AI Use Cases: The Limitless Roles of Artificial Intelligence

In this day and age, the rapid development of artificial intelligence (AI) has been a game-changer across multiple industries and sectors. With its ability to process vast amounts of information, learn from patterns, and make informed decisions, AI has changed how we do things forever.

In this article, we will look into all the incredible ways in which AI is used to make our jobs faster, more accurate, and overall much easier. 


Let’s start in the transportation industry, where many AI use cases can be found to make our traveling smarter, more efficient, and safer.

Here are some of the most pivotable ways AI is used within the transportation industry.

Automated vehicles

Automated vehicles sound futuristic but have been around since 1925 when Francis Houdina showcased his full-size, remote control car in Manhattan. The engine could start, the gears could shift, and the horn could sound remotely. 

First ever radio controlled car.


Sure, it crashed a few times, and the control wasn’t perfect, but it was the first look at automated vehicles, something that was barely considered beforehand.

Now, things are much more polished due to the advancement of AI technology. We no longer have to control vehicles via a remote; AI knows exactly what to do. 

With cameras and radar sensors, automated vehicles today can use computer vision to recognize objects around them, such as lampposts, pedestrians, and other cars. It also allows them to adapt to changes on the road, like around construction or in bad weather.

Many self-driving vehicles on the market today use AI for safe, autonomous driving. Here are some of the most popular ones:

  • Tesla Autopilot: Tesla is one of the pioneers behind autonomous vehicles; they offer features such as cruise control, automatic lane changing, and park assist.
  • Navya: A French company specializing in autonomous vehicles, their most notable one is a driverless, electric shuttle bus for public transportation. 
  • Waymo: Waymo has been working hard on self-driving taxis since 2009. They use machine learning to give their cars the ability to judge their route and the intent of other drivers on the road. 

Traffic management

There’s nothing worse than sitting in traffic after a long day at the office. AI can be used to regulate and control the flow of vehicles to prevent blockages and accidents.

Real-time traffic congestion and patterns are analyzed with AI algorithms to collect data to recommend drivers’ alternate routes. As well as this, AI in traffic management can predict traffic before it’s even happening and use it to optimize traffic light timings at intersections. 

With all of this useful data, our traffic flows, stop lights don’t cause needless waiting, and people get home to their families sooner. With all of this combined, overall road safety is improved as drivers don’t get defensive and reckless trying to get from A to B.

Accident prevention

In 2021, over 42,000 Americans died due to road accidents. This is an increase of over 10% since 2020. Driving over the speed limit and not wearing seatbelts are the two main factors contributing to fatal accidents. 

What can AI do to help decrease fatalities on the road? Patterns of unsafe driving behavior and real-time warnings of nearby accidents help identify potential risks and prevent incidents.

Signs of fatigue, distraction, or intoxication can be identified with systems that look out for nodding, yawning, and other erratic physical movements. If the driver seems unfit to drive and a risk to others, then the AI will use loud noises to wake them up and advise them to pull over.

AI fatigue system analyzing a driver.



Farming has long been back-breaking work, but with the introduction of AI, it is becoming more efficient and profitable.

Pest and disease control

Pests and diseases can wipe out full fields of animals and crops in no time. AI systems such as Agrio can identify, monitor, and prevent this damage by giving farmers advanced warnings. 

Algorithms are also used to analyze data from various sources concerning agriculture’s welfare, including weather data, satellite imagery, and plant health sensors.

This helps detect pests, diseases, and detrimental weather early and provides timely recommendations to decrease the negative impact. Areas in which AI can save a farmer’s livelihood are outbreaks, pesticide use optimization, and overall crop health.

Farm management systems

AI farm management systems use sensors, drones, and other Internet of Things (IoT) devices to gather real-time information on:

  • Crop health
  • Weather patterns
  • Livestock behavior
  • Soil conditions
  • Water usage

This data gives farmers a much deeper insight into the condition of their farms and how best to prepare for natural disasters. Machine learning algorithms analyze historical data as well as current data to provide decisions based on cold, hard facts. This reduces a lot of risks that come naturally to this industry.

An example of a farm management system.


With the use of AI, farm management systems make agriculture more efficient, reduce costs, and increase production. 

Automated harvesting

Machines and AI are used in agriculture to automate gathering crops by deciphering ripeness and maturity, ensuring that each and every crop is harvested right on time.

AI-powered robotic systems with cutting tools and grippers harvest the crops in less time than a human or old tractor would. With computer vision, these machines know where the crops are and navigate the fields without causing damage to get to them. 

Reduced labor and time are two huge benefits of automated harvesting, as well as the peace of mind that all crops are perfectly ripe and high-quality for selling.


In the modern age, education is becoming much more accessible, immersive, and personalized, creating an even playing ground for all learners to get where they want to go. This has all been possible with AI-powered tools.

Personalized teaching

Personalized teaching is when learning plans, instructions, and experiences are tailored to accommodate students’ needs and abilities. With AI, performance records, learning styles, and interests are used to determine the best path to success. 

