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:

Banner Machine learning at insurance companies 950×540

How America’s Top 4 Insurance Companies are Using Machine Learning

The insurance industry is a competitive sector representing an estimated $507 billion or 2.7 percent of the US Gross Domestic Product. As customers become increasingly selective about tailoring their insurance purchases to their unique needs, leading insurers are exploring how machine learning (ML) can improve business operations and customer satisfaction.

Unmanned Aerial Vehicles (UAVs) - Comparing the USA, Israel, and China

Unmanned Aerial Vehicles (UAVs) – Comparing the USA, Israel, and China

While in previous decades military unmanned aerial vehicles (UAV) were very simple pieces of equipment, the technology has advanced rapidly. They are now used all over the world and are a multi-billion dollar industry. According to the Teal Group, current worldwide military UAV production stands at around $2.8 billion, and they project it will grow to $9.4 billion in 2025.

Artificial Intelligence in Sports - Current and Future Applications

Artificial Intelligence in Sports – Current and Future Applications

The North American sports industry is a cultural and economic staple generating billions of dollars in revenue each year. Spectator sports fall under the broader category of arts, entertainment, and recreation, representing 1.1 percent of the GDP in 2016. Artificial intelligence in sports may have been rare just five years ago - but now AI and machine vision are making their way into a number of sports industry applications, from chatbots to computer vision and beyond.

In manufactoring 950×540

Machine Learning in Manufacturing – Present and Future Use-Cases

Major companies including GE, Siemens, Intel, Funac, Kuka, Bosch, NVIDIA and Microsoft are all making significant investments in machine learning-powered approaches to improve all aspects of manufacturing. The technology is being used to bring down labor costs, reduce product defects, shorten unplanned downtimes, improve transition times, and increase production speed.

Artificial Intelligence in in Oil and Gas 950×540

Artificial Intelligence in Oil and Gas – Comparing the Applications of 5 Oil Giants

Oil remains one of the most highly valued commodities in the energy sector. Estimates of total energy investment in 2016 tip the scale at approximately $1.7 trillion which represents 2.2 percent of the global GDP. However, as concerns over the environmental impact of energy production and consumption persist, oil and gas companies are actively seeking innovative approaches to achieving their business goals while reducing environmental impact.

Machine Learning in Retail - Near-Term Applications and Implications

Machine Learning in Retail – Near-Term Applications and Implications

When managers and leaders think about machine learning in retail, they often imagine helpful in-store robots, automated processes like checkout or stocking shelves, or conversational agents that suggest products and answer questions for customers. While these applications should be considered as disruptive factors for retail’s future, it’s unlikely that these factors will be the first wave of AI’s impact on the sector.

Military Robotics Innovation

Military Robotics Innovation – Comparing the US to Other Major Powers

The market for military robotics is massive, and many developments can be observed in public competitions, university campuses, and DARPA's own announcements.

Use Cases of AI for Customer Service - What's Working Now

Use Cases of AI for Customer Service – What’s Working Now

Artificial Intelligence is currently being deployed in customer service to both augment and replace human agents - with the primary goals of improving the customer experience and reducing human customer service costs. While the technology is not yet able to perform all the tasks a human customer service representative could, many consumer requests are very simple ask that sometimes be handled by current AI technologies without human input.