According to Confluent’s Data Streaming Report 2026, prepared from the responses of 4,625 IT managers in 14 countries, data streaming platforms have surpassed artificial intelligence and machine learning as a strategic priority for companies for the first time.
The business technology conversation no longer revolves solely around artificial intelligence. As organizations advance their adoption, so does the focus on the infrastructure that makes it possible: data. In this context, data streaming is consolidated as the technology that allows you to connect, process and activate information in real time to drive AI initiatives more effectively.
«This change reflects an increasingly evident reality: the success of artificial intelligence depends directly on the quality, availability and activation capacity of the data that feeds it. That’s why organizations are paying increasing attention to data streaming infrastructures, which allow information to be connected, processed and used in real time,” explains Shaun Clowes, product manager at Confluent.
What the figures reveal
The main finding of the report is that data streaming platforms have surpassed artificial intelligence as a strategic priority for companies for the first time. Looking ahead to 2026, 49% of IT managers place data streaming among their top investment areas, compared to 45% who prioritize AI and machine learning. Just a year ago, the situation was the opposite.
The study also reveals that data management, protection and governance is consolidated as one of the main priorities for organizations, reaching 88% when combining main and secondary priorities. Cybersecurity continues to lead technology concerns, with 96% mentions.
Beyond the percentages, the results reflect an evolution in the way in which companies face the adoption of artificial intelligence. As projects move toward production environments, organizations are increasingly aware that AI performance depends on the ability to have data that is reliable, accessible, and updated in real time, a capability provided by data streaming.
«Strengthening data infrastructure has become an essential requirement so that artificial intelligence initiatives can scale and generate value in a sustainable way. In this scenario, data streaming plays an essential role,” says Clowes.
Data infrastructure: the hidden challenge behind AI ambitions
The report reveals that the main obstacle to scaling artificial intelligence is no longer the models, but the data infrastructure that supports them. In fact, 72% of IT leaders say they have faced three or more challenges when deploying AI initiatives due to the limitations of their data systems, reinforcing the need to invest in data streaming platforms.
Among the most common problems are data silos (74%), the lack of coherence between different sources of information (72%) and difficulties in guaranteeing traceability, updating and quality of data (71%). In addition, 60% acknowledge that they are simultaneously managing at least five data-related challenges.
As AI is integrated into increasingly critical processes, having up-to-date information has become a priority. Not surprisingly, the percentage of IT managers who identify real-time data processing as one of their main challenges has increased from 61% in 2025 to 72% in 2026, driving the adoption of data streaming solutions.
What this change in priorities reveals
More than a displacement of artificial intelligence, this change reflects an evolution in the way companies approach its adoption. Organizations are increasingly aware that the success of any AI initiative depends, to a large extent, on the quality, availability and updating of the data that feeds it, an area in which data streaming has become a strategic component.
The report’s findings support this trend: 94% of IT decision-makers say they have seen—or expect to see—a positive impact from data streaming platforms on the performance of their AI investments. Additionally, 50% of organizations expect to see at least a five-fold return on investment, while 88% expect to at least double the value invested.
Organizations are aware that the success of AI depends on the quality, availability and updating of the data that feeds it.
Data streaming is also establishing itself as an enabler for other strategic priorities. Customer experience (97%) and cybersecurity and risk management (93%) are among the areas in which organizations expect to obtain the greatest benefits from these platforms.
What these changes mean for technology leaders
This shift in priorities reflects an evolution in the way organizations approach digital transformation. The challenge is no longer just incorporating new AI capabilities, but ensuring that the data infrastructure is ready to support and scale them through a robust data streaming strategy.
Although the gap between streaming data and AI as a strategic priority remains narrow, the trend points to a change in focus. “The conversation is no longer just about the capabilities of artificial intelligence, but also the ability of organizations to have data connected, governed and available in real time that can turn that potential into real results. Data streaming will be a key element to achieve this,” concludes Clowes.