Graph as to how personalized teaching works. It breaks off into two branches:1. Student classification to Hierarchical clustering that goes into student analysis, teaching content, and teaching evaluation.2. Personalized course recommendation to artificial intelligence recommendation


AI systems used in education also can collect data from students and use it to alter the learning route for them to follow as they go. This adaptive, flexible learning allows teachers to identify the strengths and weaknesses of those they teach in a more black-and-white way. This helps save time originally spent on guesswork.

An example of this kind of AI technology in education is Century Tech. This app combines learning science and neuroscience to create the best learning plan for each student.

Administrative automation

When it comes to education, there are numerous administrative tasks that need to be done every day, including student records, employee information, and more. With AI, these boring, time-consuming tasks are given to automation programs so that human employees can focus on other areas. 

By using AI, not only are you alleviating repetitive tasks but also guaranteeing accurate, efficient results. Student enrollment, scheduling, and data management consist of large amounts of data, which not all humans are good at (or enjoy). 

On the other hand, AI is a pro at analyzing, processing, and learning from big data, which gives it the ability to get better and better at its given job.

Regarding admin tasks, generative AI, such as ChatGPT is typically used to help fill in forms or reports that don’t require a personal touch. 

Student assessment

AI assesses students by analyzing their work and providing thorough feedback. It helps simplify the grading process and alleviate errors. AI can evaluate quizzes, assignments, and even exams if trained on specific parameters. 

As well as this, AI can detect patterns in student responses to see their strengths and what needs improvement. Unfortunately, some teachers can be biased and inconsistent in their grading, but using AI keeps it straightforward, giving each student a fair evaluation.


Sustainability is a growing focus as our world increases to show signs of climate change. By using AI, organizations can find innovative ways to address these challenges.

Waste management

We are creating more single-use plastic waste than ever before and if we don’t do something about it, it will only increase. 

Artificial intelligence has all the tools necessary to help optimize our waste management processes by predicting waste generation levels and determining the best way to collect, recycle, or dispose of it. With AI, waste management systems can reduce pricing, minimize environmental impact, and improve resources through data analysis.

Greyparrot AI is one of the leading technologies behind this optimization. They use computer vision to find material on a waste disposal conveyor belt that is suitable for recycling. Humans are already doing this but at a fraction of the speed and accuracy of this application of AI.

Greyparrot AI working in a waste management conveyor belt.


Energy optimization

We need to make our energy count, and AI is the way to do it. By analyzing energy usage patterns and energy wastage, users get insight into how they can change their behavior to save power. AI such as this is used by Amazon to predict demand to minimize waste and increased costs. 

Residential energy contributes about 20% of greenhouse gas each year. AI has many tricks up its sleeve which can help homes save energy and minimize their contribution to climate change. 

AI-powered energy monitoring systems and devices identify which areas of the household are wasting energy and how best to combat it. Personalized energy efficiency recommendations to homeowners can be given to suggest energy-saving appliances or usage habits.

Climate monitoring

AI is used to monitor and understand climate patterns with more accuracy. It involves looking at vast amounts of climate data from various sources, including satellites, weather forecasts, and previous records. 

This information contributes to predicting trends and anomalies, helping environmental scientists and researchers to better understand climate change and make informed decisions.

Climate monitoring systems have become better at predicting climate events, thus giving earlier warnings of dangerous natural disasters. Additionally, climate change as a whole is supported with large datasets to develop mitigation strategies and promote sustainable practices to fight the impacts.


With cybercrime getting more sophisticated, cybersecurity must be at least one step ahead at all times. Even though AI can be used for evil, it can also be used for good, and here are some examples of how cybersecurity has benefited from it.

Fraud detection and prevention

Cybersecurity in AI does wonders to keep individuals and organizations safe from cyber attacks. Machine learning and deep learning are used to find anomalies and irregular patterns that may pinpoint fraudulent behavior and transactions.

From phishing attempts to malware threats, AI takes no chances and, as it continues to develop, will get more advanced at spotting sneaky cyberattacks that would have otherwise gone undetected.

Thanks to AI, fraud detection becomes more accurate and reduces false alarms, which leads to undue panic and frantic password changes. What’s better is that AI is always learning, so it will continue to outpace the bad guys.

8 Benefits of using AI in Cybersecurity1. AI learns more over time2. Artificial intelligence identifies unknown threats3. AI can handle a lot of data4. Better vulnerability management5. Better overall security6. Accelerates detection & response times7. Duplicative process reduce8. Securing authentication


User authentication

As annoying as it can be when your login doesn’t work, one day, you’ll be grateful that your bank was so suspicious of you. With advanced AI technology and algorithms, the user’s identification is verified down to the last detail.

AI has gotten to know us so well that it can even analyze various factors such as mouse movements, typing patterns, and biometric data to ensure that only authorized users can access a device.

Security analytics

AI is used to analyze security data and identify potential threats by processing vast amounts of data and detecting suspicious activities.

