What is Artificial Intelligence?

We hear about AI every day, but the mechanics behind it aren’t always clear. So, what is artificial intelligence? In short, it’s any technology that can mimic human intelligence and decision-making processes. While AI is commonly associated with robotics and semi-autonomous machines, a large subset of artificial intelligence deals primarily with software that can imitate human behavior through functions like pattern recognition, natural language processing (NLP), and machine learning.

How exactly does artificial intelligence work and how is it used today? Read on to learn more about the various types of artificial intelligence in the world today, their benefits, and the wide range of applications for this technology across different industries.

Artificial Intelligence 101

The capabilities of artificial intelligence are incredibly diverse, spanning from basic repetitive functions to incredibly complex machine learning algorithms that mirror human thought processes. To understand how AI operates, it helps to know the roles it performs. Essentially, artificial intelligence falls into two categories: narrow AI and general AI.

Narrow AI

The vast majority of AI seen in the world today falls under this label. With narrow AI, a software program or a machine is given a predefined set of instructions to follow in order to complete a limited range of tasks. A few narrow artificial intelligence examples may include programming a Roomba to navigate basic obstacles throughout a house or developing basic reactive machines that can attach labels to products on an assembly line. Today, narrow AI is used to create facial recognition software, program customer service chatbots, and develop NLP models like the kind used in predictive texting. The same basic principle is used when developing recommendation engines for websites and apps, such as Netflix or Amazon.

General AI

In contrast, general AI aims to perform a wide variety of complex tasks on a level that’s comparable to human intelligence. While narrow AI lacks the ability to carry knowledge from one domain to another, general AI would have the ability to learn from previous experiences and apply that knowledge to improve a diversity of future decision-making processes. Human technology isn’t quite advanced enough to create a fully autonomous general AI system yet, but the basic premise of Moore’s Law suggests a breakthrough in this form of artificial intelligence is just around the corner.

Components of Artificial Intelligence

AI must be able to follow instructions, interpret data, and demonstrate a basic ability to navigate obstacles or solve problems. Here are the fundamental components of the various types of artificial intelligence in use today.

Learning and Reasoning

Human beings learn through experience, and as time goes on, we use the lessons gleaned from these experiences to reason through problems we encounter in the future. Artificial intelligence works in a similar way. Through memorization or trial and error, AI can compile a storehouse of previous experiences to determine the best way to reach a desired result. For example, an AI program can be fed decades of historical weather data in a given region to output the most statistically probable forecasts. In much the same way, AI can examine a company’s prior sales performance to infer future outcomes.


Another key aspect of artificial intelligence is the ability to perceive an environment and react accordingly. This is done through any number of sensors and visual input devices, such as a temperature monitoring module or a high-definition camera. Today, perception in AI is most commonly seen in autonomous vehicles that gather huge volumes of sensory input to conduct lane changes, recognize pedestrians, and avoid accidents.


Artificial intelligence can quickly evaluate a wide range of options to find the correct solution to a problem. A good example of this can be seen in modern chess engines which utilize popular algorithms such as Alpha-Beta Pruning or the MinMax algorithm to determine which moves are most likely to produce the desired outcome, which is checkmate or the resignation of the opponent. For the chess engine Stockfish, this is done by evaluating the position of the pieces after each move and calculating all possible moves the opponent can make. Next, the AI carefully calculates the best responses to gain incremental advantages that eventually lead to victory.

Natural Language Abilities

Another major component of AI is speech recognition. Just as with Amazon’s Alexa and Apple’s Siri, a large subset of AI today is heavily focused on natural language processing. This branch of computer science seeks to constantly improve upon the abilities of artificial intelligence to recognize, interpret, and ultimately respond to human speech. The development of NLP can also be observed in the rise of virtual assistants and chatbots online or voice assistants for automated customer service phone systems. However, NLP also encompasses audio-to-text transcription, translation, or even creating applications that can reproduce original text from various source materials. Artificial intelligence companies like OpenAI continue to work on mimicking human writing through their ChatGPT platform, while cloud-based apps like Grammarly offer fast and accurate editing suggestions that even human proofreaders can miss.

