As companies continue their journey to digital transformation, no industry remains unaffected by the rise of AI. Here in this post, we will outline the most powerful artificial intelligence examples across 10 industry sectors.
Technological advancement, competitive advantage, and immediate financial returns are the strongest drivers responsible for the rise in AI investments.
Deloitte carried out a survey in the 3rd quarter of 2018 spanning 10 Industries.
According to the survey, 82% of companies reported an average return of 17% as a direct result of their investment in cognitive technologies.
It also reports that 37% of those respondents said their companies invested in excess of $5M in 2018.
Below is a comprehensive list of 30 most recent artificial intelligence examples, spread across 10 different industry sectors.
30 Artificial Intelligence Examples
The oil and gas giant, BP is a great example of industry’s increasing interest to harness the power of AI.
They have just invested $5M in series A round of Belmont Technology, an artificial intelligence startup.
Their objective is to unlock critical data, to create an overview of surface assets and identify new connections to improve BP’s oversight of its projects.
Going forward, they plan to use this technology for their primary interest; Upstream Work, meaning the exploration for natural gas fields as well as its recovery, and production.
An energy industry insider, Irina Slav of Divergente LLC, says that 2019 is marked to be the year artificial intelligence will be used by gas & oil companies for the first time in the field.
They will use artificial intelligence to gather existing wells’ data and to see how its yield will change over time.
AI will also be used as a Digital Oil Analyst according to Florian Thaler, co-founder, and chief executive at OilX, an oil-tech startup.
Thaler says that “the current exponential growth in oil data from sensors and satellites is unprecedented and is not showing signs of slowing down”.
Growth of Data driving growth of AI
One of the biggest challenges faced by Minestar, a Canadian energy company, is the amount of time it takes to put together bid packages for new projects.
A new package can take a team of four people, 6 to 8 months, then another 8 to 9 months to review submitted bids.
In 2018 Minestar engaged IBM Watson Artificial Intelligence Supercomputer to carry out the same work, Watson only needed 72 hours.
This year, a number of Canadian Energy Companies plan to use Watson to solve issues such as reduction of drilling costs, improve forecasting methods, reduce energy consumption and improve employee safety.
All major gas and oil giants are engaged in some form of AI in their operations and are seeking advanced methods of reducing the overall impact of production and driving efficiencies.
Some of the most innovative artificial intelligence examples are by Total, ExxonMobil, and Royal Dutch Shell.
Using AI and Drones to Monitor Cables and Pylons
Energy companies best demonstrate artificial intelligence examples in the use of drones.
National Grid, UK’s second largest electricity and natural gas delivery company, uses AI and drones to monitor and help maintain over 11,000 km’s of cables and pylons transmitting electricity to properties across the country.
The drones use onboard cameras to capture images (including infrared) and video to assess the condition of steel for signs of corrosion and wear.
They also inspect cables and pylons for faults and damaged conductors.
Once this work is carried out, AI analyses the data to establish whether there’s a requirement to replace parts or carry out any maintenance work.
The best artificial intelligence examples are found in the finance sector, starting with J.P. Morgan Chase, who in June 2018 piloted the world’s first A.I. Powered Virtual Assistant for corporate payments.
The Assistant was primarily developed to help clients navigate their online cash management portals.
Rather than manually searching through online options, all they have to do is ask the Virtual Assistant questions such as the balance of their accounts.
The more a client uses the Assistant, the more it learns; it will eventually make suggestions according to client’s preferences and past behaviours.
Furthermore, J P Morgan has been heavily investing in artificial intelligence with a high-profile hiring of ex-Google employee Apoorv Saxena joining as its new head of AI and machine learning services.
Global transactions leader, Paypal, has made 4 acquisitions in 2018, two of which were AI companies; Jetlore and Simility.
Launched in 2014, Jetlore develops prediction technology, which analyses consumer behaviour.
It first establishes what constitutes natural account activity, then uses that model to detect abnormalities.
This process exposes suspicious accounts, which allows the AI to filter out and prevent fraud such as account hacking.
Simility deals with identifying and stopping fraudulent wire transfers before they have a chance to be processed.
Both acquisitions provide Paypal’s customers with a safer, more personalised service, and prevent fraud on every level.
Deutsche Bank’s Algorithmic Trading Platform
Deutsche Bank’s upgraded its proprietary equities trading platform named Autobahn 2.0.
The (self-learning) algorithm equipped with momentum detection set a new benchmark in the sector when it was rolled out by the bank in 2018.
