As organizations push to scale artificial intelligence initiatives, shortcomings in data infrastructure are proving to be a primary obstacle. According to the 2026 Data Streaming Report from Confluent, real-time data capabilities are becoming foundational to unlocking AI value.
The 2026 Data Streaming Report, based on responses from 4,625 IT leaders across 14 countries, indicates that data streaming platforms (DSPs) have transitioned from specialized tools to strategic priorities. 88% of respondents rank investment in DSPs as a high priority, reflecting their role in enabling continuous, governed data flows essential for modern AI systems.
Legacy batch-processing architectures often result in latency, fragmentation, and operational complexity. In contrast, DSPs provide unified real-time data foundations. 94% of technology leaders report that DSPs amplify the impact of AI investments, while 90% state they ease the path to AI adoption. 83% note that DSPs help reduce skills gaps and support organizational readiness for agentic AI.
Business outcomes linked to DSP adoption include richer customer experiences (97%), AI innovation (93%), improved risk management (93%), and reduced time to market (89%). Half of organizations report at least 5x return on investment, with 88% achieving 2x or more. Higher maturity levels correlate with stronger ROI: 68% of organizations at Levels 4 and 5 anticipate or achieve 5x ROI, compared to 51% at Level 3.
Maturity continues to advance. 55% of organizations are now at Level 3 (critical silos with broader production deployment), up from 51% the previous year. Level 5 (real-time enterprise) has doubled to 2%. 22% remain at Level 1, indicating ongoing influx of new adopters.
Agentic AI adoption stands at 32% in production, limited by skills gaps (69%), LLM reliability concerns (68%), and data infrastructure/quality issues (66%). DSPs are viewed as key enablers, with 88% of leaders stating they unlock agentic AI progress through trustworthy, contextualized, real-time data. 76% say DSPs enable the use of enterprise data for AI-based systems.
Data challenges persist, including silos (74%), inconsistency of sources (72%), and uncertain lineage, timeliness, or quality. DSPs help mitigate these: 93% for breaking down silos, 87% for discovery and access, and 81% for governance.
Shift-left integration—processing and governing data closer to the source—is gaining traction. 77% of IT leaders highlight its benefits for data quality and reduced costs, up from 66% previously. Data products built this way support reuse and consistency across use cases.
Germany-specific insights from the report’s press release show 70% of German IT leaders citing insufficient real-time data infrastructure as the top barrier to AI scaling. 80% rank data streaming as a priority, compared to 74% for AI/ML. 84% see DSPs accelerating agentic AI, and 90% expect them to boost AI investment impact.
Case studies illustrate practical value. L’Oréal credits data streaming for digital transformation and agility. Notion uses it for timely AI tool updates. Siemens highlights a single point of truth for physical and virtual worlds. Stone Pagamentos reports faster integrations via managed connectors.
The report underscores that while interest in AI is high, success hinges on modern data foundations. Organizations investing in DSPs position themselves to realize real-time value and competitive advantage.
Dr. Jakob Jung is Editor-in-Chief of Security Storage and Channel Germany. He has been working in IT journalism for more than 20 years. His career includes Computer Reseller News, Heise Resale, Informationweek, Techtarget (storage and data center) and ChannelBiz. He also freelances for numerous IT publications, including Computerwoche, Channelpartner, IT-Business, Storage-Insider and ZDnet. His main topics are channel, storage, security, data center, ERP and CRM.
Contact via Mail: jakob.jung@security-storage-und-channel-germany.de