What Is Artificial Intelligence (AI) Technology and How Is It Used?

Artificial intelligence, or AI, is everywhere—from the headlines we read to the industries we work in. It’s shaping job markets and redefining how businesses operate. Often discussed alongside machine learning, deep learning, and big data, AI and AI systems go beyond computing applications alone.

Although images of robots and futuristic gadgets may come to mind, AI is more than a buzzword. So, what exactly is AI, and how is it transforming the way we live and work? Read on to explore what artificial intelligence is, how it’s used, and what the future may hold.

What Is Artificial Intelligence?

AI empowers machines to reason, learn, and perform tasks—often with minimal human oversight. It enables computers to process complex functions once thought exclusive to humans, like visual recognition, language understanding, and data-based decision-making. The ways that AI can be used are myriad, from automating repetitive tasks and personalizing mobile app experiences to creating virtual assistants and facilitating smart home ecosystems.

Artificial intelligence was conceptualized in June 1956, when a group of scientists and mathematicians met at Dartmouth College to discuss the idea of a computer that could think. They didn’t know what to call it or how it would work, but their conversations there created the spark that ignited artificial intelligence. Since that “Dartmouth workshop,” as it has come to be called, there have been both highs and lows throughout the development of AI technology. For some years, progress on developing intelligent computers stalled, but recent advancements have reignited the field and integrated AI technology into many people’s daily lives.

How Does Artificial Intelligence Differ from Human Intelligence?

Artificial intelligence and its underlying algorithms are designed by humans, and while an AI system can learn, adapt, or grow from its surroundings, it still has clear limitations. Compared to AI, human intelligence has a far greater capacity for multitasking, memory, social interaction, and self-awareness. Artificial intelligence doesn’t have an I.Q., making it very different from human intelligence.

There are many facets of human thought and decision-making that artificial intelligence simply cannot master. For instance, processing feelings or nurturing relationships is beyond the capabilities of machines, no matter how useful they might otherwise be. Cognitive learning and machine learning will always be distinct. Essentially, human thought encompasses much more than a machine could ever be taught or equipped for.

Although AI can outperform humans in narrow tasks like pattern recognition or data processing, it has no consciousness, intuition, or independent reasoning, which makes it fundamentally different from human intelligence. Today’s systems are considered “weak AI,” built for specific tasks, while the idea of “strong AI,” or machines with human-level reasoning and consciousness, remains purely theoretical.

While AI is powerful, it's a tool built within clear boundaries—not a human substitute.

How Does AI Work?

While it’s one thing to understand what AI is, it’s another to know how it actually works. AI operates by processing data through advanced algorithms. It combs large data sets with those algorithms, learning from the patterns or notable features in the data.

There are several theories and subfields within the broader field of AI, including:

• Machine learning. Machine learning often uses algorithms and, in some cases, neural networks to find hidden insights from data without being programmed for what to look for or what to conclude. Machine learning is a common way for AI systems to detect patterns and increase their intelligence over time.
• Deep learning. Deep learning utilizes large neural networks with many layers, taking advantage of their size to process huge amounts of data with complex patterns. Deep learning is an element of machine learning, but with larger data sets and more layers.
• Cognitive computing. Cognitive computing aims to mimic human interaction with machines. Think of robots that can see and hear and then respond as a human would.
• Computer vision. Computer vision uses pattern recognition and deep learning to understand an image or video. This means the machine can look around and take photos or videos in real time and interpret its surroundings.
• Natural language processing (NLP). NLP enables computers to comprehend, interpret, and respond to human language in a natural or conversational way. Common tasks performed by NLP tools include speech recognition, language translation, and chatbot services. Generative AI tools like ChatGPT, Gemini, and Copilot use NLP to create new content based on user prompts.

How Is AI Used?