The (self-learning) algorithm is equipped with momentum detection.
Autobahn 2.0 predicts price and volume with greater accuracy and provides the best results when it executes client orders on the equities trading platform.
It’s one of the most functionally rich solutions available on the market today.
AI Claims Handling
Health insurance is big business and Allianz Insurance has partnered with Keoghs, an AI software company.
Last year Allianz launched what they say is a first, end-to-end “truly” automated system to process Stage 3 injury claims through the Ministry of Justice.
The new systems allow users to process claims with literally a push of a button, significantly reducing previously required time and effort.
The financial services industry incorporate a whole host of artificial intelligence examples into their operations from identifying fraud, algorithmic trading, portfolio management, claims handling and anti money laundering (AML) and loan / insurance underwriting
2018 has started to see a number of courts around the globe approving the use of facial recognition software to track and find missing persons.
One of the best real-life cases in the use of AI was recently reported in India, where Police traced a staggering 3,000 children in just 4 days using facial recognition software.
In 2019, governments around the world are beginning to develop laws in order to regulate this technology.
Regulation is a crucial next step as more government agencies as well as various businesses such as shopping malls incorporate facial recognition software into their strategies.
Public Safety and Public Cameras
Public safety is another example, where cities and other authorities are looking to AI driven recognition software.
They want to use it to combat security issues, particularly in ‘danger zones’ or during high-profile events.
Public cameras and monitoring have been around for a long time, but seeing a camera does not necessarily make us feel any safer.
This may change with the integration of artificial intelligence into these systems.
Along with faces, advanced recognition software monitors assets and identifies objects such as unattended bags at airports or other public spaces.
Burning or cutting off fingers – AI will catch you
Burning or cutting off fingerprints, which has been a growing trend among “career criminals”, will no longer allow these individuals to escape justice.
The FBI has engaged tech companies across the United States to develop a next-generation AI-powered system for their enormous biometric database.
This new system won’t be fooled by obscured or missing fingerprints as it will compensate for unidentified surfaces by classifying them as yet un-readable prints.
The system will also keep up to date with any new changes to the fingertips by learning in real-time.
Fighting Welfare Fraud with AI
With annual losses of over £2.1billion, the UK government is at the forefront of using artificial intelligence to combat pension fraud.
They are using AI to stop criminals responsible for these tremendous losses which have dramatically increased over the last few years.
This is one of the very best artificial intelligence examples as it deals with large-scale corruption and massive amounts of taxpayers money.
It achieves that by scanning claims to discover signs of fraud such as same phone numbers or similar styles of handwriting.
Once the AI flags a claim for possible fraud, a human takes over for further investigation.
Using AI for Drug Discovery
There is no shortage of artificial intelligence examples in the healthcare sector, they extend to every corner of this industry.
It normally takes many years to discover new drugs using traditional methods, Johnson & Johnson has found a way to make this process 250 times faster by using artificial intelligence.
Before tests can begin, the AI will comb through enormous amounts of data to find chemical compounds most likely to effectively treat the targeted disease.
But drug development is not the only area where Johnson & Johnson plans to utilise the power of artificial intelligence.
In a recent interview, Georgia Papathomas, the Head of Data Sciences at the company said,
“I am trying to set up data scientists for all of J&J, from strategy, to process, and governance as well as trading data as an asset, and apply it in every single function across J&J, from finance to HR”.
The area of prosthetics is getting a lot of international attention and AI funding.
One of the finest examples of this can be observed at Newcastle University, where engineers have developed a low-cost bionic hand fitted with a tiny camera.
The artificial intelligence responds to the visual input from the camera with a sequence of relevant movements.
The AI adjusts these movements depending on the situation, for example; it recognises the objects in front of it and modifies the strength of the grip accordingly.
Your next doctor’s visit could be with Doctor A.I. developed by Babylon Health, the company claims that artificial intelligence can diagnose a person just as well, if not better than a medical professional.
This software has met with a lot of controversy from medical practitioners, who say that “No algorithm or app will be able to do what a GP does”.
But Babylon Health is fighting to prove otherwise; unveiling the results of Clinical Exam taken by the AI, at a recent industry event attended by many doctors, who themselves had to take that same exam as part of the certification process.
The only difference being that an average result (over the last 5 years) for humans is 72%, Doctor A.I. scored 82%.
Foxconn is one of the largest manufacturers in the world, they produce the majority of Apple’s products.
The company has recently started the process of hiring some of the world’s best AI professionals.
As part of this move, Foxconn has committed $342 million over a 5 year period to be spent on AI Research & Development.