At Consensus, our Natural Language Processing solutions will ensure your healthcare institution’s paperwork always remains organized and accurate, freeing up valuable physician time while improving efficiency in the process. We call it Clarity, and it’s a powerful data extraction tool that can speed up referrals, expedite prior authorizations, improve treatment times, and help eliminate congested workflows that bog down daily operations.

Evolution of AI

As technology improves, the scope and breadth of what AI can do continues to evolve. Over the past 80 years, artificial intelligence has gone from a mere concept in the imagination of engineers and computer scientists to a ubiquitous mainstay of modern existence in most of the known world.

The history of AI can be traced back to the 1940s and 1950s when the first digital computers were manufactured. In 1952, English computer scientist Christopher Strachey created the world’s first artificial intelligence program that could complete a game of checkers without human intervention. Artificial intelligence continued to improve in the decades that followed, leading to breakthroughs in basic neural networks such as Perceptron in 1958. By 1966, Shakey — the world’s first mobile intelligent robot — was introduced to the world.

With the release of Deep Blue in 1997, the world marveled as AI managed to beat chess grandmaster Gary Kasparov in a series of six games, revealing for the first time that artificial intelligence could operate on an analytical level comparable to humans. Today, the rapid advancement of AI can be seen everywhere from virtual assistants like Alexa to self-driving cars and powerful tools like ChatGPT.

The evolution of artificial intelligence consists of three main stages.

Machine Learning

With machine learning models, an artificial intelligence system is “trained” to identify patterns from various datasets it’s provided. This learning process may be either supervised, unsupervised, or a combination of both. Alternatively, a reinforcement machine learning approach can be used to teach an AI program by trial and error which outputs are desirable. Some commonly seen applications of machine learning include programs that can help financial institutions automate credit score calculations or loan recommendations, spam filters for email, or data mining processes.

Deep Learning

The next tier of artificial intelligence is deep learning, which is a more advanced machine learning apparatus that relies on the development of neural networks to rapidly process vast amounts of complex data. Input received by deep learning artificial intelligence software passes through multiple layers of “nodes” similar to the way a human brain functions. As data passes through each layer, the output gradually becomes more and more accurate. Deep learning algorithms are often used in areas like facial recognition, detecting specific objects embedded in images, or even identifying fraud in huge amounts of financial transaction datasets. Due to the massive amount of computational power needed to create deep learning neural networks, clusters of GPUs on cloud services are often used to conserve resources and reduce neural network training times.

Generative Models

With generative models, an AI program is fed a large volume of data such as thousands of articles, videos, or images which the AI can then learn to emulate or recreate on its own. For example, a human can provide a generative AI program with thousands of images of fine art throughout history, and the program will use that information to create new images based on specific criteria the operator wants. Today, generative models represent the frontier of artificial intelligence systems as they demonstrate a level of creativity that other forms of AI lack.

Applications of Artificial Intelligence

AI’s potential continues to expand every year as computer scientists discover new ways to overcome old obstacles. Where once artificial intelligence was seen as a mere novelty, this technology has found its way into virtually every aspect of modern life. Here are some artificial intelligence examples found in various industries today.

Healthcare Industry

In the world of healthcare, AI has found use cases in helping to predict the health outcomes of patients, the development of personal health virtual assistants, and the automation of processing health records or paperwork. Machine learning in AI may also be applied to assist physicians in improving the accuracy of diagnoses, which can improve patient experiences and outcomes.

Considering the sheer volume of patient records, faxes, and other physical documents healthcare institutions deal with on a daily basis, mistakes are bound to happen. That’s why our team at Consensus launched our AI-powered Clarity Clinical Documentation system. Clarity CD takes all the guesswork out of collating documents through real-time image capture and natural language processing. From there, Clarity will automatically identify patterns in the text to ensure all records are properly organized without the need for redundant human supervision.

