With the rapid success of OpenAI’s ChatGPT and other emerging types of AI solutions in the last several years, organizations have been scrambling to adopt artificial intelligence by “any means necessary.” This pivot has changed how organizations think about modern enterprise data architecture.
The survey, “2025 Market Study: Modern Data Architecture in the AI Era” conducted by Radiant Advisors and Unisphere Research, and sponsored by Denodo, Onehouse, and Quest Software, documents how organizations are building integrated AI-enabling infrastructure stacks through the adoption of GenAI with LLMs, including RAG and knowledge graphs, as well as data lakehouses and semantic layer technologies.
Organizations have progressed beyond experimental approaches to establish strategic commitment around AI-enabling capabilities, the survey finds.
The shift to smaller, focused budgets validates this evolution of AI as a business case. It reflects organizational recognition that competitive advantage comes from intelligent automation and targeted implementations rather than comprehensive system replacements. The survey notes, this approach allows organizations to demonstrate rapid value realization while progressing toward integrated AI-enabling architectures through incremental, strategic deployments.
According to the survey, GenAI with LLMs have captured most of the organizational attention and research bandwidth, with 57.9% of companies actively evaluating this technology despite its recent emergence in the enterprise data architecture landscape.
Traditional architecture research is experiencing an attention shift, with cloud data warehousing evaluation declining from 53.3% to 39.0% and real-time analytics research dropping from 51.4% to 38.6%.
“When nearly 60% of organizations actively research the same architecture and technology [GenAI], this capability is recognized as essential infrastructure rather than optional innovation. This concentrated attention suggests that data leaders not currently evaluating AI-enabling architectures may risk falling behind in their strategic planning cycles,” the survey said.
AI and GenAI use case adoption leads the primary business justification at 49.4%, maintaining its position as the most compelling driver for architectural transformation while slightly strengthening from 48.6% in 2023.
Business value and operational efficiency drivers have emerged in 2025 as major new justification themes, with previously unmeasured drivers such as “improve data freshness and accessibility” (40.2%), “modernize legacy data architecture” (38.2%), and “reduce total cost of ownership” (36.3%) now representing measurable investment motivations.
Traditional performance-focused drivers have experienced a substantial decline in interest, with “increase operational real-time analytics” dropping from 49.5% to 37.1% and “increase broader analytics performance, scalability, and agility” falling from 47.1% to 31.3%.
The strategic implications for data leaders center on developing integrated business cases that combine AI enablement with operational transformation, rather than relying on traditional arguments for technical improvements, according to the survey.
These patterns indicate that successful architectural initiatives now necessitate business justifications that illustrate how AI capabilities will transform business operations, while also improving data accessibility, reducing costs, and creating reusable data assets.
“Data leaders should structure their business cases to highlight how AI-enabling architectures will create sustainable competitive advantages through intelligent automation, enhanced decision-making capabilities, and data-driven business model innovations, while also providing the operational efficiency and cost management benefits that executive stakeholders expect from infrastructure investments,” the survey reflects.
To read the full report, go here.