Top AI Applications Transforming Our World

Here are some of the most common examples of AI applications being used today. 
 

Generative AI and large language models (LLMs)

By now, most people are familiar with generative AI in the form of ChatGPT, Gemini, Copilot and so on. Generative AI is a broad term for AI that can create original content, including text, visuals, video and audio outputs, while large language models can only create text outputs. All LLMs are a form of generative AI, but not all generative AI tools are built on LLMs. 

LLMs are used for text-based tasks such as chatbots, virtual assistants, language translation and reporting. Generative AI models can be used to perform similar tasks, as well as more creative uses such as targeted advertising content, virtual product try-ons, music composition and more.
 

Recommendation engines

Recommendation engines are AI systems that utilize big data analytics and machine learning to analyze patterns in behavior data and make relevant recommendations based on those patterns. Search engines, ecommerce sites, social media networks and streaming platforms use them widely to recommend content, products or services to users based on their buying or browsing behavior — so next time you spot that “Because you watched” or “Customers also bought” phrasing in an app or interface, recommendation engines are likely part of that experience. 
 

Computer vision systems

Computer vision is a form of AI that uses machine learning and neural networks to teach computers how to see, observe and understand in the way that human vision does. Instead of retinas and a visual cortex, computer vision uses cameras, data and algorithms to process information. It is widely used in manufacturing to find imperceptible issues or defects with products. 
 

Natural language processing (NLP) and virtual assistants

NLP is AI that uses machine learning to enable computers to communicate and understand in human language. NLP is already widely used for customer service chatbots, voice-activated GPS systems and question-answering virtual assistants such as Amazon’s Alexa. Enterprises can use NLP to streamline operations and simplify processes by automating repetitive tasks and improving data analysis.
 

Predictive analytics in business

Predictive AI employs statistical analysis and machine learning to recognize patterns and predict the future. With predictive AI, organizations can analyze large amounts of data quickly to figure out potential hiccups or risks to the business. For example, teams may be able to use it to forecast future supply chain disruptions or predict potential mechanical failures, allowing them to plan accordingly.

AI applications are being used to streamline operations and foster innovation across a wide variety of industries. Here are some examples of how various sectors are using artificial intelligence today. 
 

Healthcare

The healthcare industry is using AI applications for everything from administrative tasks to medical diagnoses and treatment. AI systems built with NLP are being used to extract information from unstructured medical records for more efficient billing, coding and data management. In addition to using AI tools to take notes during appointments, doctors are using AI systems to analyze patient data to create personalized treatment plans. 

AI is also being used to speed up the development of new drugs. For example, researchers from Massachusetts Institute of Technology recently used AI to help design antibiotics that can kill drug-resistant MRSA. Though efforts like these still require plenty of human expertise and training, with artificial intelligence, researchers can analyze vast amounts of medical and scientific data quickly and efficiently to accelerate the process of discovering new, potentially life-saving treatments.
 

Advertising

Artificial intelligence is transforming every aspect of advertising, from personalization to performance analysis to delivery optimization. With AI, marketers can analyze customer data and behaviors to create hyper-targeted ads designed to increase engagement and conversion rates. AI tools can also be used to determine optimal times, channels and formats for ad delivery to maximize campaign ROI.
 

Financial services

The financial services sector is currently using AI for fraud detection, risk management, compliance activities, the creation of personalized products and services, document automation and more.

With AI, financial services organizations can more accurately monitor for fraudulent transactions and quickly act upon them when detected. AI tools also automate financial workflows, reducing manual errors in tasks such as data processing, document processing and analytics.
 

Gaming

The gaming industry has used some form of artificial intelligence for years to create scripts and images, as well as new levels and maps in real time. AI is also used to analyze the difficulty of a game to keep players engaged. Some companies are using AI as a tool to generate more personalized gaming experiences. For example, one game uses biofeedback with AI-driven devices to measure users’ physiological responses — such as stress or excitement — to adjust the experience of the gameplay itself. 
 

Retail and commerce

AI has transformed the retail and ecommerce space by enhancing the customer experience and improving operations. In addition to customer service chatbots, recommendation engines monitor and analyze customer behavior, steering shoppers toward relevant products they may not have seen, increasing sales potential (and, hopefully, utility for the customers themselves). 

Dynamic pricing is also on the rise. Using AI and machine learning, retailers can optimize pricing in real time based on market demand and competitor activity to optimize revenue.
 

Manufacturing

Artificial intelligence is a key driver behind the fourth industrial revolution, our current era of smart manufacturing. AI technologies like NLP, machine learning and computer vision are being used to improve nearly every aspect of manufacturing including better energy efficiency, enhanced predictive maintenance, improved supply chain management and the ability to offer custom manufacturing services.

Using AI-driven automation, quality control and predictive analysis, manufacturers can speed up production and optimize workflows while reducing human error as well as labor and maintenance costs. AI tools also give manufacturers a competitive edge by allowing them to innovate faster and more efficiently as they respond to evolving market demands. 
 

Education

As educators are increasingly tasked with doing more for less, AI is becoming an invaluable tool inside and outside the classroom. Teachers are using AI tools to streamline lesson plans, create content and grade assignments, which means less time spent on administrative tasks and more time spent on educating.

AI is also facilitating more individualized learning. Without increasing their workload, teachers can develop AI-generated content that is tailored to a student’s individual needs, allowing them to progress at their own pace with activities that align with their learning style. 
 

Customer service

Customer service can make or break customer loyalty. With AI, businesses can analyze customer behavior in real time, anticipate their needs and resolve issues quickly and efficiently. AI also allows for the 24/7 availability of customer service without the need for costly staffing and facilities.

And though chatbots have been the norm for years, AI is now evolving beyond basic support scripts. Today, advanced generative models use sentiment analysis technology to interpret the tone and emotion of a customer’s message, letting the business respond more quickly to unhappy customers with the appropriate care.