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:
Several car makers predict they will able to make true self-driving cars in the next few years - as we've covered in our recent self-driving car timeline article. This technology, though, is only valuable if there are plenty of roads these self-driving cars are legally allowed to travel on. Even if the technologies allow for true autonomy, without legal permission the self-driving cars are mostly worthless to individuals and companies.
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.
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.
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.
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.
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.
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.