Artificial intelligence (AI) explained
In the simplest terms, AI which stands for artificial intelligence refers to systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they gather. AI manifests itself in several forms. Some examples are:

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Chatbots use artificial intelligence to understand customer problems faster and provide more effective answers
Smart assistants use artificial intelligence to analyze critical information from large free text datasets to improve scheduling
Recommendation engines can provide automatic recommendations for TV programs based on users’ viewing habits
Artificial intelligence is much more about the process and ability to think and analyze data with superpowers than any particular format or function. Although artificial intelligence conjures up images of high-functioning humanoid robots taking over the world, artificial intelligence is not intended to replace humans. It’s designed to significantly improve human capabilities and contributions. This makes it a very valuable business asset.

Artificial intelligence terms
Artificial intelligence has become a catchall term for applications that perform complex tasks that once required human input such as communicating with customers online or playing chess. The term is often used interchangeably with its subfields, which include machine learning and deep learning. But there are differences. For example, machine learning focuses on building systems that learn or improve their performance based on the data they consume. It’s important to note that although all machine learning is artificial intelligence, not all artificial intelligence is machine learning.

To get the full value from AI, many companies are making significant investments in data science teams. Data science, an interdisciplinary field that uses scientific and other methods to extract value from data, combines skills from fields such as statistics and computer science with business knowledge to analyze data collected from multiple sources.

AI and developers
Developers use artificial intelligence to more efficiently perform tasks that would otherwise be done manually, connect with customers, identify patterns and solve problems. To get started with AI, developers need to have a background in mathematics and be comfortable with algorithms.

When starting to use AI to build an app, it helps to start small. By building a relatively simple project, like tic-tac, for example, you’ll learn the basics of artificial intelligence. Learning by doing is a great way to level up any skill, and artificial intelligence is no different. Once you’ve successfully completed one or more small-scale projects, there are no limits to where AI can take you.

How AI technology can help organizations
The central principle of artificial intelligence is to replicate – and then exceed – the way humans perceive and respond to the world. It’s quickly becoming the cornerstone of innovation. Powered by various forms of machine learning that identify patterns in data to enable predictions, AI can add value to your business by:

Providing a more comprehensive understanding of the wealth of data available
Relying on predictions to automate overly complex or mundane tasks
AI in the organization
AI technology improves the performance and productivity of the organization by automating processes or tasks that once required human power. AI can also understand data at a scale no human could. This capability can return significant business benefits. For example, Netflix uses machine learning to provide a level of personalization that helped the company grow its customer base by more than 25% in 2017.

Most companies have made data science a priority and are investing heavily in it. In Gartner’s latest survey of more than 3,000 CIOs, respondents ranked analytics and business intelligence as the most differentiating technology for their organizations. The CIOs surveyed see these technologies as the most strategic for their companies; Therefore, they attract the newest investment.

AI has value in almost every function, business and industry. It includes general and industry-specific applications such as:

Using business and demographic data to predict how much certain customers will spend during their relationship with a business (or customer lifetime value)
Optimize pricing based on customer behavior and preferences
Using image recognition to analyze X-ray images for signs of cancer
How organizations use artificial intelligence
According to the Harvard Business Review, organizations primarily use artificial intelligence to:

Detection and deterrence of security breaches (44 percent)
Solve users’ technology problems (41 percent)
Reduce production management work (34 percent)
Internal compliance measurement using approved suppliers (34 percent)
What is driving the adoption of artificial intelligence?
Three factors drive the development of AI in industries:

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Affordable high performance computing capability is readily available. The abundance of commodity computing power in the cloud allows easy access to affordable, high-performance computing power. Prior to this development, the only computing environments available for AI were non-cloud-based and expensive.
Large amounts of data are available for training. Artificial intelligence needs to be trained on a lot of data to make the right predictions. The emergence of various data tagging tools, plus the ease and availability with which organizations can store and process structured and unstructured data, is enabling more organizations to build and train AI algorithms.
Applied AI provides competitive advantage. Organizations are increasingly recognizing the competitive advantage of applying AI insights to business objectives and making it a business priority. For example, targeted recommendations provided by AI can help businesses make better decisions faster. Many of AI’s features and capabilities can lead to lower costs, reduced risk, faster time to market and much more.
5 common myths about enterprise AI
While many companies have successfully adopted AI technology, there’s also quite a bit of misinformation about AI and what it can and can’t do. Here we explore five common myths about AI: