More flexible production, greater productivity, and the development of new business models are all possible today thanks to digital solutions. But the future of industry offers even more potential: Cutting-edge technologies will create new opportunities for both discrete and process industries to fulfill their customers’ individual requirements.

CBT Infotech enables industrial companies of all sizes to implement current and future technologies for the automation and digitalization. Thus, they can tap into the full potential of Industries 4.0 and get ready for the next level of their digital transformation journey.

Today’s artificial intelligence market is not easy to quantify. Besides the lack of consensus on a coherent definition for “artificial intelligence” as a term, the field’s nascent stage of development makes it difficult to carve out silos or hard barriers of where one industry or application ends, and another begins.

If you’re interested in how developments in machine learning and AI might impact your own company or business, then keeping an eye on trends of industry and application growth is pertinent; we hope that this article will be a good jumping off point to some of the most thought-out assessments of AI and it’s “segments” as we could collate from the web. We’re unable to ensure accuracy of all of the data sets and research from other companies and researchers, but we’re happy to put them on display here for you to dig into and make sense of.

This article serves as a living overview of existing efforts by media, research firms, and others, who have attempted to move from the eagle eye’s view of the AI industry to categorizing technologies under the grand umbrella. Older breakdowns and analyses begin at top of the article and move down to newer trends. In cases where a company or individual has published annual updates of the same breakdown, we’ve kept those breakdowns together for ease of comparison. We end by pulling together what we believe to be key meta-trends and insights from these ongoing analyses.

To help differentiate between some of the terms thrown around the idea of AI, here are some general definitions with technologies associated with AI. These areas are not separate from each other – for example, robotics can utilize machine vision technologies, and robotics process automation can utilize natural language processing for customer service chatbots.

• Robotics:Engineering involved in designing and manufacturing robots. The significant advantage of this technology is that some of the robots can be utilized to perform tasks that are difficult or impossible by human standards.
• Robotic process automation: The use of specialized computer programs or software robots that automate and standardize high-volume repetitive and tedious tasks usually done by humans.
• Machine learning: The science of making computer systems perform actions without being explicitly programmed. By using existing data, computers can forecast future behaviors, patterns, and outcomes without needing human intervention.
• Natural language processing:Focused on the interactions between computers and human languages, especially how computer systems can be programmed to analyze, interpret, and manipulate a large amount of natural language data.
• Machine vision: The science and technology of using computer systems to provide imaging-based automated inspection and analysis with the aid of a camera, analog-to-digital conversion, and digital signal processing.

The influence of AI technology can be seen across sectors such as transportation, education, manufacturing, online shopping, communication, sports, media, healthcare, politics and government, banking and finance, aerospace, and so much more.

Below is a list of essential industries impacted by AI:

• Transportation:Autonomous car, also known as a self-driving car, is a vehicle that can sense its environment and is capable of moving without human interference. This technology can transform the transportation system, because it can analyze traffic and alternative routes, thus reducing travel times.
• Manufacturing:high performing robots work faster, and complete tasks more efficiently than humans. Also, they can work for long periods nonstop as long as the power required for them to function is available. By using 3D technology and machine vision, these machines can speed up the process of product manufacturing.
• Healthcare:Applications such as autonomous surgical robots, virtual nursing assistants, automated image diagnosis, and dosage error reduction have been some of the ways AI has been crucial for the technological advancements in the health sector.
• Entertainment:machine learning can predict a user’s behavior to make recommendations on the type of movie, music, TV shows, and other content he’ll be interested in. Also, adverts can now be personalized based on the user’s preference, thereby increasing the chances a marketer will make a sale.
• Sports:AI technology like automation and predictive analysis can be used in business decisions, sponsorship activations, ticket sales, and determining athletes’ performance.

Future applications of AI would be utilized in automated transportation, cyborg technology, solving problems associated with climate change, deep-sea and space exploration.