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Explore our analyst articles on the impact of AI across industries

AI for Fraud Detection in Retail

AI for Fraud Detection in Retail – 2 Powerful Use Cases

Leading retailers - like Walmart, Stop & Shop, and Home Depot - are enhancing their payment and fraud detection systems, using artificial intelligence that learns transaction norms and infers risk from the context of each transaction.

Artificial Intelligence and the Future of Supply Chain and Logstics

Artificial Intelligence and the Future of Supply Chain and Logistics

Supply chains contain every material, component, product and packaging for the objects that together compose the world we live in. However, there is an often invisible ingredient to successful supply chains: data. 

Machine Vision in Retail - Current Use-Cases and Applications

Machine Vision in Retail – Current Use-Cases and Applications

The retail industry collects massive amounts of data every day, and this makes its key processes ripe for automation with machine learning. Along with the manufacturing sector, the retail industry likely stands to benefit the most from one particular AI technique in the next few years: machine vision, also known as computer vision.

Natural Language Processing in Retail - Current Applications

Natural Language Processing in Retail – Current Applications

The retail and eCommerce sectors were among the first to adopt natural language processing (NLP) in the enterprise, particularly by way of chatbots and conversational interfaces. In this article, we cover three ways retailers can use NLP to automate business processes and offer the customer a better experience. We also give examples of AI vendors that offer this technology and describe their products. The NLP capabilities we discuss include:

Top 3 Most Funded AI Startups in Retail - An Overview

Top 3 Most Funded AI Startups in Retail – An Overview

The retail industry could be losing nearly $1 trillion in sales annually due to business process errors that could be automated by AI, such as restocking in eCommerce. In this article, we discuss the top 3 most well-funded AI startups selling to the retail industry and how their solutions could help retailers and eCommerce sites save money lost to fraud and increase revenue through customer analytics.
Signifyd - Retail and eCommerce Fraud Detection
Signifyd is the most well-funded AI startup in the fraud detection industry for retail and eCommerce, having raised $180 million. They were founded in August 2011 and specialize in fraud detection for retail and eCommerce companies. Their most prominent offering is called “guaranteed fraud detection,” and it likely uses anomaly detection technology to recognize fraudulent transactions and prevent chargebacks. The offering was originally announced exclusively for the Magento eCommerce platform in 2017.

More From Consumer goods Articles
Artificial Intelligence Toys for Kids

Artificial Intelligence Toys for Kids – Current Products and Categories

The business world has been talking about AI for several years now, and it's safe to say that it's reached a certain cultural moment among executives in areas like banking, insurance, and pharma. Government leaders have been much slower to start the conversation around the capabilities of AI, including the possibilities they offer to militaries and the ethical implications of AI when it comes to governance and the legal system.

AI in Taste and Art – The Current State of Machine Learning for Understanding Preferences

AI in Taste and Art – The Current State of Machine Learning for Understanding Preferences

Artificial intelligence and machine learning have fueled technological innovations in marketing, eCommerce, and several other industries. Many people experience the benefits of AI and ML systems without even knowing it every time they search on Google or click on a song in Spotify.

Artificial Intelligence in Gestural Interfaces - Possible Near-Term Applications

Artificial Intelligence in Gestural Interfaces – Possible Near-Term Applications

Gesture-based interfaces are applications that allow users to control devices using hand and other body parts. Today, they are found in devices used in home automation, shopping, consumer electronics, virtual reality and augmented reality gaming, navigation, and driving, among others.

Artificial Intelligence for Video Search and the YouTube of the Future

Machine Learning for Video Search and Video Education – How it Works

Episode Summary: AI, specifically natural language processing, has made it easier to understand text as a medium in a deeper, more efficient way and at scale. With video, the situation is quite different. AI is already being used to help industries that work in the video medium. However, searching for content within videos is more challenging because video is not just voice and sound, it is also a collection of moving and still images on screen. How could AI work to overcome that challenge?

AI for Pricing - Comparing 5 Current Applications

AI for Pricing – Comparing 5 Current Applications

In recent years, artificial intelligence has enabled pricing solutions to track buying trends and determine more competitive product prices. While static pricing keeps prices absolute, dynamic pricing adjusts prices to offer customers different prices based on external factors and their individual buying habits.

More From Entertainment Articles
Deploying a Chatbot in Financial Services

Deploying a Chatbot in Financial Services – Strategic Considerations

Our AI Opportunity Landscape research clearly demonstrates how chatbots are relatively over-hyped in the marketplace, and most buyers drastically overestimate their effectiveness as a result. Some of our press releases about the bloviated claims about chatbot deployments have ruffled the feathers of conversational interface vendors.

