AI Use Case &
Case Study Library
Structured intelligence across industries, functions, and outcomes — so your leadership team invests in AI that actually works.
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View functions→''Rooms to go'' uses Machine Learning to offer tailored add-on options to customers
Home furnishing retailer Rooms To Go has leveraged Google Analytics to gain a better understanding of their consumers. By identifying products that are often sold together the company was able to customise and personalise their customers'' experience which lead to increased sales and improved the overall shopping experience.
Linked use case: Personalise product recommendations to target prospective customers
1-800 Flowers deploys chatbots to offer a personalised gift buying experience that will increase customer engagement and sales
1-800 Flowers launched its IBM Watson-powered concierge service - Gwyn (gifts when you need) in May, 2017 to help customers get more personalised results and engage them better.
Linked use case: Automate sales conversations through a text chatbot
20th Century Fox and IBM Research reduce movie marketing production time by using machine learning to select scenes for a movie trailer
20th Century Fox implemented IBM Research to select scenes for inclusion in a movie trailer for a feature-length horror film. This process can take a month manually, but was reduced to 24 hours using machine learning from start to finish.
Linked use case: Automate content generation for video and image based marketing materials
30SecondsToFly struggles to scale the automation of SMB corporate travel management with the deployment of text chatbots
30SecondsToFly''s Claire, a travel assistant, uses natural language processing and machine-learning capabilities to assist travellers with their bookings. The technology can provide SMBs with a valuable customer service provider able to adhere to a company''s travel policies. The chatbot is available to process booking queries through SMS or the messaging platform Slack.
Linked use case: Automate customer service conversations through a text chatbot
7-Eleven improved customer marketing and in-store capacity planning in Indonesia and Mexico using machine learning to predict demand variations
7-Eleven decided to use AI to optimise capacity planning and marketing. They established an information analysis environment to analyse patterns and gather valuable insights from point-of-sale data.
Linked use case: Ensure inventory availability by predicting demand and triggering appropriate action
A UK registered charity predicts visitor flow to its building with Markov chain algorithms
A UK registered charity leveraged technology from ASI to predict visitor flow. The provider used wifi usage data to track crowd movement within the building and gather information on the amount of time people spent in each location. ASI created a model indicating the most likely routes people would take through the attraction, congestion points and locations prone to overcrowding using Markov chain algorithms. The algorithm simulated the movement of 500 different hypothetical visitors over a fifteen minute period to come up with the results.
Linked use case: Optimise product layout in stores
A global transport provider gains a significant competitive advantage by implementing AI for supply chain visibility
Hong Kong-based Gravity Supply Chain is utilising artificial intelligence (AI) and big data to bring e-commerce-style supply chain visibility to international freight.
Linked use case: Optimise supply chain
A large european bank identifies issues in post-trade operations by analysing mailboxes with the use of machine learning
A large european bank is leveraging re:infer''s technology to identify inefficiencies from communication data. By using supervised and unsupervised learning the system analysed 300 of the bank''s shared mailboxes to identify issues in operations. The system then conducted a more targeted analysis of the fixed income mailboxes to identify and quantify specific issues that needed attention. The bank identified several areas for improvement and implemented the necessary targeted solutions to improve efficiency.
A large european integrated electric power company is predicting, diagnosing and reducing equipment failures in conventional power plants with machine learning
A large european integrated electric power company implemented C3 IoT''s C3 Predictive Maintenance solution to achieve more accurate predictions of equipment failure and maintenance needs. The technology uses advanced machine learning-based algorithms to monitor instrument signals, track failure modes and detect anomalies in equipment components. The company''s 2,640 megawatt conventional coal-fired power plant benefited from the implementation at it improved prognostic lead time and flexibility in scheduling of maintenance tasks and reduced ununplanned, emergency maintenance tasks.
Linked use case: Predict problems and recommend proactive maintenance for power generation and supporting equipment
AI system predicts risk of diabetes with an 88% accuracy rate in tests
Shanghai’s Ruijin Hospital has partnered with the Chinese AI startup 4Paradigm to apply AI in healthcare, particularly chronic health conditions. They have tested an AI-backed diabetes prediction and management product, which they hope will help them identify patients at risk of developing diabetes up to 15 years in advance. The system showed an 88% accuracy in tests on information from 170,000 people.
Linked use case: Predict risk of condition developing at an early stage
AKQA creates a new sports game using neural networks
Design agency AKQA trained a neural network on data from 400 popular sports around the world as part of a project for Design week. The system came up with a new game, Speedgate, a six players ball game on a field with three gates, which incorporates elements of croquet, rugby and soccer.
ANZ bank identifies high risk loans and predicts customer defaults with deep learning
ANZ bank has collaborated with Nvidia and Monash University researchers to develop deep learning technology. The neural network was trained on customer credit card data and is able to assess risk on a much more frequent basis than current practices and predict the client who are likely to default on payments. The system is currently a proof of concept as the bank has stated that it needs to fully understand how it works before it commercialises it.
Linked use case: Evaluate customer credit risk using application and other relevant data for faster and more efficient decisions
ARUP saves 790 engineering hours using machine learning to detect utility clash points planning a light rail system for Auckland
Arup, in a joint venture with Jacobs, was selected to plan a new light rail system for the city of Auckland. The assessment of utility systems clashing at different locations along the proposed rail line was automated using supervised learning algorithms, reducing the amount of engineering time which would have been required for manual checks by 790 hours.
