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Data Streaming Now Central to AI Strategies, New Report Finds
A new industry study has revealed that while data streaming is increasingly essential for artificial intelligence (AI), it is also introducing serious bottlenecks for large organizations. The research, conducted by Conduktor, the intelligent data hub for streaming data and AI, highlights a growing list of pain points among enterprises integrating data streaming into AI and machine learning (ML) workflows.
RELATED: Data streaming complexity undermines corporate AI readiness, Conduktor report warns
Surveying 200 senior IT and data executives from companies earning at least $50 million annually, the study found that 43% already use data streaming to train or run AI systems. This compares to 83% who rely on it for workflow automation and 51% who use it to support real-time decision-making.
AI Integration Now the Top Priority for Data Streaming Systems
The research shows that integration with AI/ML platforms has overtaken traditional priorities such as connectors to mainstream applications, security, and governance.
Executives identified the top three data quality issues undermining AI performance:
- Inconsistent data formats or schemas
- Duplicate events that distort AI outputs
- Missing or incomplete data
These issues can significantly skew models, reduce accuracy, and slow down deployment cycles.
Scaling Introduces New Risks and Costs
As organizations deepen their AI investments, scaling supporting data infrastructure has become increasingly complex. The key challenges cited include:
- Data privacy and security concerns (72%)
- High infrastructure costs (59%)
- Insufficient real-time processing capabilities (58%)
To support AI workloads, enterprises are turning to a mix of cloud-based tools. The top platforms reported were Google Cloud Vertex AI, Microsoft Azure Machine Learning, Amazon SageMaker Data Wrangler, and AWS Glue DataBrew.
Strong Confidence Despite Persistent Pain Points
Despite the challenges, confidence in data streaming remains high.
- 80% of respondents rated their AI–data streaming integration as “good”
- 9% said “excellent”
- 11% said “average”
Conduktor CEO Nicolas Orban emphasized that AI depends on fresh, contextualized, high-quality data and that streaming platforms are now core to modern workloads.
He noted, however, that while most organizations believe their integrations are strong, key problems persist:
- 58% still struggle with data quality
- 72% face ongoing privacy and compliance issues
- Fragmented data continues to lead to missed signals, low trust, and poor decisions
Orban said Conduktor’s platform helps organizations unify streaming data for full visibility and control, improving IT productivity.
Global Market for Streaming Data Systems Set to Surge
According to market intelligence firm Dataintelo, the global streaming data processing software market was valued at $9.5 billion in 2023 and is projected to grow to $23.8 billion by 2032, representing a 10.8% CAGR.
This growth is being driven largely by the rising need for real-time data processing across industries — fueled by massive data volumes from social media, IoT devices, and enterprise systems.
Learn more about Conduktor’s streaming data hub.
- Conduktor commissioned market research firm Pureprofile to conduct a survey with senior IT / data executives at large companies with an annual revenue of $50 million or more and who have over 500 employees, to capture their views on their organisation’s data streaming / data streaming platform strategies. 200 senior executives from across Europe and the US completed the survey online in July 2025.
- Source: https://dataintelo.com/report/global-streaming-data-processing-system-software-market