Unifying AI Initiatives and Focusing on Impact

One of Australasia’s Largest Banks Unifies Their AI Efforts

The following is a case study for Emerj's AI Opportunity Landscape research. To learn more about how we help companies develop winning AI strategies and identify the highest-ROI applications, watch the two-minute video summary of our AI Opportunity Landscape research.
Problem
The bank had many scattered AI projects, but struggled with:

Artificial Intelligence at Mitsubishi UFJ Financial - Current Initiatives

Artificial Intelligence at Mitsubishi UFJ Financial – Current Initiatives

Mitsubishi UFJ Financial (MUFG) is a Japanese holdings bank and financial services company ranked 5th on S&P Global’s list of the top 100 banks, and the largest Japanese bank on the list.

Machine Learning in Payments - an Overview in Disruptive Times

Machine Learning in Payments – an Overview in Disruptive Times

The coronavirus pandemic has ushered in a new era of digital payments; those who once mailed checks and made purchases in person are now paying their bills electronically and shopping online. As the economy is rattled by the coronavirus, there are some AI startups in the payments space that will succeed and others that will fail. All are pivoting rapidly to eCommerce, if that wasn't already their focus to begin with.

AI-Based Enterprise Search for Claims Processing and Fraud Detection

AI-Based Enterprise Search for Claims Processing and Fraud Detection

Large insurance companies have been experimenting with AI since the middle of the 2010s, piloting chatbots and collecting telematics data for future AI projects. The insurance industry more than many others relies on the collection of data to make critical business decisions.  Whether writing policies, or processing claims efficiently the way insurers employ data will determine the lifetime value of the customer.  

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Artificial Intelligence and National Security Economic Impacts and Considerations@2x

Artificial Intelligence and National Security – Economic Impacts and Considerations

In July 2017, The State Council of China released the “New Generation Artificial Intelligence Development Plan," outlining China's strategy to build a US$150 billion Chinese AI industry in a few short years, and to become the leading nation in AI by the year 2030. Other nations followed suit quickly with national AI strategies of their own - with the US trailing behind by nearly two years before developing a semblance of an AI initiative. The proposed 2021 budget for the national security budget in the US is $740 billion - with a billions of dollars being earmarked for AI specifically (learn more: US Public Sector AI Opportunity Report). 

Emerj at the Launch of the OECD AI Policy Observatory in Paris

Emerj at the Launch of the OECD AI Policy Observatory in Paris

Event Title: Launch of the OECD AI Policy Observatory

Event Host: OECD

Weaponized Artificial Intelligence – Critical Dual-Use Applications

Weaponized Artificial Intelligence – Critical Dual-Use Applications

This article is based on a presentation given by Emerj CEO Daniel Faggella in Geneva, at the 2019 New Shape Forum: Weapons Governance for the Geneva Disarmament Platform. To learn more about Emerj's AI presentations and speaking, visit our presentations page.

Artificial Intelligence in Policing

Artificial Intelligence in Policing – Use-Cases, Ethical Concerns, and Trends

In July of 2018, Daniel Faggella spoke at the Interpol--United Nations (UNICRI) Global Meeting on the Opportunities and Risks of Artificial Intelligence and Robotics for Law Enforcement. It was the very first event on the usage of AI in policing, security and law enforcement by the UN and INTERPOL. 

Emerj CEO Presents at the 2019 New Shape Forum: Weapons Governance

Emerj CEO Presents at the 2019 New Shape Forum: Weapons Governance

Event Title: 2019 New Shape Forum: Weapons Governance

Date: September 30, 2019 - October 1, 2019

More From Government Articles
AI in the Hospital Settling

AI in the Hospital Setting – Challenges and Trends

This article is based on a presentation at the 2017 AI Applications Summit conference in Boston, entitled “Artificial Intelligence in the Hospital Setting” (slide deck embedded below) delivered by Emerj CEO Daniel Faggella - updated with recent insights and interviews from Emerj's podcast and AI Opportunity Landscape data.

AI at Johnson & Johnson 950×540

AI at Johnson & Johnson – Current Investments

We see evidence dating back to 2017 that Johnson & Johnson has been regularly publishing about their investments and initiatives related to artificial intelligence. At present, Johnson & Johnson does not seem to boast any mature, deployed applications with the firm itself, but its AI-related investment initiatives indicate their aspirations.

AI for Pandemic Response

Artificial Intelligence for Pandemic Response and Outbreak Tracking

The COVID-19 pandemic has caused incredible disruption in healthcare systems across the world, as well as an immediate demand for innovative solutions to the growing number of coronavirus patients. Many AI vendors are already trying to find ways they can serve this demand through augmenting their machine learning-powered products - from diagnostics interfaces to radiology solutions and everything in between. 

AI in Mental Health and Well-being - Current Applications and Trends

AI in Mental Health and Well-being – Current Applications and Trends

There are numerous AI initiatives in progress across the healthcare industry; some of these are for mental health and well-being. In this article, we offer an overview of how AI is facilitating mental healthcare.