Education Industry

Artificial intelligence also has numerous applications in the field of education. For teachers, AI can be used to analyze patterns in student performance and assist with devising training programs or tests that best accommodate the personal needs of individual students. In addition, AI can assist those in administrative roles with tracking enrollment and attendance records or automating repetitive workflows like admission processing. Examples of how AI can help to improve teaching approaches and curriculum can already be seen in language learning programs such as Duolingo and Babble AI.

E-Commerce Industry

The rise of artificial intelligence in business is already having a profound impact on the way companies operate and how they engage with customers. In the e-commerce industry, for example, AI can help businesses generate personalized recommendations for customers based on previous purchases or predictable behaviors. Meanwhile, AI chatbots can help e-commerce platforms more efficiently manage and process customer service queries, automate product returns, or provide individuals with answers to FAQs by correlating keywords in the chat box to previously resolved queries.

Robotics Industry

The field of robotics continues to undergo an impressive transformation thanks to constant breakthroughs in artificial intelligence. In large-scale manufacturing environments, AI can be trained to identify quality control issues with a high level of accuracy through the use of computer vision algorithms. AI-augmented robotics can also be used to automate certain agricultural tasks like planting, watering, or recognizing and picking ripe fruit. The same concept is already at work in today’s self-driving vehicles.

Benefits of AI

Artificial intelligence offers numerous advantages if you know how to leverage the technology. AI makes it possible for businesses and organizations to streamline operations, make more informed decisions, or even enhance the security of employees, customers, and patients. Here are some of the most valuable benefits of artificial intelligence.

Productivity and Efficiency

One of the most attractive features of AI is its ability to automate many redundant tasks that would otherwise consume human labor resources. This translates directly to more productive staff and more efficient workflows. For example, AI can be used to automate new employee onboarding and payroll distribution, so you can streamline the hiring process and free up time for HR staff to focus on other matters.

In a healthcare environment where prior authorizations can slow down treatment or congest patient processing, AI offers a wealth of advantages. At Consensus, our Clarity Natural Language Processing AI solution makes it easy to convert unstructured prior authorization requests into a ready-made digital format for payers. This means faster treatment times and improved patient outcomes. In addition, our Clarity system removes any guesswork or human errors that can occur during the transcription and billing process, saving your healthcare institution time and labor.


Artificial intelligence also makes it easier for organizations to make more informed decisions. For example, datasets of employee performance reviews, attendance records, and hours worked can be used to help generate recommendations regarding pay increases or promotions. Alternatively, AI can assist with trend analysis of revenue streams to identify growth opportunities or assist in determining the best time to expand operations. Likewise, artificial intelligence can be used to monitor inventory at businesses to track breakage, identify overstock, or adjust procurement to eliminate unnecessary waste.

Safety and Security

Another key benefit of artificial intelligence is its ability to improve security for both customers and employees. This is especially true for organizations such as financial institutions or hospitals that constantly handle a tremendous amount of private data. AI can assist in fraud detection, identifying suspicious emails, and mitigating human errors that can result in data breaches or other liabilities. The high level of accuracy AI achieves ensures that fewer oversights or potential security concerns fall through the cracks unnoticed, making an organization much more resilient against bad actors such as scammers or cybercriminals.

Explore the Future of AI

As the field of artificial intelligence breaks new ground in the years ahead, organizations that fail to capitalize on the benefits it offers may find themselves left behind. To stay competitive, leaders and stakeholders should take the time to invest in exploring the many uses of AI and endeavor to stay up to date on new developments as they arise. Considering the many benefits artificial intelligence offers in terms of efficiency, accuracy, and workflow optimization, it’s only a matter of time before AI becomes the norm instead of the exception.

At Consensus Cloud Solutions, our goal is to empower organizations to navigate the digital transformation currently taking place by providing trusted and secure AI-powered solutions to meet all their changing needs. From offering natural language processing for more efficient data extraction to robotic process automation and workflow enhancement, we aim to provide top-tier enterprise solutions supported by today’s most cutting-edge artificial intelligence systems. Learn more about how to leverage AI for your organization today.