50 AI Examples from the World's biggest companies

Written by Luke Renner

Manceps has gathered 50 Artificial Intelligence and Machine Learning examples from the first 50 companies in the Fortune 500.
 
We sought to answer a few questions:

• How are the world's biggest companies deploying artificial intelligence today?
• What AI examples are out there?
• What lessons can stakeholders everywhere apply to their own organizations?

Explore AI Examples from All of These Companies

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AI Super Power
Optical Character Recognition
Uses
Brick-and-mortar Stores
Corporate Campuses
Factory Floors
Emergency Rooms
Airports
Walmart is deploying machine learning and image processing to all of its locations to make it easier for employees to keep their stores running smoothly. Using thousands of video cameras, weighted sensors on shelves, and other technologies, Walmart’s in-store tech can tell employees when certain products are running low or produce is starting to go bad.
 
In one example, image processing systems could identify bananas that had started to brown, eliminating the need for employees to manually inspect fruit. Similarly, traffic flow systems could anticipate downtimes, giving employees the chance to restock shelves or gather up shopping carts from the parking lot.

Key Takeaways

The lesson here is that visual data and image processing can improve the efficiency of nearly all the physical spaces in which organizations operate. By training an extra set of AI eyes onto all sorts of workspaces, artificial intelligence can automate inspections, catching things that humans may have missed and/or leaving them free for other tasks.

Ask Yourself: Does my business operate in any physical spaces that could benefit from an extra pair of eyes?

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Discussion Questions for AI Readiness
AI Super Power
Automated Operations
Uses
Sourcing job candidates
Conducting research
22Artboard 2
Prospecting for business opportunities
Diagnosing Patients
Designing products
ExxonMobil deployed an AI-powered algorithm to make it easier for its deepwater prospecting teams to drill at the bottom of the sea. Trained on a dataset that leveraged drilling specifications of previous jobs as well as survey information from the ocean floor, this Drilling Advisory System empowered their team to “automatically optimize drilling parameters”. The algorithm led to improved drilling and safety performance, and lower costs.

Key Takeaways

Like ExxonMobil and their ongoing effort to drill for oil, repetition within your organization is a good indicator that you might be able to deploy an AI system. In this case, ExxonMobil could transform its experience with off-shore prospecting into an algorithm that could automatically apply that experience to future jobs.

Ask Yourself: Is repetition a major part of my business?

AI Super Power
Optical Character Recognition
Uses
Fashion
Retail
Marketing
Artboard 1
Customer Service
Media & Content Creation
Apple is infusing as much AI into their products and operations as possible. In 2019, the world's largest technology firm made several key artificial intelligence acquisitions, which served the following purposes:
 
1. Bring greater personalization to web search and Siri results;
2. Shore up their competitive disadvantage in the self-driving car space;
3. Make images “shoppable” by allowing users to search using photos, rather than keywords;
4. Improve iPhone photography with AI-powered photo enhancement.
 
Siri, of course, is another example of how Apple runs on AI. The voice-powered assistant is designed for continual, at-the-edge improvement, which means it uses customer communications to further train itself without having to transmit those private communications to Apple servers.

Key Takeaways

Just like the digital transformation of the ’80s and ’90s that led to a computer on every desk in America, Artificial Intelligence represents a massive opportunity for transformation within your business. AI, combined with machine learning, gives organizations an unprecedented ability to personalize the products, services, and search results of each of their customers. Personalization is one of the drivers of the digital economy. Today, consumers have come to expect that their experiences will be customized and individually curated.

Ask Yourself: Would my customers benefit from increased customization and personalization?

AI Super Power
Data-driven Decisions
Uses
Mortgage Lending
Insurance Underwriting
Credit Card Applications
College Admissions
Background Checks
GUARD, a Berkshire Hathaway insurance subsidiary, has partnered with an AI data platform to optimize the underwriting process for its small and medium business segment. The goal of the partnership is to spare underwriters from having to spend so much time finding, gathering, and organizing client data. By structuring the data in a more efficient and actionable way, the organization hopes to dramatically reduce the time it takes from submission to quote. According to the announcement, “with only a business name and an address as inputs, insurers can obtain the information necessary to evaluate the ‘right’ risks and profitably grow and maintain their portfolio.”

