Matthew DeMello
Matthew is Senior Editor at Emerj, focused on enterprise AI use-cases and trends. He previously served as podcast producer with CrossBorder Solutions, a venture-back AI-enabled tax solutions firm. Prior, Matthew served three years at the World Policy Institute as a news editor and podcast producer.
Articles by Matthew
30 articles
This interview analysis is sponsored by Arkestro and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.
As life sciences organizations increasingly adopt AI to enhance productivity, streamline workflows, and improve quality, aligning AI initiatives with business objectives and evolving traditional return on investment (ROI) metrics have become essential strategies. These practices not only secure executive buy-in but also ensure sustained success in AI adoption.
This article is sponsored by Arkestro, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.
AstraZeneca is a global biopharmaceutical company that researches, develops, manufactures, and markets prescription drugs and vaccines. Its key therapeutic areas include oncology, cardiovascular, renal, metabolism, respiratory, and immunology. In 2022, the company reported revenue of $42.67 billion and a profit of $4.08 billion. The company has a significant global presence, employing around 89,900 people across more than 60 countries as of 2023.
This interview analysis is sponsored by Quantiphi and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.
Riya Pahuja also contributed reporting to this article.
As AI systems become increasingly capable of greater cognitive functions across vast enterprises and public functions, more severe concern around how these technologies might impact humanity and how those impacts are covered by relevant media is becoming a central talking point across global governing bodies.
AI is driving change across many industries, including logistics and manufacturing. Companies need to strike the right balance between automation and human intervention. This interaction represents a specific area of study known as human-automation interaction.
Navigating AI's challenges in transforming critical business operations applications are two pivotal aspects driving what is becoming a right of passage for nearly every industry in the evolution of modern enterprises. As organizations strive to harness the power of AI, they encounter intricate challenges, from data extraction to the complex task of molding AI into a tool that enhances various business functions.
AI initiatives that cannot find ROI have no use in modern business. However, the path to ROI from enterprise-wide digital transformations is never a straight and narrow road. A pre-pandemic survey from MIT Sloan Management Review and Boston Consulting Group found that 70% of companies among those surveyed reported no value from their AI investments.
This article is sponsored by Riskified, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.
The advent of the COVID-19 pandemic is leaving retail and eCommerce enterprises awash in numerous, often chaotic trends, many of which are proving critical for driving AI adoption throughout the industry. Perhaps most prominent among these market dynamics is an enormous shift to online retail.
Event Title: 4th OECD Global Forum on Digital Security for Prosperity
Event Host: OECD
Location: Paris, France
For a tech subsector on everyone's proverbial lips' at the moment, things can hardly be described as 'easygoing' for the AI vendor startup market in 2023.
While machine learning might be as close to a household name as any AI capability in 2023, any serious historian will tell you the technology itself is nothing new. The term 'machine learning' was coined in an IBM study on computer gaming and AI dating back to 1959.
Untangling Manufacturing Procurement with Data in the “Next Normal” – with David Schultz of Westfall
This article is sponsored by Arkestro, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.
Banks and banking AI vendors turn to Emerj to help them maximize ROI by allocating their funds to the most high-need areas. Our research also helps them make smarter decisions by identifying the projects that are more accessible and have the highest chance of resulting in near-term financial returns.
While the steel industry may not be synonymous with AI adoption, steel manufacturers are not different from any other business in ensuring efficiency in their output and throughput. There are almost certainly opportunities for AI implementation across an industry worth hundreds of billions of dollars that currently lags behind in adopting AI technology.
Intelligent document processing is best thought of as another name for data extraction, where paper-based information is transferred to a digital format. According to the U.S. Governmental Services Administration, roughly 80% of any organization's data comes from unstructured sources – like paper records management.
Compliance workflows across financial services are no strangers to AI. Noncoding enterprise leaders are often awash in reports on how robust the AI vendor market is for AML and KYC or KYCC (know your customer's customer) compliance. Celent estimated that spending in the financial services sector on AML/KYC compliance tech and operations would reach $37.1 billion last year, an increase of 13.7% from 2020.
Insurance is a growing arena for AI adoption and in many cases, automation is leading the way to streamline customer experiences and the organizational pipelines behind them along the entire customer journey.
Financial services is an industry rife with repetitive processes and workflows that do not ultimately require human judgment to complete. Nearly three out of five leading banks polled [pdf] in a survey from Arizant, American Banker, and robotic process automation (RPA) vendor UiPath reported that their organizations had already implemented "moderate or significant" automation technologies by March 2022 to accomplish these tasks at their organizations.
AI plays a more significant role in our lives every day, and cybersecurity is hardly an exception – for both the "cat" and "mouse" sides of the table. According to a study from the Ponemon Institute in partnership with Accenture, cybercrime alone cost financial services firms $18.5 million on average in 2018.
This article was not sponsored, but draws upon a webinar sponsored by Uniphore. This article was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.
The AI vendor market is as diverse as the global economy itself. As AI applications evolve into every corner of our lives, so do the expertise and proficiency of the data professionals, business leaders and subject matter experts at the heart of the products and services transforming how we live and work.
This interview analysis is sponsored by SambaNova Systems was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.
Payment Card Industry (PCI) compliance is a rite of passage for emerging businesses, or at least a compelling marketing narrative for those who take the initiative to achieve certification before partners, future deals and business circumstances demand it.
COVID-19 did not just bring waves of diseases and contagious variants across the world starting in early 2020 – a tsunami of fraud soon followed the broad sweep of a pandemic that would engulf the global insurance industry.
The finance industry has evolved quite a long way since the days of the SAC scandal and after being diagnosed with an insider trading epidemic in 2014 by academic studies from McGill and New York University – learning countless lessons along the way.
Picture a financial services company and images of numbers, analysis, and data-crunching in scrutinizing reports come to mind — and for good reason. In the heavily regulated world of financial services, decision-makers rely on data to feed their decisions and support their conclusions.
In 2020, fines for Anti-Money Laundering (AML) noncompliance reached $2.2 billion, up nearly 400% from 2019, according to Kroll data. The trend continued into 2021. Through June 30, AML fines totaled $994 million, suggesting another year of strict regulatory enforcement action.
Like many legacy and document-heavy industries in 2022, the entire financial services sector is undergoing a transformation through AI capabilities. These technologies have successfully disrupted many systems and processes once considered sacrosanct: personal financial transactions, collection and analysis of consumer data, personalized offerings of financial products and services, and more.