Sign of the times: QR code turns better with AI

AI corrects errors and personalises codes in the ubiquitous signs used by billions of people. It creates dynamic images that change at frequent intervals to prevent misuse

Japanese engineer Masahiro Hara is not widely known, but his creation is ubiquitous. Hara invented the QR code, short for quick response code, in 1994 while working for Japanese automotive technology company Denso Corporation. After several experiments, Denso initially used his creation for inventory management but later the code was made available for public use. 

Denso retained its patent for the code but decided not to exercise its right: A rare thing to do by a private company. “This policy was in place from the very beginning of the code development, honouring the developers' intent that the QR code could be used by as many people as possible. Thus the QR code, which could be used at no cost and without worrying about potential problems, grew into a public code used by people all over the world,” says Denso on a website about the technology’s history. 

The QR code became popular in Japan in 2002 across industries and since then it has become a striking example of everyday technology tool. 

In the first phase, electronic readers were required for capturing information in QR codes. In the second phase, dedicated apps had to be downloaded on devices for reading the codes. Such barriers disappeared when cameras began reading the codes. The coronavirus pandemic created an urgent need for contactless information and transaction options. Cameras on smartphones took the technology to every sector. The post-pandemic world saw a global surge in QR code use, enabled by smartphone cameras.

The rise of contactless payments, especially in large markets like India, has taken the QR code to nearly all consumers. The QR code is now being combined with artificial intelligence (AI) for new levels of utility and adoption. Billions of transactions are enabled by QR codes in sectors as diverse as retail, real estate, health care and consumer goods. 

AI is improving the security, efficiency and adaptability of QR codes. AI improves images, corrects errors and personalises codes. Smart computer vision algorithms are helping identify and locate a QR code within a larger image. By improving image quality, AI ensures that a QR code’s data and pattern are sharper and readable. Information in digital business cards to products can be personalised in a code. 

The rapid rise in QR code usage has led to incidents of frauds though. Some people have been tricked into using QR codes that claim to represent an authentic product or service. Here too AI has a solution: It creates dynamic QR codes that change at frequent intervals to prevent misuse. 

The global QR code payments market was valued at $8.07 billion in 2020 and it is projected to reach $35.07 billion by 2030, according to Allied Market Research. Apart from payments, product and information are the other high growth sectors for QR codes. 

India has its own stack of QR code. The National Payment Corporation of India worked with the International Card Schemes (ICS) to develop a common standard and launch Bharat QR, a digital payment mechanism that merchants and e-commerce websites are using. 

As with many technologies, QR code has grown in phases and is likely to see more evolution. Matters of security and authenticity are being resolved using AI and smarter codes. New phases of development would be micro codes invisible to the human eye. The addition of colours will allow even more data to be stored in a QR code. With their invention and public sharing of the technology, Masahiro Hara and Denso enabled the most democratic deployment of technology in recent history.

In response to a question about his invention’s future, Hara once said: “...I just want to let a lot of people use the code, come up with new ways of using it with them, and put these ideas into practice. This is the way, I’d like to think, that evolutionary improvements have been made to the QR code.”