Artificial intelligence (AI) has a wide range of uses in businesses, including streamlining job processes and aggregating business data.
Many people still associate AI with science-fiction dystopias, but that depiction is fading away as AI develops and becomes more commonplace in our daily lives. Today, AI is a household name – and sometimes even a household presence like Alexa or Google Assistant.
AI should be looked at for business capabilities more than technologies. In business, AI has a wide range of uses; most of us interact with AI in some form daily. From marketing to chatbots, AI is implemented in virtually every business process across all industries.
As AI technologies increase, they are becoming imperative for businesses that want to maintain a competitive edge.
What is artificial intelligence?
According to IBM, artificial intelligence leverages computers and machines to mimic the problem-solving and decision-making capabilities of the human mind.
Over the years, multiple definitions of AI have surfaced. John McCarthy wrote a paper in 2004 called, What Is Artificial Intelligence? where he defined AI.
“It is the science and engineering of making intelligent machines, especially intelligent computer programs,” he wrote. “It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable.”
Naming specific applications as “artificial intelligence” is like calling a car a “vehicle” – it’s technically correct but doesn’t cover any specifics. To understand what type of AI is predominant in business, we must dig deeper.
Machine learning vs. deep learning
It’s important to note that both machine learning and deep learning are subfields of AI, and deep learning is a subfield of machine learning.
Machine learning is one of the most common types of AI in development for business purposes today. Machine learning is primarily used to process large amounts of data quickly. These types of AI are algorithms that appear to “learn” over time.
Deep learning is an even more specific version of machine learning that relies on neural networks to engage in what is known as nonlinear reasoning. Deep learning is crucial to performing more advanced functions, such as fraud detection, by analyzing a wide range of factors at once.
Deep learning has a great deal of promise in business and is likely to be used more often. Machine learning is more dependent on user information inputted. In contrast, deep learning models are far more scalable and detailed and are more independent as performance improves as data is received.
AI in business today
Rather than serving as a replacement for human intelligence, AI is used as a support tool for businesses. AI is adept at analyzing and processing troves of data much faster than a human brain could. AI software can come up with synthesized courses of action and present them to the human user. In this way, you can use AI to see the possible consequences of each step and streamline the decision-making process.
“Artificial intelligence is kind of the second coming of software,” said Amir Husain, founder and CEO of machine-learning company SparkCognition, explained to Business News Daily. “It’s a form of software that makes decisions on its own, that’s able to act even in situations not foreseen by the programmers. Artificial intelligence has a wider latitude of decision-making ability as opposed to traditional software.”
Many businesses use AI to reduce operational costs, increase efficiency, grow revenue, and improve customer experience.
An example of how businesses can use AI to increase efficiency and improve customer experience is AI chatbots. AI chatbots are a fascinating advancement in today’s digital technology landscape. Whether answering specific questions or guiding you through a complex B2B sales process, AI chatbots can do it all.
AI chatbot software can understand language and facial expressions outside of pre-programmed commands and provide a response based on existing data. This software allows site visitors to lead the conversation, voicing their intent in their own words.
With AI chatbots constantly learning from their conversations, over time, they can adapt their responses to a wide range of uses, such as analyzing a customer’s feelings or making predictions about what a site visitor is looking for on your website.
According to a recent Infosys study, the main driving force for using AI in business is competitor advantage.
- 76% of IT and business decision-makers believe that AI is fundamental for future success.
- 64% of respondents believe that their organization’s future growth depends on large-scale AI adoption.
- Most decision-makers believe AI can deliver positive change for society (70%) and the economy (76%).
In conclusion, deploying the right AI technology to your business may gain the ability to save time and money by automating and optimizing routing processes and tasks. Business decisions based on outputs from cognitive technologies use insight to predict customer preferences and offer them a better, more personalized experience, mine vast amounts of data to generate quality leads and grow your customer base.
Interested in learning more about the world of artificial intelligence?
Canadian College of Business and Technology’s Diploma in Data Engineering and Analytics will help students gain the knowledge, practical experience and confidence of a data expert. Data engineers essentially transfer raw data into readily accessible data for machine learning, AI and analytics systems.
Trebas Institute Montreal’s Analytics, Big Data and Business Intelligence program will give students the ability to set up networked and automated databases, operate data warehouses, perform refined analyses and produce detailed reports.
Toronto School of Management’s Diploma in Data Analytics helps students to learn to analyze data using cutting-edge technology to drive proactive decision-making and optimize business performance.