At the beginning of the 19th century, the economist David Ricardo explained his theory of international trade based on comparative advantage by choosing as an example Portuguese wine exchanged for British wool. The impact of artificial intelligence on the economy is recent; everything has changed in recent years. At the beginning of the 21st century, access to data becomes a comparative advantage.
The first article explains the major economic and societal challenges of artificial intelligence (AI) in the wine industry. We will then focus on the likely impact of AI on value transformation, more commonly known as disruption. David will then examine the contributions of AI on professional pricing in wine distribution. Finally, we will reflect on the impacts of wine price personalization for consumers at the dawn of AI-managed dynamic pricing.
The importance of raw data for AI
The characteristics of the technical landscape of artificial intelligence (AI) have metamorphosed since 1950, when Alan Turing first questioned the ability of machines to think. Data is a crucial element in the development of these self-learning AI machines.
When it comes to deep learning, the more trained an AI is, the more relevant it is. Within organizations, companies and administrations, the stakes and the importance of big data seem to be more and more understood and assimilated. What is much less understood is the crucial importance of raw data in artificial intelligence. Metcalfe’s law – theorized by Robert Metcalfe, the inventor of the recent internet standard – explains that the value of a network grows as the square of the network users.
Data: a crucial asset
In fact, organizations that have access to large databases are in possession of a critical asset.
Only a few players in the wine industry have built their business model on data: let’s mention the New Zealand website Wine-Searcher and the Danish company Vivino. In contrast Amazon stopped selling wine on its dedicated marketplace, Amazon Wine, in 2017. The Drizly platform has become with Wine.com the leader in online sales across the Atlantic.
The ability to continue learning with new data can therefore be a source of sustainable competitive advantage. The fact that companies have collected a lot of information does not necessarily hurt consumers. There is more direct interaction between companies and consumers, and prices are better adjusted.
Being consumers of American and Chinese giants
It is undeniable that GAFAM (Google, Apple, Facebook, Amazon, Microsoft) and BATX (Baidu, Alibaba, Tencent, Xiaomi), whose success is largely due to their ability to collect data, are starting with a clear advantage in the global artificial intelligence race.
These digital giants have every interest in opening up their machine learning algorithms, to capitalize on the logic of open innovation. Although these large companies are currently forging numerous partnerships with research organizations to feed data into their algorithms and improve them, they are careful not to open up all their data.
They thus retain control over their strategic assets, and determine the conditions of access and use. However, LVMH (Moët-Hennessy) recently partnered with Google Cloud for an AI project. The system will exploit trillions of personal data.
The danger is that companies will become mere consumers of solutions developed by digital giants.
May or may not be complementary to AI
New technologies risk widening the gap between countries where automation is already established or not, between players oriented or not towards artificial intelligence, between employees complementary or not with AI.
Kevin Kelly, one of the intellectuals of artificial intelligence, predicts that “the real management tomorrow is not to manage people, it is to manage people and AI. It’s about managing intelligences because there will be several types of artificial intelligence. Various economic studies legitimize this sentiment, predicting the replacement of 10% to 70% of jobs by machines in the next ten years. The jobs threatened by AI are the non-manual jobs, whether they are sophisticated or not.
In the next article, David will discuss customizing professional wine pricing with artificial intelligence. Feel free to share with us in comments.