Artificial intelligence is being used in hundreds—if not thousands—of ways around the world. Examples of its uses include the following:

• Voice recognition. Many people call out for Siri when they need directions or ask Alexa when they need to set a timer. This technology is a form of AI that uses machine learning to turn sound waves into text. A decoder blends the speech model’s sound-based probabilities with a language model’s expectations about words to pick the most likely wording, which then feeds systems that understand intent, verify speakers, and protect privacy. 
• Self-driving cars. ML models power self-driving vehicles from seeing to steering. Perception ML models turn camera, radar, and lidar data into detections of lanes, signs, lights, and road users. Sensor data is fused, and localization uses it to keep the car’s precise position on the map. Prediction ML models anticipate what others will do next, and planning/control select and execute safe trajectories in real time. Systems learn from large-scale driving data and simulation to handle varied traffic, weather, and lighting. 
• Chatbots. Many organizations use artificial intelligence to augment their customer service teams. For example, chatbots can interact with customers and answer general questions, freeing up time for real customer service agents. Chatbots learn information from users to produce helpful, relevant output. Sometimes, certain words or phrases entered into a chatbot may trigger specific responses. This AI-powered tool can offer a humanlike level of interaction for customers.
• Online shopping. Online shopping systems use AI—especially machine learning—to learn about your preferences and predict products you’ll be most interested in. Amazon and other retailers continually refine these AI systems to tailor recommendations, search results, and deals to each user, making online shopping more convenient and relevant.
• Streaming services. Streaming services use AI behind the scenes when you watch shows or listen to music. Netflix, Hulu, Spotify, and others analyze your viewing/listening history and patterns to suggest what you might enjoy next, helping you discover new content more easily.
• Healthcare technology. Artificial intelligence plays an important role in healthcare technology to help diagnose diseases, develop medicine, monitor patients, and more. AI technology can actively learn about patient needs to improve its usefulness as time goes on.
• Factory and warehouse systems. Shipping and retail industries have fundamentally changed thanks to dedicated forms of AI software. Computer systems that automate entire shipping processes (and adapt as needed) improve the speed and efficiency of manufacturing and supply chains. These systems can also help maintain safe working conditions.
• Educational tools. AI tools—such as plagiarism detectors, citation helpers, tutoring chatbots, and adaptive learning apps—can support teaching and learning when used with clear guidelines and humans review the results. Teachers can offload routine tasks like drafting quizzes, giving formative feedback, and triaging short-answer grading, freeing time for lesson planning and individual support. Students get practice sets, instant hints, and language help that adjust to their progress.  

What Is the Future of AI?

AI systems are already impacting how people live, and the door to the future is wide open for how it might impact society. AI-driven technology will likely continue improving efficiency, boosting productivity, and expanding into more industries. Though the future of AI is promising, there will likely be more discussions on data privacy, security, and continued software development to help keep individuals and businesses safe as AI advances.

While some people worry that AI could take their jobs, it is more likely that AI will change how they do their jobs. In fact, all sectors of the economy show an increase in their demand for AI skills. (The Fearless Future: 2025 Global AI Jobs Barometer - US Analysis). Whether learning new AI tools or building AI systems, workers who develop AI skills have more control over their future in the changing workforce landscape. They are preparing themselves for whatever comes next. There is even evidence that wages of workers with AI skills are higher than those without. (AI Jobs Barometer | PwC).

The exciting news is that we are still in the early stages of this change, giving those who have yet to invest in their AI skill preparation a wonderful opportunity to get started. A recent article from the Federal Reserve indicates that AI adoption rates by companies range from 5 to 40%. (The Fed - Measuring AI Uptake in the Workplace). This means most companies have yet to fully embrace AI. There still is time to get started. 

This lower adoption rate also helps frame current economic conditions. While AI job disruption explains some of the impact to the job market, the lower adoption rate indicates other economic forces are playing a more significant role. In fact, the Bureau of Labor Statistics is projecting exceptionally strong growth in high AI-exposure occupations over the next several years because of AI (Incorporating AI impacts in BLS employment projections: occupational case studies : Monthly Labor Review : U.S. Bureau of Labor Statistics). This means that jobs such as software and data engineering, while currently experiencing higher disruption and slower job growth, (The Fearless Future: 2025 Global AI Jobs Barometer - US Analysis), are strong career choices for the future. 

As artificial intelligence reshapes industries and creates new career possibilities, there has never been a better time to build your expertise. At WGU, degree programs like the M.S. in Software Engineering – AI Engineering and the M.S. in Computer Science – Artificial Intelligence and Machine Learning are designed to help you master emerging technologies and lead innovation. By earning a flexible, online IT degree at WGU, you’ll gain the modern skills and practical experience needed to launch or advance an exciting career in AI and position yourself at the forefront of this world-changing revolution.

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