Key Takeaways

Regardless of whether your organization has its own datasets or needs to acquire it from other sources, this example illustrates the fact that artificial intelligence puts customer data to work. Any time your organization uses data to make decisions about the services it offers its customers, artificial intelligence could be used to bring greater speed, accuracy, and fairness to the process.

Ask Yourself: Does my organization collect a lot of data to make decisions?

AI Super Power
AI-Centered Corporate Strategy
Uses
Supply Chain Management
Artboard 24
Customer Recommendations
Logistics
When it comes to making the best use of artificial intelligence, there’s an argument to be made that Amazon sits at the front of the pack. The company has employed AI across its entire operation with its leaders famously required to explain how they intend to deploy AI in their annual business plans. 

 

In one of its first forays into AI, Amazon built a recommendation engine to make it easier for customers to surface more of the things they might like to buy. Today, their entire distribution infrastructure runs on AI. Combined with robotics and other innovations, Amazon’s warehouses are some of the most advanced artificial intelligence incubators on earth.

 

How else could they offer one-hour delivery to an expanding slate of markets?

Key Takeaways

Speaking at the inaugural re:Mars event, Amazon Go VP Dilip Kumar told the crowd that "If you start with a genuine customer problem, you can use the power of machine learning... to build a stellar customer experience." This philosophy drives Amazon’s AI strategy.
 
Similarly, artificial intelligence should inspire all organizations to take a look at their (and their customers’) pain points to see if greater analytics, efficiencies, and/or automations could solve some of their toughest business challenges.

Ask Yourself: Could greater analytics, efficiencies, or automations make my customer's lives easier?

AI Super Power
Natural Language Processing
Uses
Law
Medicine
Journalism
ШКОЛА - без глазок - БЕЗ ОБВОДОК на артбордах
Liberal Arts
Artboard 1
Customer Service
Like Amazon, the massive healthcare organization is deploying natural language processing across large swaths of its business. One of the biggest responsibilities of the organization is to authorize (or deny) payments for doctor-recommended medical procedures. This process of getting pre-approval can be costly, which is why Unitedhealth Group is using machine learning to streamline and automate as much of this process as possible.
 
Unitedhealth has also turned to natural language processing to sort the more than one million calls they get to their customer service line each day. Their goal is to deliver a better customer experience to all of their 115 million customers.

Key Takeaways

Natural language processing gives Machine Learning algorithms the powerful ability to organize, summarize, and understand language. Whether words are handwritten, scanned, scraped from a PDF, downloaded from a database, or spoken into a phone, these systems can glean not only the words being used but also their deep intrinsic meaning.
 
If your organization traffics in files, books, records, customer records, etc., natural language processing can streamline and automate almost everything you can think to do with that content.

Ask Yourself: Is reading a major part of my organization's daily activities?

AI Super Power
Artboard 2
Smart Contracts
Uses
Digital Identity
Finance
Real Estate
Internet of Things
Healthcare
Like Unitedhealth Group, McKesson is also in the healthcare industry; however, one of the ways the organization is deploying artificial intelligence is less about managing their patients and more about managing their business. For several years, McKesson has maintained a partnership with a global professional services firm focused on bringing about digital transformation. According to Emerj, this partnership was designed to bring smart contracts and Artificial Intelligence to several business processes, including:
 
• Customer payments, such as hospital stays and prescription drugs;
• Patient information gathering, storage, and processing;
• Automated contract management;
• Vendor payments and reimbursements.

 

 

Key Takeaways

Smart Contracts bring a layer of automation to how businesses operate and respond to market conditions. Adding artificial intelligence to these types of contracts opens the door to all sorts of novel business practices. We’re talking factories that automatically shift their output based on supply-chain fluctuations; prices that automatically shift based on demand; vendor payments that go out the instant certain conditions are met.
 
Smart contracts are particularly useful to your accountants, promising to automate and simplify much of the work they do over and over again.

Ask Yourself: How would your business change if you could automatically execute contracts?

