Preparing for the inevitable implementation of AI, and whatever its future iterations may be, requires a look at architectural patterns. From cloud data warehouses and real-time analytics to data lakehouses, data fabric, and data mesh trends, how are enterprises currently planning to support generative AI (GenAI) at the infrastructural level?
In another installation of the new webinar series brought to you by DBTA and Radiant Advisors—also sponsored by Quest and TimeXtender—John O'Brien, principal advisor and CEO, Radiant Advisors, unveiled the results of a comprehensive study tracking enterprise adoption rates and maturity across key architectural patterns, highlighting how organizations are prepping for AI without sacrificing governance and security.
The Radiant Ascent Webinars explore modern enterprise data and analytics architecture, featuring monthly deep dives into emerging technologies and best practices. In each episode, John will guide you through a new technical summit, unpacking complex architectural challenges and revealing proven strategies.
In this episode, Modern Data Architecture Trends in the Era of AI: The 2025 Q1 Survey Results, O’Brien offers viewers a sneak peek at the latest findings in the data architecture space.
This survey was conducted in March 2025 with 259 qualified respondents—97% of which reside in North America—which was a follow-up from a 2023 survey. Questions regarding data architectures ranged in topic from budgets to cloud data warehousing; data lakehouse; data fabric; streaming and data analytics; semantic layers and search; and GenAI.
O’Brien began with the first survey question, relating to budget: “Has your organization budgeted for initiative(s) related to modernizing the data platform, enabling real-time analytics, implementing data products, or enabling AI, GenAI, or ML?”
According to the results, 42.9% of respondents reported they have, and those budgets were approved, with 42.4% reporting they have submitted a budget and are awaiting approval—making up a total of 85.3%.
“When it comes to…modernizing the data platform…85%—overwhelming, in my opinion—are taking action on this,” said O’Brien. “This shows that this [budgeting] is a very active part of companies and IT organizations.”
Drilling down further, for those who responded that their budgets were approved, they were further asked about the amount. Those who allocated $50,001-$100k showed a massive leap from 2023, indicating a 384.5% change.
O’Brien noted that, as an advisor to many companies, this was particularly interesting as he believed more companies were allocating within the $100,001-$500k range. This represents a “shift between kind of the ‘normal’ [range] and…smaller, use case…projects,” said O’Brien.
The next survey question posed: “Which of the following data architectures is your company currently researching or considering? (Click all that apply)”
The top three results were GenAI with large language models (LLMs) (68.4%), real-time analytics (63.7%), and modernizing to cloud data warehouses (58.2%).
O’Brien explained that while GenAI taking the top spot was new to the 2025 survey, it’s unsurprising given the cultural focus on the technology. He further wondered if the push for real-time analytics is related to the GenAI demand, adding how modernizing to cloud data warehouses continues to be a mainstream focus.
Delivering further context, O’Brien examined these results compared to 2023’s findings, noting how real-time analytics overtook cloud data warehouse modernization in 2025’s survey. This flip could be “a combination of the drive and need for real-time analytics and streaming data or it could also be, ‘We’ve worked on the cloud data warehousing in the last couple of years, and it’s not something we’re looking forward to; it’s something we consider done,’” O’Brien explained.
Other architectural patterns, including data lakehouse, streaming IoT data, and data fabric, all increased in consideration compared to 2023.
The survey continued with the following: “Which data architectures do you understand well, including its compelling business value? (Click all that apply)”
This question found that cloud data warehousing took the lead with 51%, followed closely by GenAI with LLMs (49.8%). Below these two patterns was a steep drop, where real-time analytics came in at 32.8% and data lakehouse at 32%.
Compared to 2023’s findings, real-time analytics and data lakehouse dropped by 20.2% and 10%, respectively.
However, “When we’re looking at this, we have to keep in mind that we introduced two new features in this survey—GenAI with LLMs, which jumped all the way to the top. You have to imagine that that pools with it quite a bit of people’s attention and focus when it comes to business value,” noted O’Brien. “I wouldn't say that people feel that those [real-time analytics and data lakehouses] are less valuable…it’s…[just] shifted the focus to cloud warehousing, which has been the mainstream, and the new GenAI space.”
This is only a snippet of the full Modern Data Architecture Trends in the Era of AI: The 2025 Q1 Survey Results webinar. For the full webinar, featuring even more survey results and examinations, a Q&A, and more, you can view an archived version of the webinar here.