It is hard to open a newspaper, or listen to the news without some story about the ever expanding influence of AI coming up and how it is going to transform our lives like nothing that has come before. It’s not surprising, therefore, that the mass majority look at AI as more of a threat and something to be scared of rather than want to see how they can use it to its maximum effect in their working lives. For AI expert and data scientist, Joanna Dabrowska, such a response is completely understandable - at least initially. As she says: “Each wave of change brings a degree of fear. That is, in many ways, human nature.” But it also can’t be ignored and we all need to not only embrace it, but truly understand how AI can actually make all our lives better in the same way that past huge technological advances have done - like the internet. Here she sets out how she is working with wine companies on how best to implement AI in their businesses and where the true value of AI is in helping take the wine industry to the next technological level.
If someone had told me a few years ago that one day I would be writing about AI implementation, opportunities and challenges in the wine industry, I would probably not have believed it. I would have been excited, but also hesitant.
Excited, because I have spent 15 years working in AI, analytics and data science, across companies including Amazon Web Services, PwC, Deloitte and Expedia. In each of these, I led complex projects, from proof of concept through to enterprise transformation. And in every single one, the first thing to fix was data, and how it was being used. We call this data literacy.
Hesitant, because I had no real background in wine beyond frequent visits to Porto wineries as a student, and later vineyard visits and tastings as a young professional. At that point, I had the impression that the wine industry relied more on relationships than on data. It took formal wine study, and a few industry tastings, to realise quite how much data exists in wine, and how little of it is used effectively.
Today, I bring these two perspectives together, combining data and AI expertise with wine journalism, judging, and speaking engagements.
However, whenever I introduce the topic of AI in wine, something shifts in the room. Most people are already using it, yet few talk about it openly, and fewer still question its limitations. Instead, the conversation often defaults to risk. AI makes mistakes. It can be confidently wrong.
But underneath that sits something else. Fear. Fear of replacement, fear of losing craft, fear of a future in which algorithms write tasting notes and ChatGPT sells the latest release of Burgundy.
It is understandable. The coverage so far has been relentlessly dramatic. But it is also, in my view, unhelpful. The more useful question is what AI actually does well, where it creates value, and how the wine trade can use it, and is already using it, in practice.
What AI is, and what it is not
The AI most people in the wine trade are encountering daily is generative AI.
Generative AI is a branch of artificial intelligence designed to create entirely new content such as text, images, or video, by learning patterns from existing data. Common examples include Large Language Models (LLMs) like ChatGPT and Claude for writing, Diffusion Models like Midjourney and DALL-E for creating visuals, and Video Generation Models like Sora or Runway for moving imagery.
Generative AI, including Large Language Models (LLMs), excels at creating content by identifying patterns, whereas traditional machine learning is designed for predictive tasks like forecasting market trends. While AI can analyse data rapidly, it cannot replace the sensory expertise, interpersonal connection, and nuanced interpretation provided by a human.
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