AI Super Power
diagnose-heartbeat-heart-rate-pulse-medical-healthcare
Automated Diagnostics
Uses
Transportation
Machinery
logistics
Logistics
Telecommunications
Medicine
2 years ago, CVS Health entered into an agreement with AI startup Buoy Health to deliver AI-powered customizations and healthcare recommendations to their more than 1,100 Minuteclinics across the US. Delivered via in-store kiosk, the CVS system automates the patient intake process by asking customers a series of questions about their current symptoms and previous health history. AI then uses these answers to direct patients to either an on-site healthcare professional, a medical consultation via webcam, or an approved over-the-counter solution.

Key Takeaways

While Artificial Intelligence has been driving innovation across both medical diagnostics and customer service, respectively, these AI-powered Minuteclinics represent one of the first attempts to integrate these capabilities and roll them out at scale.
 
Whether providing technical support or processing returns, the work of customer service is to diagnose a problem and deliver a solution. CVS’s foray into automating this process is a good reminder that other organizations should consider doing the same. Regardless of whether your team spends its time diagnosing a mechanical issue, a technical problem, or a delivery concern, artificial intelligence can surface solutions more quickly and accurately.

Ask Yourself: Does your organization leverage diagnostics to identify and solve problems?

AI Super Power
Image Recognition
Uses
Passports
baggage rummage, airport security, xray, inspection_1
Xrays
Engine Parts
Pumpkin Patches
Archival Footage
AT&T is one of those organizations that have tried to bring artificial intelligence to almost every aspect of their business. Unlike the majority of the Fortune 100 organizations on this list, AT&T is more than willing to tout how artificial intelligence is driving their business. The organization owns dozens of media companies including HBO, AOL Time Warner, and ESPN, which means many of their AI plays are related to cataloging their video library and serving relevant ads.

 

On their dedicated Data Science and AI page, they outline several initiatives including:

 

• Video processing and image recognition to generate highly detailed descriptions of video content, “to power enhanced content experiences and more relevant advertising.”
• Natural language processing to improve the accuracy of genre and category labels across their video library.
• Predictive algorithms to better match advertisers with their ideal customers.
• Geospatial data analysis
• Machine learning for cybersecurity.

Key Takeaways

AT&T understands the almost limitless, seemingly magical capabilities that artificial intelligence can bring to their business. By thinking creatively about opportunities for automation, AT&T can deliver a better product for both its customers and its advertisers.
Their work with image recognition is particularly notable. Image Recognition is an extremely powerful tool that works on all sorts of visual data such as images, video, drone footage, or LIDAR surveys. Beyond the media examples above, training machines to perceive the visual world has all sorts of use cases that can be customized to the individual needs of your organization.
 
A good place to start is to make a list of all the things people in your organization regularly inspect. In most cases, an AI system can be trained to complete those inspections automatically.

Ask Yourself: What are things your organization regularly inspects?

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AI Super Power
Automated Data Processing
Uses
Finance
Insurance
Real Estate
Medicine
Amerisourcebergen, the world’s most profitable pharmaceutical company, is bringing artificial intelligence to its benefit verification process. In 2018, the pharmaceutical conglomerate announced that one of their subsidiaries had launched an AI-powered electronic benefit verification solution that would leverage a dataset of “health coverage and payer data collected from millions of manual verifications” to evaluate each incoming benefit verification. Today, their system can predict outcomes and process data in real-time with only a tiny fraction getting forwarded to a human clinician for further investigation.

Key Takeaways

AmerisourceBergen joins virtually every other major healthcare company in its quest to bring greater automation to the benefit verification process. The ongoing challenge of healthcare conglomerates is to balance expensive treatment options with their need to drive profitability. To achieve this balance, treatment plans must be efficacious and carefully considered.
 
More broadly, the thrust of their effort here is to transform a crush of data into action. Regardless of whether your information overload comes in the form of healthcare data or multinational financial information, artificial intelligence can bring order to chaos.

Ask Yourself: Is your organization drowning in data?