One of their main objectives is to embed data collecting (AI powered) sensors throughout their manufacturing plant and equipment.
Captured data will identify maintenance issues and improve manufacturing processes.
Foxconn says their motive behind this investment is to offer advanced manufacturing services to existing and future clients.
Toyota manufacturing plant in Sweden uses AI-driven trolleys filled with baskets full of tools, parts, and components.
The trolleys move around the factory very slowly, knowing exactly where they are, what they are carrying, and which workstation requires the delivery of goods.
The onboard AI allows them to navigate around the factory and avoid obstacles and collisions.
Soon, technology will expand to generate reports to improve inventory management and production efficiencies.
It seems manufacturers no longer have to wait for something to break or to manually assess the condition of their equipment, in order to know it’s time for maintenance.
‘Predictive maintenance’ with Artificial Intelligence
Predictive maintenance is the latest technology featured in our artificial intelligence examples.
Mitsubishi Electric is utilising the power of ‘predictive maintenance’ technology-driven by IBM’s Watson artificial intelligence.
This tech allows them to correctly ascertain the health of their assets by gathering maintenance data, based on actual use and wear.
In one example, the servo controllers and frequency inverters exchange both vibration and friction data with the software in real-time.
The company has also begun to develop mobile apps for closer monitoring of equipment and production processes.
Generative Design, Humans and AI working Together
Traditionally the work of a designer (in any field) involves labouring over a single design over an extended period of time, with limited variances to present to their clients.
Other artificial intelligence examples on how manufacturing is embracing AI is in Generative Design a process where humans and AI work together to simulate and produce thousands of design variables for one or many products, after inputting design and cost restraints.
Siemens is one such company at attempting to use this technology to dramatically reduce the time to create new designs for their products.
But it’s not just Siemens, companies of all kinds are lining up to use generative design to create new products, even NASA has now joined the ranks in a bid to improve designs for products and equipment used in space exploration.
Most people know that Netflix uses machine learning to personalise viewing suggestions for their users.
According to the company the AI bases these suggestions on previous viewing choices as well as other data, which Netflix wants to keep a secret.
This year they are engaging artificial intelligence to identify users, who share their accounts/passwords with others in order to avoid paying subscription fees.
Research shows that a staggering 26% of millennials are engaging in this practice, which deprives streaming companies of big profits.
NBC has partnered with Vilynx, who develop AI focused solely on media.
It doesn’t just analyse data, but it makes recommendations to enhance the success of e.g. marketing videos.
This AI is very specific and covers all relevant data such as; video content, shoot’s location, main character, background music, and the list goes on.
There is nothing more annoying than trying to catch up on recent news, and then having to go through the daunting task of scrolling through articles we have no interest in.
To start, users must select interest options, but the more they read, the better the AI learns and serves up improved news suggestions.
The professional services sector showcases some of the greatest artificial intelligence examples, most of which revolve around saving time and driving efficiency.
Traditionally during when companies file for tax, the work of an accountant involves many hours labouring over repetitive tasks.
Even then, they might not always be able to extract full value for their clients in R&D tax reliefs as well as other tax write-offs.
KPMG, one of the largest top-tier professional service firm in the world plans to change this by teaming up with IBM.
They already have a KPMG Ignite, a portfolio of AI blocks, which allows their clients to improve and automate decisions and business processes.
The partnership with IBM will allow them to take it to another level and extract full value at tax time for KPMG’s clients, made up of world’s largest and most prestige corporations.
The largest legal firm in the world, Baker McKenzie has partnered with LitiGate to automate legal research as well as other processes required to successfully run a law practice.
A recent study designed by experts and law professors from Duke & UCLA, had the country’s top corporate lawyers go head-to-head with an AI called LawGeex.
Their job was to spot flaws in a non-disclosure agreement.
The AI came out on top with 94% accuracy vs. the professionals with 85%.
It also completed the exercise in just 26 seconds, comparing to the average of 92 minutes needed by the lawyers.
Retail & Consumer Services
Bypassing Checkouts with AI
Here are a couple of artificial intelligence examples used in the retail sector, known for incorporating technology into every process.
Wouldn’t it be great to go for a quick run to the shop on a busy night and not have to wait in line?
We might be able to do that sooner than we thought with Walmart, who are working hard in an effort to bypass the traditional checkout altogether.
Based on a pilot successfully tested in an Amazon store, Walmart wants to achieve this with the use of computer vision, sensors spread throughout the store and machine learning technology.
