely on artificial intelligence. The same research says that 45% of businesses agree that AI/machine learning/deep-learning have the influence on their work and 24% of enterprises believe that it will have an impact in the next one or three years.
So how exactly different types of businesses are using AI and what influence does it have on their operation?
The finance sector is often mentioned as one of the leaders in the context of the adoption of artificial intelligence. 32% of financial services executives said that they are using AI technologies in business activities, according to the survey made by Narrative Science in conjunction with the National Business Research Institute. In finance, AI is used in several ways starting from predictive analytics to security systems or from personal finance to consumer services.
Let’s look at analytic part first. AI technologies help to manage structured and unstructured data, making right decisions and getting more profit. Switzerland-based start-up Veezoo helps finance companies to research their finance data and find the best data visualization and thus to “make complex information easy to understand.” Finance firms use machine learning not only to enhance their investment strategies but also to check whether the regulatory requirements are met and flag the existing problems immediately. In other words, they use AI to improve their risk management.
Many banks, Barclays in particular, have already incorporated chatbots or AI assistants into their day-to-day operation. Today bank customers can ask AI assistants to make payments, to check their account balance or to find the nearby ATM. But virtual assistants can do much more than simple routine tasks. AI assistant named Sara from Commercial Bank of Dubai that is available 24/7 can easily give some useful advice on investing.
AI is also revolutionizing wealth management and trading. San Francisco-based startup Digit can take care of customers’ savings with the help of algorithms. Big finance companies also use robo-advisors, that provide automated advice based on the analysis of the particular portfolio. According to Bloomberg news, such giants of investment banking as Goldman Sachs, Bank of America, Citigroup and JPMorgan are planning either to purchase startups aimed to create a robo-advisor or to develop their own solutions.
But bots and virtual assistants are not the prerogatives of the finance industry. AI bots or personal health assistants are becoming more and more popular in the healthcare too. According to the report of CBinsights, more than 90 companies use machine learning algorithms and predictive analytics to provide virtual assistance to patients, to reduce drugs development time or to diagnose diseases. When we talk about healthcare assistance, we should mention Molly, a virtual Nurse created by the startup sense.ly. Molly is not only able to provide simple administrative needs to patients or chat with them in different languages but also gives personalized care such as follow-ups, analyzing their condition and provide patients with instructions on how to improve their health.
Improving diagnostics and treatment with the help of machine learning becomes more and more popular. CBI insights found at least 22 companies aimed at developing new tools for imaging and diagnostics. An American startup KenSci intelligence plans to solve the problem of missed diagnosis using AI. Pathway Genomics is working on a blood test aimed to figure out if it is possible to detect or predict particular cancers. Giants like Google or Samsung invest billions of dollars in creating biometric sensors enabling to extend lifespans and prevent serious diseases. The GE Healthcare and UC San Francisco think that they can develop the whole library of deep learning algorithms to improve diagnosis, find effective treatment plan, clinical workflows and shorten time to recovery.
Real estate is one more industry that welcomes AI with open arms. Today prospective property owners usually start with search engines that can be a good example of artificial intelligence. All the requirements starting with price or place to more complex such as return on investment can be displayed to a buyer or seller in a convenient form.
Aside from search engines, many specific tools and apps can help ease the process of making a deal. The project Citybldr uses AI, notably the algorithm with over 180 factors to determine «the best use» of property. It evaluates not just the property itself, but the potential value of the land the property stands on.
The AVM (Automated Valuation Model) from Onboard Informatics uses regression analysis and estimates the market values of the real estate objects. Boomtown helps to match potential buyers with properties. Realstir gives a chance to compare areas, and Address Report checks the history of properties, promising to reveal «the unbiased truth about any apartment».
Chatbots are also very helpful in real estate. They answer the questions of the clients via messaging apps, collect pieces of information, and fill different forms for the potential buyers or sellers. What is also essential bots are cutting the human factor from the real estate workflow – after communicating with bots clients do not feel obliged to take an offer, so the decision-making process becomes less stressed thus more comfortable.
Many aspects of the real estate activities have become much more convenient not only for particular clients but big businesses. International companies beyond any doubts benefit from deep learning technology that helps to extract and structure huge amounts of data and translate the useful information from international contracts to any languages. Deep learning technologies also make the reporting process for real estate companies with offices all over the world much easier.
With a rapidly growing amount of challenges in the agricultural sector, this industry is also turning to AI to find possible solutions in new technologies. One of the biggest challenges for the agriculture is to maximize food resources to feed 9 billion people in 2050 (forecast). Some companies have already started to work in this direction. Last year Swiss startup Gamaya raised enough funding to use drones and AI to improve farming.
The idea is to use drones with hyperspectral cameras to detect all changes that can’t be seen by human eye – all changes in water, pests, crop yields – and then to analyze these pictures with AI algorithms to alert farmers about possible problems. Gamaya is not the only project aimed to help grow crops more efficiently. There is whole “industry” based on AI called precision agriculture.
It implies collecting and processing data, placing special sensors in the field, analyzing images taken by drones and even building models and simulations that can predict conditions thus helping farmers to make smarter decisions regarding planting or harvesting.
AI already includes the variety of useful tools and technologies that are dramatically remaking the face of many industries. And its usage will apparently only increase in the future. The tech giants such as IBM, Apple, Google, and Intel that are fighting for AI startups and many other companies that create their AI technologies reinforces this view. Deals with the AI startups grew almost five times in the last five years – to 698 in 2016.
Moreover, over 30 companies using AI algorithms have been acquired only in the first quarter of 2017. Also According to IDC, the AI market will rise from 8 billion dollars in 2016 to more than 47 billion dollars in 2020. Nobody knows exactly where will the next breakthrough of AI take place, but there is no doubt that artificial technologies will continue to reshape different industries.
As Coursera’s co-founder and computer scientist Andrew Ng said, artificial intelligence will become “the new electricity.” He added that he couldn’t name an industry ”that AI will not transform in the next several years.” Can you?