Facing the Future: Emerging AI Facial Recognition

Facial recognition technology is a rapidly growing multi-billion dollar industry. Estimates indicate that 74% of hoteliers expect widespread adoption of facial recognition and biometric technology in the hotel industry alone by 2025. This increase in adoption rates is attributed to more recent advances in artificial intelligence (IA) – because it has not always been feasible. for this technology to thrive in all industries.

Although the concept of facial recognition has been around for many years, it has taken time to gain widespread adoption due to reliability issues. Industries such as finance and security cannot afford the costly mistake of a facial recognition error. With new technologies like AI, opportunities have arisen to adopt facial recognition in a variety of different fields. Today, there are many success stories where AI has delivered reliable and accurate facial recognition technology. According to the National Institute of Standards and Technology (NIST), the best facial recognition technology had an error rate of just 0.08% in April 2020.

AI options for facial recognition

The rise of AI has been the catalyst for the growing variety of facial recognition tools. It is important to know the resources and understand what is available today. Some technologies can be quickly deployed without machine learning expertise, while others require deeper expertise and understanding of the technology. Additionally, price ranges can vary widely, from free solutions to more expensive options costing tens of thousands of dollars per year. The most popular include AWS Rekognition and Azure Facial Recognition services. These tools are easy to get started and integrate services that require payment for each recognition.

The downside of using cloud providers is that sensitive information is sent to the cloud and the end user has little or no visibility into what they are doing with the information. As an alternative, many free and open source facial recognition software options have emerged, such as CompreFace or FaceNet. Unlike cloud services, the individual or organization will need to deploy and manage the tools. However, when security is a concern, this method allows the end user to store and process their data securely.

AI Facial Recognition Growth Markets

The future prospects of AI-based facial recognition offer a variety of applications across a wide range of potential growth markets. An application of this technology is present, whether for schools and universities or in workplaces. In most organizations, attendance requires some form of manual intervention, whether by the employee having to manually check in when they arrive at work, or at schools, from the part of the teacher who must call attendance to ensure that each student is present. Facial recognition systems offer the ability to automate this previously manual task, saving employers and teachers valuable time and ensuring increased attendance accuracy.

Another potential growth market for facial recognition technology is in the area of ​​marketing and personalization. Imagine a scenario where retail stores can have additional data on which products their customers view and spend the most time with. Today, online e-commerce organizations are already able to track this data and use this information to offer suggested or related products, offer targeted discounts and promotions, and even create tailored online experiences. for specific customers. Using facial recognition technology, retail spaces could mimic at least part of that experience, offering real-time discounts or changing electronic displays to attract specific customers as they move through the store. . Another potential use case for facial recognition is to help create VIP experiences for key customers. When a customer known to make frequent purchases enters the store, staff can be alerted to their presence and ready to create a “VIP experience” for them.

An additional use case for facial recognition comes from the hospitality industry, it could be used to streamline check-in and check-out processes. For example, when a guest arrives at the hotel, facial recognition could display their contact information and register them automatically. Put simply, the software could automatically display their file and information for the hotel employee to create a more personalized and streamlined experience.

A decade ago, before AI really became a technology of the future, facial recognition was mostly conceptual. However, advances in artificial intelligence and machine learning are making it possible to apply facial recognition in a wide variety of applications to create efficiencies that not only reduce the manual workload of employees, but create convenience that improves the customer experience. Accuracy rates have improved dramatically with AI facial recognition, and with advances in technology, we expect even more reliable solutions in the future. As more and more applications and use cases emerge, the AI ​​facial recognition market will continue to grow in 2022 and beyond.

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