Emerj CEO Presented at the OECD's Symposium Artificial Intelligence for Science, Industry and Society

Emerj CEO Keynotes OECD’s Symposium on AI for Pharma R&D

Event Title: Symposium Artificial Intelligence for Science, Industry and Society

More From Healthcare Articles
Understanding Predictive Maintenance in Manufacturing

Understanding Predictive Maintenance in Manufacturing

The hypothesis is simple:

Equipment breakdowns or downtime is extremely expensive (imagine a train broken down on isolated tracks, hundreds of miles from the nearest depot)
Heavy equipment (engines, wind turbines, manufacturing machines) produce various streams of data (heat, vibration, time-series, etc)
Machine learning could be used to detect "failure patterns" in that data, helping businesses to maintain equipment health more effectively

How Machines and Robots Learn – the Progression of AI

How Robots Learn – an Interview with Jürgen Schmidhuber

This week, we speak with arguably one of the best-known folks in the domain of neural networks: Jurgen Schmidhuber. He's working on a lot of different applications now in heavy industry, self-driving cars, and other spaces.

Artificial Intelligence In Industrial Automation – Current Applications

Artificial Intelligence In Industrial Automation – Current Applications

Accenture forecast the Industrial Internet of Things could contribute $10 trillion to the global economy by 2030. The report also suggested that sensors, material tracking mechanisms, 3D printing, automated product design, robotics, and wearables could help manufacturers reduce costs and increase productivity. Predictive asset maintenance could potentially reduce equipment and machinery maintenance costs by up to 30% and result in up to 70% fewer breakdowns.

Predictive Analytics in the Oil and Gas Industry - Current Applications

Predictive Analytics in the Oil and Gas Industry – Current Applications

McKinsey reported that most oil and gas operators have not maximized the production potential of their assets. A typical offshore platform, according to the 2017 report, runs at about 77% of its maximum production potential. Industry-wide, the shortfall comes to about 10 million barrels per day, or $200 billion in annual revenue.

AI for Predictive Maintenance Applications in Industry - Examining 5 Use Cases

AI for Predictive Maintenance Applications in Industry – Examining 5 Use Cases

With the entrance of artificial intelligence and its capabilities of recognizing temperature, vibration, and other factors from sensors pre-built into machinery and vehicles, business leaders in heavy industry might be interested in the possible opportunities of predictive and preventative maintenance applications.

More From Heavy industry Articles
Virtual Reality Shopping and Artificial Intelligence - 5 Near-Term Applications

Virtual Reality Shopping and Artificial Intelligence – 5 Near-Term Applications

By implementing an immersive virtual-reality environment, some AI applications claim it is possible to test products or retail ideas that have not been brought to on the market, putting them on a virtual shelf to study consumer reactions and behavior to real-time merchandising.

Artificial Intelligence for Video Search and the YouTube of the Future

Machine Learning for Video Search and Video Education – How it Works

Episode Summary: AI, specifically natural language processing, has made it easier to understand text as a medium in a deeper, more efficient way and at scale. With video, the situation is quite different. AI is already being used to help industries that work in the video medium. However, searching for content within videos is more challenging because video is not just voice and sound, it is also a collection of moving and still images on screen. How could AI work to overcome that challenge?

AI for Speech Recognition - Current Companies, Technology, and Where Its Headed 1

AI for Speech Recognition – Current Companies, Technology, and Trends

Speech recognition is technology that can recognize spoken words, which can then be converted to text. A subset of speech recognition is voice recognition, which is the technology for identifying a person based on their voice.

Amazon Fake Review

Crowdsourced Content Moderation – How it Works and What’s Possible

As the web grows and we spend more and more time online, moderation becomes a bigger and bigger challenge. Content influences buyers, and businesses eager to gain the trust of those customers are likely to do whatever they can to win.

Artificial Intelligence for Video Marketing - Emotion Recognition, Video Generation, and More

Artificial Intelligence in Video Marketing – Emotion Recognition, Video Generation, and More

eMarketer estimates that 62% of global internet users accessed digital video in 2017, and that number is expected to rise to 63.4% by 2020. This may be marginal growth, but, essentially, consumers are expected to spend more time watching video content. 

More From Media Articles
Information Extraction in Oil and Gas - Using AI to Find Oil

Information Extraction in Oil and Gas – Using AI to Find Oil

Oil and gas companies face many of the same challenges as large banks and established insurance firms when it comes to searching through their backlogs of documents. They want to use the data stored within these documents to make decisions on where to drill and determine whether or not they’re in compliance with laws and regulations. 

