From Security to Personalization_ AI Face Recognition Use Cases for 2024

From Security to Personalization: AI Face Recognition Use Cases for 2024

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Facial recognition technology was a product of fiction for most people just about 20 years ago. However, it’s not new – the first solution was made around the 60s. 

What started as a technology that recognized faces from newspapers and drawings evolved into today’s greatest surveillance and personalization tool. At this point, facial recognition is widely implemented by different companies and startups.

But what if you’ve just started looking into implementing this tool? Is it even worth it? Let’s dive into market stats first.

AI Facial Recognition: Market Statistics

You’ve probably heard about facial recognition and its uses before, and it’s no wonder. Based on Statista’s data, the world market for biometrics verification and identification was 33.26 billion USD in 2019.

With this tendency having no signs of stopping, experts forecast this market to reach 99.63 billion USD by 2027. The niche is likely to grow three times in less than a decade! 

Biometric authentication and identification market revenue

It’s hard to believe that machines can actually recognize faces accurately. Let’s talk about research around this topic. 

A couple of years ago, the National Institute of Standards and Technology (NIST) published FRVT, also known as the Facial Recognition Vendor Test. Based on algorithms developed for academic and commercial use, it helps determine the accuracy of current facial recognition tools. 

Find more exciting use cases in our article about computer vision Read more

Recent results showed that facial recognition technology can reach accuracy scores of up to 99.97% in ideal conditions. High accuracy and reliability are the main reasons why the face recognition market is growing so fast.

Think about how much value this technology could bring to your business. As a leading computer vision development company, we can help you develop and adapt facial recognition for your specific needs – leave your request in this form, and we will reach out to you the same day. 

Insights from Our Practice: Face Analysis for Photography Services

Photographers usually take thousands of pictures during events, parties, or other festive celebrations. But how can you quickly find a photo of a specific person in a huge pool of content?

This is the exact issue our Japanese client wanted to address. Their company provides photo services at schools, kindergartens, camps, and various children’s events. Finding a child in these photos is a real challenge. But innovations can help. 

This is where the idea of the face recognition app came from, and this is how it works from the user’s perspective:

  1. Photographers take pictures and upload photos into the system;
  2. Parents log in to select photos of their children;
  3. Upon request, the system returns the results of all found and recognized faces.

Face recognition and analysis application by CHI Software

And so we got to work. After conducting a study to improve face recognition accuracy, we had to do the following steps:

  • Set up a cloud environment for development and product hosting;
  • Improve the accuracy of rolled and rotated face recognition (by 45-90 degrees), background recognition, and extremely small/big face detection;
  • Automate monitoring, analytical, and comparative manual processes. 

After integrating these AI features, we are still providing the app with support and updates. Click here to learn more about the technologies we used and our team’s experience working on this project.

Not sure that facial recognition is what you need? Let's find out together! Contact the CHI team

Facial Recognition Technology: Uses in Industries

Numerous industries have already adopted facial recognition, but how exactly does it help? This section will cover the biggest industries that have benefited from this technology, starting with healthcare. 

Industries that use facial recognition


After implementing facial biometrics in healthcare systems, check-ins have become much easier and faster. By analyzing a patient’s face, the system can get all the needed information such as medical history or insurance. It helps to speed up the admission process and can match a person with the list of patients. 

Face recognition can also detect rare disorders and monitor the patient’s mental state, applying facial emotion detection. In the future, we’ll see even more implementations, for example, measuring the patient’s heart rate just by looking at the camera. 


Facial identification is becoming an indispensable part of the next generation of cars. It tackles some security issues and elevates the ride experience of the driver and passengers.

Genesis car facial recognition

Car facial recognition by Genesis

For example, Genesis, a Korean automotive brand, introduced a car entry with face recognition a couple of years ago. This allows owners to access their vehicles without keys by scanning their faces.

At the same time, Hyundai launched a facial recognition system to adjust seats, displays, and side mirrors for a certain driver by recognizing their face.

The Future in Focus: Image Recognition Trends and Applications for 2024 Read more


Some college campuses and universities have implemented face detection as well. The idea is to check classroom attendance and optimize dorm security.

Such software takes photos of a classroom and checks for students’ faces. Then, it compares the list of students in the classroom to the list of students that are supposed to be there. It is also used as a security measure on campuses by the same principle. 


Facial recognition technology is almost everywhere since finance is one of the most security-driven sectors. For example, banks use facial authentication. You probably already encountered this when you wanted to open a bank account, and the clerk asked you to move your head in different directions in front of the camera. After that, you can magically log into your banking app using solely your face ID. 

A woman uses an ATM with facial recognition technology during the presentation of the new service by CaixaBank

An ATM with facial recognition technology by CaixaBank

The technology used by banks is more meticulous compared to regular facial recognition. Instead of just taking a picture of your face to store in a database for future comparison, they also compare it to your picture on documents. This helps prevent identity theft, financial fraud, or money laundering,


It comes as no surprise that the security sector has been using facial recognition for some time already. It helps find missing people, monitor large crowds, and even solve crimes, for example, by identifying a suspect. 

However, the use of face verification for security purposes is a controversial topic in public. The concerns are in the algorithm’s reliability and how its dataset was created. 

The two aspects affect how innovations perform with low-quality photos or people of color, possibly leading to bias in the system. Some countries have already paid special attention to these concerns and have started governing this technology at the state level.


While it is new for Western countries, a lot of countries in the Asian region have already implemented payments powered by face recognition. And soon, you might be able to pay for everything the same way at checkouts, even on public transport.

A woman uses a facial recognition device at an IFuree Go self-service supermarket

A facial recognition device at an IFuree Go self-service supermarket

It works by associating a customer’s photo with their wallet. Thanks to this, self-checkout machines can extract payments without needing cash or a card. This might sound futuristic, but in reality, a Chinese company Alipay already launched the “Smile-to-Pay” system.


Facial recognition is a potent tool. By implementing it correctly, you can eliminate small inconveniences that take a lot of time, effectively enhancing user experience. 

Even though the discussion around the ethics of facial recognition is still in progress, the technology showed a lot of value for industries that adopted it, such as healthcare, automotive, education, finance, security, and retail. 

Nevertheless, facial recognition development could be a tricky process for any business. We at CHI Software specialize in such solutions and can help your development at any stage! Leave us a message in the contact form, and we’ll get back to you within one workday.


  • How is AI face recognition different from traditional facial recognition methods? arrow

    AI face recognition offers higher accuracy and better adapts to non-conventional photos (e.g., low-quality or blurry images) compared to traditional methods that rely on manual feature selection.

  • What are the primary benefits of AI face recognition for businesses? arrow

    Better security, faster customer service, and accessibility are the primary business benefits of AI face recognition. Not to mention the personalized service each customer can get by just scanning their face.

  • What industries are leveraging AI face recognition technology? arrow

    Security, financial, and retail industries are leveraging face analysis the most nowadays. But recently, we started to see this technology used more in other fields, like education, automotive, and healthcare.

  • What is facial recognition mostly used for? arrow

    Facial identification is the most popular use case. By scanning a face and comparing it to existing faces in the database, you can enhance security or find information about a person. However, biometrical payments that use face recognition come second because of how widespread this technology has become in recent years.

  • What is the future of AI facial recognition? arrow

    We are expecting advancements in accuracy and more efforts to address ethical and privacy concerns by improving regulations. We also can expect more industries to start using AI face recognition for their needs.

About the author
Alex Shatalov Data Scientist & ML Engineer

Alex is a Data Scientist & ML Engineer with an NLP specialization. He is passionate about AI-related technologies, fond of science, and participated in many international scientific conferences.

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