AWS S3 & AI: A Computer Weekly Downtime Upload podcast

“Every modern business is a data business,” says Mai-Lan Tomsen Bukovec, a vice president of technology at AWS responsible for data and analytics. “If you think about the journey that many of our AWS customers have started, whether it was 20 years ago or this year, it is about the digital transformation of their companies. It's about modernisation,” she says. Bukovec joined AWS in 2010, and has been responsible for the cloud provider’s S3 cloud-hosted storage as a service business. Looking at AWS’ S3 business, she says: “I have had a lot of fun working with a super talented S3 team for many years, watching the growth of cloud and data.” The first cloud service that AWS launched was S3, in 2006. She says: “The growth of cloud has in many ways been fuelled by the growth of data and the use of that data by companies all over the world.” For Bukovec, IT modernisation involves data. She says: “I think every business leader knows that data is a differentiator. We say that now with AI (artificial intelligence), but it has always been true for any type of business modernisation. In order to make accurate business decisions, Bukovec says that data needs to be clean, correct and easily accessible. She says: “One of the biggest motivators for many companies to go to the cloud was to implement a data lake to get that data in a place where it is at your fingertips so you can use it.” She regards AI as technology that boosts data accessibility. Among the questions Computer Weekly asked Bukovec is why there is a need to use AI to help people understand data, when business intelligence (BI) tools have been offering this functionality for years. She says: “One of the great ironies of BI software is it requires users to understand their data, or as she puts it “know your data”. “You have to know where your data is. You have to know where the schema is. You have to know if it's the clean data set or just the data set that a bunch of teams are working with. You have to actually know your data to know your data.” A lack of understanding of datasets limits the usefulness of data to the population of people who can use BI tools effectively. But she says: “I am certainly excited that with AI, we have a technology base - a technology capability - where you don't necessarily have to know your data to know your data.” According to Bukovec, one of the reasons why AI inference works so well is because a lot of context can be gleaned from the way the question is asked. In the context of understanding business data, she says: “If your agentic AI infrastructure has some knowledge about your role based on the type of questions you're asking, it can infer what to do with the answer in terms of how to frame the answer and how to frame options for your answer.” As a result, people do not necessarily have to know their data. Returning to S3, Bukovec says the AWS storage as a service platform holds over 700 trillion objects. “We added more than 200 trillion just in the past year alone, which is more than any prior year in S3's 20 years of existence,” she adds. And this growth is set to continue. “We are just getting started and agentic use of data is growing like crazy right now,” she says. AWS recently announced a definitive agreement to acquire DuckLabs, the developer behind DuckDB, which simplifies data queries. “One of the reasons why we are so excited about bringing DuckDB into our AWS services is because it provides a new pattern for interacting with data,” says Bukovec. The DuckDB architecture enables queries to operate locally, which directly correlates to the volume of AI tokens needed to perform query task as Bukovec explains: “When you can operate queries locally, you can operate with confidence on your data, because you're just interacting with these smaller set data sets for analysis locally, which is always going to be more efficient.”