AI Super Power
Operational Optimizations
Uses
Predictive Maintenance
Surveying
Process Optimization
Data Extraction and Interpretation
In 2016, Chevron rolled out a machine learning system that could help it identify new well locations and stimulation candidates. Trained on a dataset that included the company's large collection of historical well performance data, the system has since contributed to a 30% increase in productivity.
 
At the time, the company was also rolling out a system that analyzed the performance information of thousands of pieces of equipment to bring predictive maintenance to their operation.
 
Today, Chevron is expanding its use of artificial intelligence beyond the needs of their oil-drilling operations. They recently 
announced a partnership with Microsoft in which they’ll use natural language processing to scrape information and insights from millions of drilling reports.

Key Takeaways

Chevron’s adoption of cognitive intelligence echoes a pattern we’ve seen with many of our clients. First, companies will use AI to exclusively address their most mission-critical business challenges. Then, after seeing the transformation AI has brought to their business in one area, leaders will look to deploy AI systems in other contexts.
 
If you’re bringing AI to your company for the first time, we recommend working on a project that has an immediate and measurable ROI. This brings an enthusiasm to your project that will make the transition to AI easier for your entire company.

Ask Yourself: For our first foray into AI, what is a problem we can solve that would directly affect our bottom line?

AI Super Power
Autonomous Vehicles
Uses
Transportation
Robotics
Artboard 12
Drones
Defense
Ford is at the forefront of the transportation transformation. It was one of the first companies on earth to deploy a neural net at scale and has since brought artificial intelligence to both their assembly lines and in the operation of the vehicles they sell. Ford Edge’s all-wheel-drive system, for example, uses artificial intelligence to automatically determine if all-wheel drive is needed — more quickly and accurately than a human driver. In the factory, AI can detect wrinkles on seat fabric.
 
In 2019, to better compete in the race for full vehicle autonomy, the organization made a $1b investment into Argo.ai. The company expects to roll out a Geo-fenced self-driving car fleet within 3 years.

Key Takeaways

Self-driving cars may well be artificial intelligence’s greatest challenge. While most cars operate in predictable ways and follow predictable patterns, the long tail of outliers and special cases can quickly confuse the technology, leading to severe consequences and, as we’ve already seen, death.
 
While transportation and tech companies may disagree on the systems required for full autonomy, every single organization agrees that AI will be part of the solution.
 
While researchers have yet to completely solve the self-driving car problem, anything that moves can be imbued with some level of autonomous mobility. Some examples may include trains, drones and submersibles, consumer electronics, and even luggage.

Ask Yourself: What does my organization make that could move on its own?

AI Super Power
Generative Design
Uses
Product Design
Marketing
Video Game Design
Architecture
Manufacturing
In 2018, General Motors announced that it had partnered with Autodesk to capitalize on its brand new technology: generative design. With generative design, an engineer can feed basic design parameters into the program such as materials needed, strength requirements, weight constraints, and the part’s intended method of manufacture. From there, artificial intelligence can deliver hundreds of variations of the original design. According to The Drive, General Motors has seen a 40% reduction in weight and a 20% increase in strength.

Key Takeaways

Generative design is just one of the many ways that artificial intelligence can support (or completely handle) the creative process. Already, AI can compose music, generate photo-realistic faces, and write high converting ad copy.
 
For the product designer, however, AI is an extremely robust tool. After the AI spits out hundreds of sample designs, design teams can then go and tag their favorites and repeat the process. This allows even computer-generated designs to improve generation by generation.

Ask Yourself: How could AI support your organization's creative endeavors?

AI Super Power
Geographic Datasets
Uses
Retail
Real Estate
Land Management
Agriculture
For at least a decade, Costco has used the purchasing history of its 90 million customers as inputs to help them determine new store locations. Speaking at a thought-leadership forum last year, CIO Paul Moulton explained how over time, the organization’s pattern recognition algorithms could help them define “what a successful Costco looked like in terms of who lived where, how far they would travel, and so on.” This initiative has led to millions of new customers in recent years.
 
To shore up their competitive disadvantage against the retail juggernaut, Amazon, Costco added Kenneth Denman to their board in 2017. Mr. Denman founded the company, Emotient, which used ML to measure facial expressions and predict emotions. The company was acquired by Apple in 2016.

