Understanding AI: How Artificial Intelligence Works

Artificial Intelligence
Understanding AI: How Artificial Intelligence Works
Last Updated: May 16, 2024

Imagine unlocking the full potential of artificial intelligence (AI) in your field. For those in the corporate world, did you know that 79% of strategists consider AI essential for success in the coming years? This statistic isn’t just impressive — it’s a wake-up call.

As technology evolves, understanding how artificial intelligence works becomes crucial for everyone, from tech advisors to decision-makers. Now is the time to discover how the power of AI can change your organization for the better.

Understanding How Artificial Intelligence Works

Artificial intelligence works by processing large amounts of information through complex algorithms. It processes data to make decisions, recognize patterns, and solve problems.

At its core, AI relies on two main components: data and algorithms. These are the steps that will help you understand how AI works:

  1. Data collection: These systems begin by gathering training data. This could be anything from images and text to numbers and sounds. For example, AI can go through thousands of voice recordings to understand human speech.
  2. Data processing: After collecting information, AI starts processing and organizing it into sets. This step is important to prepare the data for analysis. It usually involves removing inconsistencies and irrelevant information.
  3. Algorithm training: With the data ready, AI uses algorithms to learn from it. Think of algorithms as instructions that AI follows to interpret the data.
  4. Pattern recognition: The AI system looks for patterns it can use as it processes information. These patterns could be anything from common email spam characteristics to recognizing the faces of individuals in photos.
  5. Decision making: Finally, AI uses the insights gained from data analysis to make decisions. This can range from predicting what you might want to watch next on a streaming service to suggesting the fastest route home based on current traffic conditions.

By repeating these steps, AI becomes better at making predictions and understanding complex patterns. The method with which AI works shows just how powerful it can be in combining large datasets with dynamic algorithms.

This combination now enables machines to perform tasks that once required human input.

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How AI Works: Real-World Applications

Not so long ago, artificial intelligence used to be just a buzzword. Today, the different types of AI have become a powerful force that’s reshaping almost every industry across the globe.

The following are some real-world applications of AI that showcase its transformative potential:

AI in Healthcare

Artificial intelligence is revolutionizing healthcare by providing unmatched efficiency and precision in diagnosing diseases. One example is the use of a deep learning algorithm that analyzes magnetic resonance imaging (MRI) of the brain in children.

A study revealed an impressive positive predictive value of 81% when diagnosing autism in high-risk individuals by the age of 24 months. Such AI applications can speed up the diagnosis process, allowing for early intervention.

Besides diagnostics, AI in healthcare is streamlining patient data management, personalizing treatment plans, and even assisting in surgical procedures. These changes all make healthcare more accurate and personalized than ever.

AI in Customer Service

AI is a game-changer in customer service, particularly in the eCommerce sector. AI-powered chatbots and virtual assistants are now the first point of contact for many customers shopping online. They provide instant responses to inquiries, guide users through purchasing, and offer personalized shopping advice based on consumer behavior and preferences.

This level of interaction enhances the customer experience and reduces the workload on human employees. AI in eCommerce allows merchants to focus on more pressing issues since they can delegate bots to handle basic customer service.

The efficiency and scalability of AI in customer service have led to improvements in customer satisfaction rates for many businesses.

AI in Autonomous Vehicles

AI in Autonomous Vehicles

The advent of AI has significantly propelled the development of autonomous vehicles. In 2019, around 31 million cars worldwide had at least some form of automation. This number showcases the rapidly growing trust and reliance on artificial intelligence to make vehicles safer, more efficient, and more autonomous.

These vehicles use AI to process data from sensors and cameras in real time. The technology allows them to understand their environment, navigate roads, avoid obstacles, and make split-second decisions.

Each year, AI-powered cars make big strides toward becoming commonplace on our roads. This exciting progress hints at a future where driving relies much more on smart technology and much less on human input.

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AI in Web Design

AI is starting to transform web design by making it more accessible and efficient than ever before. One standout example is Wix’s ADI (Artificial Design Intelligence).

This tool enables users to automate the design process by asking a few questions about their preferences and the purpose of their site. ADI can then craft a more personalized website in minutes.

Adobe’s Sensei is another innovative tool that uses AI. It does this by offering design suggestions and analyzing the performance of design elements.

These tools are just a few examples of how artificial intelligence in web design can assist in creating custom and intuitive websites.

