AI Sector Overviews Articles and Reports

Artificial intelligence “sector overview” reports are designed to help business leaders explore the possibilities and important AI trends across industries. Search our sector overview reports below:

Everyday Examples of Artificial Intelligence and Machine Learning 950×540

Everyday Examples of Artificial Intelligence and Machine Learning

With all the excitement and hype about AI that’s “just around the corner”—self-driving cars, instant machine translation, etc.—it can be difficult to see how AI is affecting the lives of regular people from moment to moment. What are examples of artificial intelligence that you're already using—right now?

Machine Learning in Gaming - Building AIs to Conquer Virtual Worlds

Machine Learning in Gaming – Building AIs to Conquer Virtual Worlds

In virtual worlds, AIs are getting smarter. The earliest instance of artificial intelligence in games was in 1952, when a lone graduate student in the UK created a rules-based AI that could play a perfect game of tic-tac-toe. Today, teams of researchers are working on—or have already succeeded in—creating AIs that can defeat humans in increasingly complex games.

Natural Language Processing – Business Applications

Natural Language Processing – Business Applications

Executives worry about their businesses.

They often have to navigate, with limited resources, a stormy market made of customers, competitors, and regulators, and the interactions between all these actors make finding answers to business questions a complex process.

Deep Learning Applications in Medical Imaging 9

Deep Learning Applications in Medical Imaging

In 1895, the German physicist, Wilhelm Röntgen, showed his wife Anna an X-ray of her hand. “I have seen my death,” she said. Medical imaging broke paradigms when it first began more than 100 years ago, and deep learning medical applications that have evolved over the past few years seem poised to once again take us beyond our current reality and open up new possibilities in the field.

Deep Learning Applications in Medical Imaging 8

Machine Learning Algorithms for Business Applications – Complete Guide

With the development of free, open-source machine learning and artificial intelligence tools like Google’s TensorFlow and sci-kit learn, as well as “ML-as-a-service” products like Google’s Cloud Prediction API and Microsoft’s Azure Machine Learning platform, it’s never been easier for companies of all sizes to harness the power of data. But machine learning is such a vast, complex field. Where do you start learning how to use it in your business?

Google Algorithm Disrupts Medical Field, Intel Launches Automated Driving Group, and More  - This Week in Artificial Intelligence 12-02-16 12

Venture Investments in Artificial Intelligence – Trends in 2016 and Beyond

Investments in artificial intelligence continued on an upward swing in 2016, following through on the technology's promise to disrupt how business is done across industries.

7 Chatbot Use Cases That Actually Work 950×540 (1)

7 Chatbot Use Cases That Actually Work

Since Facebook Messenger, WhatsApp, Kik, Slack, and a growing number of bot-creation platforms came online, developers have been churning out chatbots across industries, with Facebook's most recent bot count at over 33,000. At a CRM technologies conference in 2011, Gartner predicted that 85 percent of customer engagement would be fielded without human intervention. Though a seeming natural fit for retail and purchasing-related decisions, it doesn't appear that chatbot technology will play favorites in the coming few years, with uses cases being promoted in finance, human resources, and even legal services.

Google Algorithm Disrupts Medical Field, Intel Launches Automated Driving Group, and More  - This Week in Artificial Intelligence 12-02-16 7

Where Healthcare’s Big Data Actually Comes From

While there have been and continue to be innovative and significant machine learning applications in healthcare, the industry has been slower to come to and embrace the big data movement than other industries. But a snail's pace hasn't kept the data from mounting, and the underlying value in the data now available to health care providers and related service providers is a veritable goldmine. In this editorial, we provide an overview of where healthcare's big data actually comes from, and why providing robust data analytics services in this sector matters.