Pepper the AI Robot your New Retail Assistant
If you’re looking for a new salesperson, someone who could really drive sales and engage with your customers, then you might want to meet Pepper.
Developed by Softbank Telecom, Pepper is a greeting robot with a cute expression and height of a child.
It follows your gaze for reasons other than to maintain eye contact or to get your attention.
The artificial intelligence built into the robot “reads” our eyes and facial expressions to pick up and respond to human emotions.
When Pepper was tested by couple of stores in Palo Alto and Santa Monica, it increased foot traffic by up to 70%, and sales by 200%.
The company has since developed a new robot, Whiz, which was created for more practical purposes – cleaning floors for various businesses.
There are over 25,000 Softbank robots spread across the globe, but the company plans for further production as the demand in the market has increased for this type of technology.
There aren’t many artificial intelligence examples within the skincare sector, but there always has to be a first.
The AI stylist
L’oreal made an unprecedented move within the sector when it acquired augmented reality startup, Modiface last year.
Shortly after, they launched ‘Style my Hair’ app, which lets users “try” on a variety of hairstyles.
Next, they partnered with Facebook, to allow those users to share AR images sourced from the app, with their friends and family.
The AI processes this multitude of data to analyse skin textures, wrinkles, and face shapes.
The findings help L’oreal create future products and manage inventory volumes.
The telecom sector is afloat with artificial intelligence examples, most of which focus on data collection and analyses, let’s take a look at some examples;
The amount of data flowing through AT&T’s (global leader in telecommunication services) network, has increased by 360,000% since 2007.
They have engaged the use of artificial intelligence to make sense of all this information.
The AI processes and analyses the data to provide insights and actionable information to relevant employees, at the appropriate time, which enables them to make informed decisions and allows them to provide better customer service.
Telecom companies find it very hard to maintain high levels of service by relying on customer feedback alone, especially that in a lot of cases people don’t always report network problems.
Verizon has come up with a solution to solve the problem with machine learning ML, which use predictive analytic algorithms to monitor 3G of data (per second), covering millions of network interfaces.
Verizon claims that they were able to use this technology to identify and prevent a large number of negative “customer impacting” events.
There is a lot of excitement, and not just within the telecom circles, about the next-gen 5G technology and its potential (especially in connection with AI and Internet of Things – IoT), Verizon is one of the companies actually building it.
Sometimes artificial intelligence example can be found in non-profit initiatives, working with telecom giants to end world hunger.
Project Healthy Children teamed up with Vodafone to engage AI and IoT solutions, to gather real-time insights from more than 3000 small mills, which provide flour to millions of people in Africa.
Sensors embedded in mills by Vodafone gather and analyse data to improve processes and adjust proportions of various minerals and vitamins added to the flour, to enhance its nutritional value.
The transport industry is littered with artificial intelligence examples from self-driving cars with the development of level-4 and level-5 autonomous vehicles to self-driving ships.
Stories about the “future” are filled with stories about flying cars; they might not fly this year, but they can certainly drive themselves.
Autonomous driving is at the forefront of development at Tesla, an electric car manufacturer.
Headed by Elon Musk, the company continually improves this technology for even greater safety and reliability.
They hope to present the world with a truly driverless car in the not too distant future.
If self-driving cars are not enough to impress you, then how about autonomous ships.
Rolls-Royce has partnered with Intel to create “self-driving” ships, which have replaced a crew of 20, they use AI to identify and navigate around any potential danger zones.
Rolls-Royce also plans to start using AI to track the performance of the ship’s engine as well as help with loading/unloading of its cargo.
To finish this list of artificial intelligence examples, no mention of AI would not include one of the largest technology companies in the world, Amazon.
They incorporate a plethora of artificial intelligence examples in their processes, from the moment we start looking for products, to placing an order, picking and packing, and finally – the delivery.
Deliveries were once outsourced by Amazon, but with over 5 billion packages shipped on a yearly basis, Amazon has started to use their own trucks in 2018 to send items to customers.
The AI takes into account variables such as product availability, location, weather, traffic, and season in order to select the appropriate truck, warehouse, and route.
Our future looks bright, with so much research, innovation, and new development in the area of machine learning and deep learning often referred to collectively as simply AI.
Research shows that almost every corporation and educational institution in the world is either investing in or researching ways to take advantage of this technology.
TechRadar forecasts more than $200B will be invested into AI by 2025.
Artificial intelligence examples are visible in every industry sector, and regardless of what the future may bring, AI is here to stay and continue to spread into every aspect of our personal and professional lives