Key Takeaways

Costco is a good example of how proprietary and publicly available datasets can be combined to drive greater sales and profitability. Amazon has taught us to expect that customer data will naturally be mined and processed. However, Costco brings additional layers to these processes such as geographical information about different neighborhoods and the people who live there.
 
If the questions you’re trying to answer require more data than your company currently has, you can likely round out your set by either launching a data collection effort or licensing an existing set.

Ask Yourself: What geographic data does your company use to make decisions?

AI Super Power
Deeply trained AI models
Uses
Natural Language Processing
Optical Character Recognition
Speech Recognition
Facial recognition
Image Processing
Last year, Google released Tensorflow, its open-sourced platform for machine learning, giving everyone access to one of the most advanced machine learning platforms ever created. More than 50 Google products have adopted the platform to put deep learning to work. 
 
Internally, Google has hundreds of employees who are working on machine intelligence. Their ultimate goal is to transform their panoply of AI-related services into a cohesive digital assistant that can proactively manage and automate your entire life.

Key Takeaways

By releasing Tensorflow to the Open Source community, Google is sending a clear message that artificial intelligence is for everyone. The platform makes available all sorts of pre-trained models and machine learning algorithms. Together, they represent millions of hours of computer training, meaning everyone has access to the most powerful AI tools in existence.
 
Today, machine learning is driven, in part, by major technology companies who train models using their massive data sets. These out-of-the-box tools are very powerful, but we can make them even more powerful by layering additional functionality, customized to your individual needs.
 
By applying pre-trained machine learning models to new datasets or information, we are able to efficiently apply complex rules and learning to a new problem, without having to reinvent the wheel.

Ask Yourself: How could your organization expand upon existing machine learning models by layering additional datasets from your niche?

AI Super Power
Data-driven Decisions
Uses
Retail
Health Care
Finance
logistics
Logistics
Engineering
Cardinal Health recently released a platform designed to support oncology professionals by making available a robust set of AI-powered capabilities including:

 
1. Tools to help deliver coordinated, comprehensive, high-quality cancer care for patients in all treatment settings;
2. Actionable and effective insights that help patients become active participants in their treatment plan;
3. Resources to help develop palliative care plans that respect the values and desires of the patient and his or her family.
 
Additionally, the platform uses machine learning to identify patients at risk of 30-day mortality who would have been missed by conventional predictive analytic approaches. According to their 
self-published case study, the deployment of this platform led to an 80% increase in patients referred to palliative care and an increase in those getting flagged for depression.

Key Takeaways

One of the things AI is really good at is synthesizing a massive amount of information and using that information to drive decisions. In effect, this is also the work of medical professionals. They order up a bunch of tests (data) to diagnose the patient’s condition and then decide on a treatment plan. Perhaps this alignment explains why the healthcare sector has been so keen to bring predictive analytics and machine learning to their efforts.
 
Health Care, however, isn’t the only industry where data is driving decisions. Really, any organization that vacuums up data can use artificial intelligence to make recommendations. Cardinal Health is using it to identify patients for palliative care but your organization may use a similar model to make investments, choose a new store location, optimize a flight path, etc.

Ask Yourself: How would easy access to data foster better decision-making?

AI Super Power
Voice Interactivity
Uses
Retail
Artboard 1
Customer Service
Smart Home/Office
Internet of Things
Last summer, Walgreens announced that it was rolling out Theatro, a voice-based assistant to all of its nearly 10,000 stores. The smart speaker will bring Alexa-like natural language processing to a retail context, making it easier for employees to get answers to common questions, serve customers with less distraction, and work with their coworkers more expediently.
 
Theatro is small potatoes compared to the blockbuster multi-year partnership they recently announced with Microsoft, the goal of which is to develop “new health care delivery models, technology and retail innovations to advance and improve the future of healthcare.” This is likely a defensive move against both Jeff Bezos’s foray into Healthcare and CVS’s deployment of AI in their MinuteClinics.

Key Takeaways

One of the challenges with any emerging technology is a failure of imagination. By imagining Alexa in a different context, the company behind Theatro developed a solution that will serve tens of thousands of Walgreens employees.