Artificial Intelligence in the Food and Beverage Industry

AI in the Food and Beverage Industry – 3 Current Use-Cases

Although it's apparent that AI development is slow-moving in the industry, food and beverage companies may be able to use AI for food processing, in particular:

Predictive Maintenance in Oil and Gas - Current Applications

Predictive Maintenance in Oil and Gas – Vendors and Use-Cases

The International Energy Agency’s latest annual gas market report, Gas 2018, estimated that global gas demand could reach more than 4,100 billion cubic meters (bcm) in 2023. This is an increase from 3,740 bcm in 2017. Greater gas demands mean more oil rigs, and the machines on these rigs break down.

AI Search Applications for Compliance, Contracts, and Human Resources

AI Search Applications for Compliance, Contracts, and Human Resources

There's an entire artificial intelligence ecosystem for enterprise search. Most of this is in a purely digital world. Most vendors help with a layer of AI-enabled search that understands terms or phrases and is able to return the results or answers to questions that someone types in. But the problem is compounded when it comes to searching the physical world.

The Internet of Things in the Oil and Gas Industry - Current Applications

Internet of Things in the Oil and Gas Industry – Current Applications

According to McKinsey, global gas demand is expected to reach 4,503 billion cubic meters (bcm) in 2035, showing a more than 1% annual growth from 3,736 bcm in 2017. Asia is expected to be the biggest consumer of the resource at 47%, followed by the rest of the world (24%), the Middle East (16%), and the United States (14%).

More From Natural resources Articles
5 Phases of a Data Audit 950×540

5 Phases of an AI Data Audit – Assessing Opportunity in the Enterprise

Emerj serves enterprises to form their AI strategies, and data audits are part of Emerj's framework for identifying high-ROI AI projects. In this article, we'll break down a slice of this framework, walking through some pragmatic steps leaders can take to drive toward industry-leading outcomes in their organization.

Professional Services Leaders_ Map a Plan for Cost-Cutting, or Get Cut

Professional Services Leaders: Map an AI Plan for Cost-Cutting, or Get Cut

What to do when your clients want to cut costs?

Help them cut costs, and be part of a bigger vision beyond cost-cutting.

Speech Recognition and Transcription in Law and Legal

AI for Speech Recognition and Transcription in Law and Legal

Have you ever been frustrated with how Alexa or Siri don't always understand your verbal requests? If so, then you already understand the problem that our guest this struggles with. He's Tom Livne, co-founder and CEO of Verbit.ai.

AI for Enterprise Legal Departments - Contract Analysis and More

AI for Enterprise Legal Departments – Contract Analysis and More

AI has numerous use cases in legal, from document search to compliance and contract abstraction. This week, we speak with Lars Mahler, Chief Science Officer for LegalSifter, about what's possible with AI for legal departments today and how AI applications for legal teams, such as natural language processing-based contract analysis, work. In addition, Mahler discusses how lawyers at companies and data scientists work together to train machine learning algorithms.

AI for IT Services Firms - Backup, Recovery, and Cybersecurity

AI for IT Services Firms – Backup, Recovery, and Cybersecurity

IT services firms are doing their best to keep up with the changing landscape as AI begins to dominate the tech conversation. Many IT services firms have recently started branding themselves as AI companies without having the requisite talent to back up their claims. In reality, many of the older IT services companies are struggling to hire PhD graduates in machine learning who would rather use their skillset at global AI firms like Google and Amazon.

More From Professional services Articles
Artificial Intelligence and the Future of Supply Chain and Logstics

Artificial Intelligence and the Future of Supply Chain and Logistics

Supply chains contain every material, component, product and packaging for the objects that together compose the world we live in. However, there is an often invisible ingredient to successful supply chains: data. 

how self-driving cars work

How Self-Driving Cars Work – A Simple Overview

The National Highway Traffic Safety Administration (NHTSA) of the U.S. Department of Transportation recently released an overview report on the current state of self-driving technology.

Training Self-Driving Cars in Simulations - The Future of Automotive

Training Self-Driving Cars in Simulations – The Future of Automotive

Danny Lange heads up the AI efforts at Unity, one of the better-known firms in terms of simulations and computer graphics. They work in several different industries, but this week we speak mostly about automotive.

AI in the Automotive Industry - an Analysis of the Space

AI in the Automotive Industry – an Analysis of the Space

In this article, we explore the applications of AI software within the automotive industry from production and manufacturing to insurance and transportation. We will discuss the equipment involved in collecting and analyzing data along with the potential value they offer to manufacturers, shared mobility companies, insurers, and drivers.

Facial Recognition at Airports - Current Applications

Facial Recognition at Airports – Current Applications

Although AI has broader applications in the travel and tourism industry, facial recognition kiosks at airports have been one of the most prominent applications in the public discussion about AI. Their promise: to increase security and potentially speed up passenger boarding.

More From Transportation Articles

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