Main Types of Artificial Intelligence

AI technology’s potential appears limitless, providing users with a wide range of capabilities. Let’s take a look at the three main types of artificial intelligence below:

  • Reactive machines: These AI systems focus on specific tasks and do not store memories or past experiences for future actions. ATMs are a good example of reactive machines as they process user inputs without retaining personal usage history to influence transactions.
  • Limited memory: This type of AI can examine past data. Self-driving cars use it to make immediate decisions based on the data gathered, such as the speed and direction of other vehicles.
  • Theory of mind: Although still in its conceptual phase, this type of AI aims to understand and interpret human emotions, beliefs, and thoughts to interact socially. Its existence would represent a significant advancement in making machines more relatable and effective in human interaction. However, no fully operational example exists yet.

Different Fields of Artificial Intelligence

Various fields are shaping the future of artificial intelligence and our interactions with it. Below are the six main fields currently having the most significant impact.

Machine Learning

Machine learning (ML) is the leading field in artificial intelligence. This approach allows computers to analyze data and make decisions based on what was learned.

Unlike traditional programming, which follows explicit instructions, machine learning algorithms improve automatically through experience. This field powers everything from Netflix’s recommendation algorithms to Google’s search engine.

Machine learning companies develop systems that can predict outcomes by analyzing data patterns, resulting in smarter and more user-friendly services.

Natural Language Processing

Natural Language Processing, commonly known as NLP, bridges the gap between humans and machines. It allows computers to grasp and produce human language.

This is the same technology that powers well-known voice assistants like Siri and Alexa. It’s also present in customer support chatbots and translation services like Google Translate.

NLP makes it easier for people to interact with technology seamlessly through natural language.


Robotics combines artificial intelligence with mechanical engineering to create machines capable of performing tasks autonomously or with minimal human intervention. This field enhances efficiency and safety across various industries, from manufacturing robots that assemble cars with precision to surgical robots that perform complex operations with high accuracy.

Moreover, robotics has started to enter our homes, with robots for cleaning, entertainment, and even companionship.

Neural Networks

Neural networks take inspiration from the human brain’s structure and functioning. They’re essentially algorithms designed to recognize patterns. Such systems interpret sensory data through a kind of machine perception, labeling, or clustering of raw input.

The patterns they identify are numerical and contained in vectors. A well-known application is handwriting recognition, where the network learns to classify handwritten characters into standard characters. Voice assistants also use neural networks to understand spoken commands.

Deep Learning

Deep learning uses sections of neural networks to analyze various data input factors. The term “deep” in deep learning references the number of layers through which it processes data.

More layers allow for more complex features to be acquired and learned. This ability makes deep learning particularly useful for tasks involving large data.

For instance, deep learning is the mechanism AI development agencies use to power real-time language translation apps. It’s also used in autonomous vehicles that interpret the visual world around them to navigate safely.

Computer Vision

Computer Vision is all about enabling machines to see and interpret the world as humans do, but with a twist. It involves acquiring and understanding digital images and extracting in-depth data from the real world to produce numerical or symbolic information.

This field powers face recognition technologies found in security systems and smartphones. It’s also behind medical imaging advancements that help doctors diagnose diseases by automatically analyzing X-ray or MRI scans.

In retail, stores are using computer vision to improve shopping experiences by providing a cashier-less checkout process.

What Is the Future of AI?

The horizon of AI technology paints an exciting picture of innovation and transformation. Here’s a snapshot of what we can anticipate:

  • Generative AI adoption: A whopping 89% of AI decision-makers indicate their organizations are diving into the world of generative AI (GenAI). That will allow marketers to craft effective and highly personalized business strategies as AI marketing becomes more prevalent.
  • Ethical AI practices: As AI technologies become ingrained in our lives, ethical considerations grow in importance. Issues like data privacy, algorithmic bias, and the societal impact of automation are at the forefront of discussions.
  • AI in daily life: From smart homes that adapt to our needs to personalized healthcare based on our genetic profiles, AI is set to transform our daily routines. These innovations promise to make life more convenient, safer, and more tailored to individual preferences.


Embracing AI’s potential is no longer a futuristic idea but an urgent necessity. For many, understanding how artificial intelligence works is vital, whether you’re a tech advisor or a key decision-maker in your organization.

Now is an excellent time to adapt to the power of AI and secure a competitive edge in your market.

How AI Works FAQs

How does AI get smarter?

AI becomes smarter by learning from existing data. It uses algorithms to analyze patterns, make predictions, and improve its performance over time. The more data it processes, the better it understands complex tasks.

Can AI solve any problem?

No, AI can’t solve every problem. Artificial intelligence may have many capabilities, but it has its limits. AI shines in identifying patterns, analyzing data, and streamlining menial tasks. However, it struggles with problems that require emotional insight or creative thinking.

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