Ask Yourself: Would your customers enjoy accessing your services using their voice?

AI Super Power
tuning, equalizer, Customize, user, profile, Account, Monitor
Customer Personalization
Uses
Retail
Health Care
Finance
Marketing
Entertainment
In 2018, JP Morgan Chase tapped Apoorv Saxena as its global head of AI and Machine learning services. Saxena previously led product management for cloud-based artificial intelligence solutions at Google. 
 
Since then, Chase has made headlines for its novel use of AI throughout its business. In the summer of 2019, the company signed a five-year contract with AI ad copywriters, Persado, after a pilot project revealed a 5x increase in click-throughs on AI-generated ads. By December, the company was touting its AI capabilities to process expense reports and expedite employee reimbursements.
 
Perhaps the most famous way that artificial intelligence has come to finance is through hedge funds and other investment products whose trades are guided—and in some cases wholly dictated—by artificial intelligence. Currently, the jury is still out on AI’s ability to make predictions. AI models are, after all, susceptible to market manipulation. Nonetheless, a 2018 study found that 53% of hedge funds were using AI in its decision-making, and by 2019, over 
$17bn in assets were under AI management.

Key Takeaways

For large organizations, artificial intelligence promises to increase customer personalization, decrease bureaucratic inefficiencies, and give teams a greater ability to generate demand at scale. Artificial Intelligence gives organizations the opportunity to bring personalization to their customers, at scale.

Ask Yourself: How would greater customer personalization transform your business?

AI Super Power
5G
Uses
Autonomous Vehicles
Virtual Reality and Telepresence
Remote Medicine and Surgery
Verizon is leading the 5G revolution. The next-gen mobile data transfer technology is one hundred times faster than the 4G we currently find on our smartphones. 100xing the speed of the remote internet will profoundly alter how we interact with people at a distance and bring powerful technologies like virtual reality and autonomous vehicles to everyday consumers.
Already, Verizon is working to capitalize upon the promise of 5G by building customer loyalty from fleet managers today. Verizon’s Connect is an AI-powered fleet management solution that can automatically process in-car telemetry and dashcam footage for a variety of solutions, such as:
 
1. AI-based video filtering and search;
2. Advanced analytics;
3. Customized coaching for drivers based on in-vehicle sensors;
4. Risk mitigation from fraudulent insurance claims.

Key Takeaways

A faster mobile internet means more data: data from consumers’ phones, data from self-driving cars, and data from what Gartner predicts could be 20.4 billion internet-enabled objects and sensors by the end of this year.
 
Currently, companies already find it extremely difficult to monetize the vast amounts of data they collect. With the rise of 5G, we can expect corporations to deploy artificial intelligence with more urgency. Without AI, even more data will languish, un-utilized and under-monetized.
 
To get a jump-start on this onslaught, companies should work with data scientists today to create systems that efficiently structure and organize data as it flows into the company.

Ask Yourself: How could a lightning-fast mobile internet change the way you do business?

AI Super Power
Forecasting
Uses
Supply Chain Management
Retail
Sales
Kroger is taking machine learning very seriously.
 
In 2015, they purchased a UK analytics firm, brought it to the US, and renamed  84.51°, a tribute to the longitudinal analysis the company employs. The acquisition eventually led to an ongoing initiative called “Embedded Machine Learning”, which is charged with framing, building, deploying machine learning solutions across their business regularly.
 
Supply chain management is a key use case for the retailer. Way back in 2018, their AI-powered sales forecasting application could predict day-by-day sales numbers for each of the items in their 2500 stores, for each of the subsequent 14 days.
 
Imagine what the organization can do today.

Key Takeaways

Kroger is one of several non-tech companies on this list that have allocated the resources necessary to bring an entire AI and ML team in house. This team is responsible for designing, building, and deploying all kinds of solutions, across all areas of the company’s business.
 
By going all-in on AI, Kroger hopes to reduce costs by reducing inefficiencies and maximizing every opportunity.

Ask Yourself: How would your business change if you could double the accuracy of its forecasts?

AI Super Power