In the simplest terms, artificial intelligence (AI) refers to systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they collect. Artificial intelligence manifests itself in many forms. For example:
Chatbots use artificial intelligence to understand customers' problems faster and provide more efficient answers
Intelligent assistants leverage artificial intelligence to pull critical information from large user-defined datasets to improve scheduling
Recommendation engines can automatically suggest TV shows based on users' viewing habits
Artificial Intelligence is about super-powered thinking and data analysis capability and process rather than any particular form or function. Although artificial intelligence provides images of high-level human-like robots taking over the world, the purpose of artificial intelligence is not to replace humans. The aim is to significantly develop and contribute to human capabilities. Therefore, it is a highly valuable commercial asset.
Terms of Artificial Intelligence
Artificial Intelligence has become an all-encompassing term for application software that once performed complex tasks that required human input, such as communicating with customers online or playing chess. The term is often used interchangeably with sub-branches such as machine learning and deep learning. However, these are different concepts. For example, machine learning focuses on building systems that learn or improve performance based on the data consumed. It's important to remember that while all machine learning is AI, not all AI is machine learning.
Many companies are investing heavily in their data science teams to take advantage of all the value AI has to offer. An interdisciplinary field that uses scientific and other methods to extract value from data, data science combines the skills of fields such as statistics and computer science with business knowledge to analyze data collected from multiple sources.
How does Artificial Intelligence help organizations?
The basic principle of artificial intelligence is to imitate and then transcend how humans perceive and respond to the world. It is fast becoming the cornerstone of innovation. AI can add value to your business with the support of a wide variety of machine learning capabilities that recognize patterns in data to enable predictions:
Offers a broader understanding of much more accessible data
Relying on predictions to automate overly complex or mundane tasks
Artificial Intelligence in the Companies
AI technology improves enterprise performance and productivity by automating processes or tasks that previously required manpower. Artificial Intelligence can also make sense of data on a scale that no human can achieve. This feature can provide tremendous business benefits. For example, Netflix used machine learning to provide a certain level of personalization, resulting in more than 25 percent growth in its customer base in 2017.
Many companies are prioritizing and investing in data science. According to a recent Gartner survey of more than 3,000 CIOs, respondents rated analytics and business intelligence as the technology that makes the most difference for their organization. The surveyed CIOs view these technologies as the most strategic for their companies, thus attracting many new investments.
Artificial Intelligence delivers value for every line of business, sector and industry. This includes general and industry-specific applications such as:
Using transactional and demographic data to predict how specific customers will spend (or customer lifecycle value) throughout their relationship with a business
By optimizing pricing based on customer behavior and preferences
Using image recognition to analyze x-ray images for signs of cancer
How are companies using artificial intelligence?
According to the Harvard Business Review, companies use artificial intelligence primarily for the following purposes:
Detecting and preventing security breaches (44 percent)
Solving users' technology-related problems (41 percent)
Reducing production management efforts (34 percent)
Measuring internal compliance in using approved vendors (34 percent)
What drives the adoption of Artificial Intelligence?
Three factors behind AI development across industries:
Affordable, high-performance computing capability is easily accessible. A high amount of commodity computing power in the cloud provides easy access to affordable and high-performance computing power. Prior to this development, only non-cloud-based and exorbitantly priced computing environments were available for AI.
A large amount of data is accessible for training. Artificial Intelligence needs to be trained with large amounts of data to make accurate predictions. The emergence of a wide variety of tools for labeling data and the ability for organizations to store and process both structured and unstructured data in an easy and affordable way allows organizations to create and train AI algorithms.
Applied Artificial Intelligence provides competitive advantage. More and more companies are recognizing the competitive advantage of applying AI insights to their business goals and making it a business-wide priority. For example, targeted recommendations powered by AI can help businesses make better decisions in less time. The many features and capabilities offered by AI can reduce costs, reduce risks, accelerate time-to-market, and much more.
Advantages and challenges of making AI functional
There are several success stories that prove the value of artificial intelligence. Organizations that incorporate machine learning and cognitive interactions into their traditional business processes and applications can greatly improve the user experience and increase productivity.
However, there are some obstacles. For some reason, very few companies have deployed AI on a large scale. For example, without the use of cloud-based computing, AI projects are often numerically expensive. Also, they are complex to create and require expertise when demand is high and supply is low. Knowing when and where to incorporate AI and when to turn to third parties will help minimize these challenges.
Artificial Intelligence success stories
AI is the driving factor behind some key success stories:
According to the Harvard Business Review, the Associated Press produced 12 times as many stories by training AI software to automatically write low-yield news stories. This gave journalists more freedom to write more detailed stories.
Deep Patient, an AI-powered tool created by the Mount Sinai Icahn School of Medicine, allows doctors to identify high-risk patients even before the disease is diagnosed. The tool analyzes a patient's medical history to predict almost 80 diseases up to a year before onset, according to insideBIGDATA.
Out-of-the-box AI makes it easy to operationalize AI
The emergence of AI-powered solutions and tools means more companies can leverage AI at much lower cost and in less time. Out-of-the-box AI refers to solutions, tools, and software that have built-in AI features or automate algorithmic decision-making.
Out-of-the-box AI can be any solution, from self-healing autonomous databases using machine learning to pre-built models that can be applied to a variety of datasets to tackle challenges like image recognition and text analytics. It can help companies accelerate time to value, increase productivity, reduce costs and improve relationships with customers.
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