Linked use case: Collate and evaluate site data for architectural planning
ASOS eliminates the risk of inaccurate data entering finance systems by implementing a machine learning solution for invoice handling
ASOS has implemented a machine learning solution in order to optimise its invoice handling processes. Using Celaton''s inSTREAM™ software as a service, the company is now able to automate its their ''Purchase to Pay'' process, improve efficiency and ensure that the data entering its financial system are accurate.
Linked use case: Automate collection of banking data from non-standard documentation
ASOS.com researchers demonstrate improved customer lifetime value predictions using neural networks and automatic feature selection but do not advise implementation due to increased cost
ASOS researchers demonstrate how the currently used customer lifetime value prediction system can be improved through the use of automatic feature selection. These predictions are used in business operations such as marketing for customising and targeting retention strategies. However, due to the increase cost associated with running the best performing system, it is not at this time considered a commercially viable solution.
Linked use case: Model and predict customer lifetime value
AT&T monitors its network constantly offering seamless service and plans maintenance and upgrades optimally using machine learning
AT&T is automating network monitoring, using machine learning to predict traffic demand based on historical data, day and time, and generate alerts. All the equipments are monitored to detect anomalies and plan optimal predictive maintenance schedule.
Linked use case: Optimise network traffic load balancing
AT&T pulls sales leads from multiple systems to automate data entry into legacy systems using Robotic Process Automation
Using RPA AT&T has been able to automate data entry. Data related to sales leads is extracted from various sources and is automatically filled into enterprise system freeing up hours worth of time for employees. They have also been able to improve customer service by reducing the time taken to offer certain services like ethernet from days to hou rs.
Linked use case: Improve administrative productivity with Robotic Process Automation
AXA UK saves 18,000 people hours in six months by deploying bots to handle repetitive tasks
AXA UK has successfully deployed bots to handle repetitive tasks. Over the last six months the insurance company has leveraged 13 software bots that assist its employees in three departments, the customer property claims, the commercial property and the liability department. The three bots that were named by employees, Harry, Bert and Lenny, helped the staff in tasks like matching customer correspondence with the relevant claims record. The specific task required the bot 42 seconds, while a human needs about four minutes, thus saving the company 18,000 people hours, which translates to about £140,000 in efficiency and productivity gains.
Linked use case: Digitise and automate processes using Robotic Process Automation (RPA)
AXA used deep neural networks to increase the predictability of a customer large traffic accident from 40% to 78%
AXA wanted to reduce payout costs by better predicting the 1% of their customers that would have large traffic accidents resulting in payouts over $10,000. Using deep neural networks on over 70 variables, such as age and region of the drivers address, they increased the accuracy of prediction to 78% versus less than 40% with random forests.
Linked use case: Manage premium and risk pricing for underwriting
Abbvie achieves 90% cumulative medication adherence among patients with schizophrenia using image recognition
Abbvie used AiCure’s artificial intelligence platform to visually confirm medication ingestion. This has facilitated continuous monitoring of patient treatment leading to better compliance and streamlining of clinical trials by reducing sample size.
Linked use case: Monitor patient prescription compliance
Abellio London claims it reduced bus collisions and injuries by 29% and 60% respectively with collision avoidance technology
London’s leading bus operators, Abellio London, have collaborated with Intel''s Mobileye to launch a trial of safety technology. The aim of the project is to reduce bus collisions with cyclists, motorcycles, pedestrians and other road users and hence injuries. 66 buses were included in the trial, on three of the company’s London routes, and were equipped with a camera unit installed on the inside of the windshield and a display placed in the driver’s cab both providing audio and visual warnings. Findings to date who that Mobileye collision avoidance technology has managed to reduce collisions by 29% and reduced injuries from such collisions by 60%.
Linked use case: Automate driving with self-driving vehicles
Abundant Robotics device autonomously harvests apples using machine vision to identify appropriate fruit
Abundant Robotics, a vendor, offers technology which is able to autonomously harvest firm fruits using machine vision. Their product detects the location of apples on branches and according to their color, which signifies if they are ready for harvest, uses a vacuum style system to pull them and collect them.
Linked use case: Deploy robots to do physical tasks in the agricultural process
Accenture redeploys after automating tasks with RPA system
Accenture has developed a system, SynOps, for analysing its various data input sources and automating things like contract review. While it has been using this system internally to automate processes in finance, marketing, accounting, and procurement, purportedly resulting in the redeployment of 40,000 staff, it is now selling it tp clients.
Linked use case: Digitise and automate processes using Robotic Process Automation (RPA)
Acer America improves service by decreasing repeat caller rate by 15% with responses powered by natural language speech recognition.
Acer America drives service improvements with Nuance''s natural language speech recognition technology on hosted IVR platform. The solution, which is based on Natural Language Processing (NLP) to offer call steering, has helped reduce repeat caller rate by 15% and decreases average call time by 50 seconds, among other benefits.
Linked use case: Optimise call routing based on customer characteristics potentially including expressed intent
Action Against AMD and Benevolent AI aim to find treatments for age-related macular degeneration (AMD) that causes blindness using machine learning
Benevolent AI and a group of four charities, Blind Veterans UK, Fight for Sight, the Macular Society and Scottish War Blinded, have partnered to find treatments and a potential cure for AMD. Benevolent AI''s machine learning technology will be leveraged to analyse existing scientific papers, clinical trials information, images, formulas, patents and any other knowledge we have on age-related macular degeneration (AMD) to uncover potential patterns, connections and point researchers towards important research areas.
Linked use case: Accelerate drug discovery by automating research stages and data integration and analysis