Network logs, system logs, and other security data are used to learn from past incidents and adapt to new cyberattack methods. With machine learning and predictive modeling, AI can forecast potential threats and help with the best defense strategies.

Customer service

As customers, whether we realize it or not, we are talking to AI more than we are to humans online. The relationship between customer and business is changing, and that is down to virtual bots and increased accessibility. 

Let’s look at more detailed use cases of AI in customer service.

Chatbots and virtual assistants

AI is a fantastic tool for customer experience and makes life easier for all parties. It involves natural language processing (NLP) to fully comprehend the messages and inquiries sent to the company online and then send an appropriate, relevant reply. 

This saves a lot of time that would have been originally spent typing out the same reply or sorting through hundreds of emails. Now only the really complex cases require human intervention.

AI can assist with common queries like product information, order status, or troubleshooting. This enables these systems to learn from customer interactions, improving their responses over time. 

Chatbots and virtual assistants are available 24/7 with AI and will reply instantly. Moreover, AI doesn’t have to withstand the inevitable frustration or attitude from customers. With this, customer support gets faster, and companies save money on full-time telephone agents.

Chatbot Conversion StatisticsAverage chatbots generate 35-40% response ratesThe best bot experiences with more engages customers can generate up to 90% response ratesChatbot technology can increase website conversion rates on average by between 10-100% depending on the industry.Ecommerce stores adopted the social media Facebook Messenger chatbot to 25%Better bot experiences together with more engaged audiences are getting 80-90% response rates.Business leaders claim that, on average, chatbots have increased sales by 67%.57% of businesses say that chatbot delivers a massive ROI on minimal investment.


Speech to text

AI has made those with disabilities much more welcome as they navigate the digital landscape. With speech-to-text, spoken words are converted into written text instantly, improving communication and service quality.

Audio input is processed and then transcribed into written form, even if the user is mumbling or has a strong accent; AI has gotten so good that it will fill in the blanks and complete the sentence. 

With this technology, hard-of-hearing individuals can communicate better, and customer service agents can quickly review and respond to messages, ensuring prompt and accurate assistance. 

Personalized recommendations

Users like to feel listened to, and no one listens quite like AI. The online shopping experience can increase customer satisfaction and revenue by providing personalized recommendations, which is done by tracking customer data, behavior, purchase history, and browsing patterns to understand individual preferences. 

This information allows AI to generate personalized recommendations for products or services that match the customer’s interests. This helps customers discover relevant items and make informed purchase decisions. 

Manufacturing and robotics

AI is a connoisseur of automation and efficiency, making it perfect for manufacturing and robotics. By leveraging AI, factories and production lines are becoming more adaptive and efficient.

Quality control

Quality control has greatly improved since AI entered the scene with faster inspection speeds and lower costs, making manufacturers less likely to pack a dud and suffer the consequences later.

By analyzing visual data such as images and videos, AI tools can detect subtle flaws or inconsistencies that would have bypassed the human eye. With companies that have a reputation to withhold, this is vital as only the best; high-quality products will be given the green light.

A pharmaceutical company based in Switzerland called Lonza has benefited from using AI in its quality control to decrease manufacturing costs and improve decision-making.

All in all, quality control systems are more efficient, reduce errors and improve overall product quality with AI. This increases customer satisfaction, reduces waste, and streamlines manufacturing business processes.

Supply chain management

Even if the goods are top of the range with no flaws to be seen, it doesn’t mean much if they’re stuck at the factory. This is why supply chain optimization is so important; it must all run smoothly while adhering to a strict schedule. As you can imagine, this doesn’t leave much room for error.

However, AI models can predict demand, optimize inventory management, and automate resource administration. By taking care of these elements, the supply chain benefits from the following:

  • Reduced costs
  • Minimal delays
  • Waste reduction
  • Improved overall workflow

Human-machine interfaces (HMI)

We wouldn’t be able to communicate with machines if it weren’t for AI, especially advanced models that are more complex. There are three main types of HMI:

  1. The pushbutton replacer 
  2. The data handler
  3. The overseer.

HMIs involve robotic process automation and user-friendly, intuitive interfaces to understand human gestures, speech, and touch inputs. This makes communication more natural and accessible.

HMI robotic interface.


These AI applications enable operators to control and monitor machines with ease, making complex tasks easier and reducing the time it takes to train new employees on using such equipment. This improves productivity, reduces errors, and makes the overall user experience more streamlined.

Key takeaways

The expanding reach of AI solutions holds incredible potential to revolutionize multiple industries. From transportation and agriculture to education and cybersecurity, AI’s impact has changed our world for now and forever.

Keep in mind; these are just a fraction of the AI use cases currently out in the world. AI is also featured heavily throughout healthcare within medical imaging, financial services with e-commerce, and social media with predictive analytics.

Due to continuous innovation and integration in our day-to-day lives, it’s safe to say we would be lost without AI, and it makes us question how it will impact the same industries in the future. 

Were you aware of how many AI use cases there were? To learn more about what AI can do, head over to the Top Apps blog.