Search Results for: Natural Language Processing – Business Applications

Founded in 1984 by two computer scientists from Stanford University, Cisco Systems developed the local area network (LAN) concept and achieved a market capitalization of $224 million by the time of its IPO in 1990. Today, Cisco manufactures and markets telecommunications technology as well as other high-technology products and services.

Over the last three years of AI Opportunity Landscape research, we've examined many broad capabilities across the AI ecosystem, from computer vision to conversational interfaces to anomaly detection and beyond. Some of our earliest client research work focused on back-office automation - mostly in financial services and healthcare - and it brought us face-to-face with an array of vendors, use-cases, and opportunities for applying AI for document search and discovery.

This article was a request from one of our Catalyst members. The Catalyst Advisory Program is an application-only coaching program for AI consultants and service providers. The program involves one-to-one advisory, weekly group Q-and-A with other Catalyst members, and a series of proprietary resources and frameworks to land more AI business, and deliver more value with AI projects. Learn more at emerj.com/catalyst.

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.

Artificial intelligence is poised to change every industry - and to create trillions in economic value over the coming decades.

The top 100 global banks, including Goldman Sachs, are beginning to take AI strategies very seriously.

The auto-lending industry stands to benefit from artificial intelligence in much the same way as insurance companies, particularly when it comes to underwriting and risk management. According to Deloitte, nearly $500 billion in new loans and leases are originated annually, and 86% of new car purchases rely on borrowed money. In this article, we discuss how AI startups aim to facilitate different processes within the auto-lending industry, looking to two well-funded startups as examples of what's possible in the space:

Since the advent of online banking services, customers have had several different ways of communicating with their banks. Banks need to monitor all of these incoming customer requests and respond to them in the most efficient way possible. Further, each of the various channels of communication represents a valuable way to segment customers to not only improve how they perceive a bank’s brand but also to market banking products to them better.

Although there are established use-cases for AI applications in the business world, the claims that AI vendors make about returns from their software are often exaggerated. What is also not apparent amongst the AI hype is that adopting AI and machine learning is far more challenging than it might seem.

Our research indicates that AI applications for risk-related banking functions are more numerous than applications for other business areas. Fraud and Cybersecurity, Compliance, Loans and Lending, and Risk Management collectively made up 56% of the AI vendor products in the banking industry, as shown in the graph below: