As the shopping spree continues this festive season, experts believe that the exchange of personal data on a large scale, apart from gifts can also bring in threats. E-commerce order volumes grew by about 37% during the festive season sale of 2023 as compared to the festive sale period in 2022, as per a recent report by Unicommerce, a cloud-based E-commerce platform. In addition to the growth in order volumes, the Gross Merchandise Value (GMV) also increased by 22% during the same festive period. Automated threats are a top concern with about 62% of attacks on online retailers. America, Europe, and Asia Pacific were the top regions for bad bot attacks on retail websites, as per insights from Imperva, a cybersecurity platform.
With a population of over 1.4 billion and a fast-growing economy, the number of online shoppers is predicted to increase to 427 million by 2027. Consequently, the e-commerce industry is estimated to be worth over $350 billion by 2030, as per insights from Statista. In conversation with FE TransformX, Vinod K Singh, serial entrepreneur, tech visionary and advisor, on how the collaboration of generative AI and cloud computing is changing the e-commerce industry. (Edited Excerpts)
How is data being exchanged in the e-commerce sector?
We live in the era of the Internet of Things (IoT), ubiquitous tracking devices, and widespread smartphone use, all of which generate a significant amount of personal data about consumers. Furthermore, the rise of cloud computing, machine learning, and AI opens up enormous opportunities for e-commerce companies to use this data to improve customer experiences.
Finding a balance is the tricky part. Companies such as Amazon and Walmart, among others, might afford to make more investments in data privacy, but e-commerce startups might face much greater challenges. There is a never-ending struggle to make sure data is not abused while still being used to improve customer experiences.
Can the use of generative AI platforms for personal use bring threat? If yes then how?
There can be drawbacks and advantages to generative AI for personal use, as seen with ChatGPT and related platforms. While personalisation can be a positive aspect, data and privacy breaches are the loopholes that they bring up.
The main issue with generative AI platforms is that they could jeopardise the privacy of consumer data. These models, once trained, can be used by both malicious and ethical hackers, which is why data protection protocols must be strengthened.
How cloud computing and generative AI can provide a balance between personalisation and security?
Researchers and industry stakeholders as a whole need to take steps to address the risk of data breaches. Nonetheless, it is critical to recognise that generative AI is revolutionising other industries, including e-commerce. By allowing companies to create product descriptions and customised content that appeals to their target audience, these platforms have the potential to completely transform customer service. This can improve the shopping experience for customers by directing them to the appropriate products and quickly responding to their questions.
Many new opportunities have arisen especially for younger generations who might disrupt the e-commerce industry by spending a lot on these platforms. Here, cloud computing can be a major player in providing security at an optimised cost. With cloud computing the cost of obtaining the computer power, instruments, and security precautions required to safeguard your data has significantly decreased. Cloud computing has essentially allowed smaller players in the market who might not have large budgets to access a variety of tools and technologies to protect their data and address privacy concerns.
Cloud computing and AI are relatively costly when compared to the Indian market. So, how can we reduce this?
To suit the Indian market, global companies such as AWS, Google Cloud, and Microsoft Cloud, among others, are making adjustments to their operating models, support systems, and pricing strategies. It all comes down to affordability and ease of use.
However, Indian companies such as Reliance are also making waves, particularly with their Jio Cloud Connect and business solutions. With Jio, they were able to achieve this goal of making mobile data accessible to all. Everyone can afford 5G on their smartphone. It is expected that the future might hold many new things.
Has India truly adopted technology and are we ready for the next steps?
When it comes to the adoption and advancement of technology, I think India might be in the top ten or even the top five. The emphasis on digitisation and independence is evident in various initiatives such as the government’s ‘Make in India’ campaigns, 5G, and low-cost computing. By manufacturing in India, you save money on import duties and currency conversion, making your products more cost-effective. Also, in just the last three months, we have seen the birth of six or seven unicorns in India. That surpasses the accomplishments of certain European nations.
When it comes to technology and combining everything, won’t it affect the quality of the data?
Data quality is critical and businesses utilising AI to try to develop chatbots, personalisation engines and other systems, can sometimes lead to disastrous results. These systems occasionally produce biased or inappropriate recommendations as a result of faulty or corrupted data. Data can be taken for granted, but when things go wrong, there is no way around the need to go back and clean things up.
In the modern world, preparing our data is much more important than rushing into the realm of artificial intelligence and cutting-edge technologies. The more data you have, the more expensive it is to clean and prepare it for AI or machine learning. Although some businesses and cloud providers are attempting to make this process more cost-effective, it is still a substantial task.
How can we effectively raise awareness about the significance of data quality in the tech era?
I think that education and effective communication go hand in hand, in solving this problem. For illustration, suppose I were to approach a non-technical business owner or someone similar to you with a sizable enterprise and request a million dollars to clean and prepare the data. The first thing you would ask me is, “What is the return on investment?” Without a good idea of the benefits, it is difficult to defend such an investment.
Education is therefore essential to dispelling these myths. People need to be made aware of the value of statistical insights and high-quality data. We must collect data and demonstrate to them the value of investing in data preparation. Essentially, there is no shortcut here; building this understanding gap and demonstrating the return on investment in data quality requires education and clear communication.
Can government-backed programs raise awareness for investing in data quality during this tech era?
The government or a centralised body can play an important role in managing and cleaning shared public data that is shared by many entities. Consider details like postal codes, city codes, addresses, and other information that is generally needed. This data should only be handled by one centralised organisation, which would also guarantee that it is accessible to the general public.
Also, individual entities are still accountable for ensuring data quality when it comes to private information unique to a given business, its clients, and its particular operations. However, we can greatly lessen the problem’s overall weight and scope by centralising the management and cleaning of public data.
