According to a report by IDC, worldwide spending on artificial intelligence systems is forecast to reach $35.8 billion in 2019, an increase of 44.0% over the amount spent in 2018. The report also predicts that the retail sector will lead the spending, followed by the banking sector. Artificial intelligence is well-positioned to impact various sectors like retail, healthcare, banking, finance, discrete manufacturing, transportation, etc. According to a Gartner survey, 37% of organizations have implemented AI in some way. In the early stages, AI was based on rule-based systems, in which, the AI system depended on a knowledge base of rules to deliver business value.
Just a few years ago, companies used innovation and digital transformation mostly to differentiate themselves and to stay competitive. The dramatic growth in digital technologies and cloud computing over the last couple of years has since changed this mindset. Today, organizations must be innovative and leverage the latest technologies simply to stay in business. Enterprises that implement online retail, banking, and other services aren't considering these channels as just another route to increase their revenue. They realize that online services are fast becoming their primary revenue channel.
In the finance sector, for instance, AI and ML can help firms improve everything from their retail banking experience to their trading algorithms, business analytics and fraud detection protocols. But there's a catch: the promise of AI and ML technologies may not be realised unless some key enabling technologies are put in place at the outset. First, firms need a network with fast, scalable, secure and rapidly deployable connectivity. Second, they need a way to coordinate big data as it flows between public and private clouds. This need for smart connectivity stems from the special demands of artificial intelligence.
The Internet of things (IoT) has a significant potential to fall into the endless pit of a buzzword- vagueness, and it merely is an ecosystem of various kinds of objects that are connected through the Internet. These kinds of objects ranging from cell phones and wearables to machines, generate a constant and massive amount of data every day. The artificial intelligence (AI) also often falls into the same trap. The goal of artificial intelligence in the new IoT scenario is not only to use the humongous data to extract meaningful insights but also to help IoT integrated setups to derive higher value. It implies the machine's intelligence, where the device gains the capabilities of simulating a real human brain.
In recent times the Artificial Intelligence (AI) is the breakthrough technology. We have started learning the ways to communicate with devices. We are successful in directing machines to perform certain tasks using their intelligence. Of late, machines are performing many smarter activities using cognitive intelligence in contrast to natural intelligence (NI) displayed by human and other animals. AI is being used in many sectors and it has opened the doors of implementation of AI in many other emerging sectors.