Data Streaming Platforms: The Cornerstone of Enterprise AI

Is your artificial intelligence (AI) underperforming? You're not alone. Stale, fragmented data is a leading obstacle to optimal AI performance. Outdated information cripples your decision-making, fuels operational inefficiencies, and leads to missed opportunities—from slow fraud detection to irrelevant chatbot responses.

AI’s rapid evolution makes real-time data even more critical:

• The first wave: For purpose-built AI models trained on a specific data set, having access to high-quality, real-time data leads to more accurate predictions and faster decision-making.

• The second wave: Generative AI (GenAI) requires easy access to fresh, relevant enterprise data for more accurate, grounded outputs in retrieval-augmented generation (RAG) applications.

• The third wave: Real-time data gives agentic AI the context it needs to make autonomous, intelligent, timely decisions.

That’s why real-time data streaming isn’t merely an option. It’s essential to unlocking the full potential of AI—for your organization and your customers.

Read the full 2025 Data Streaming Report.

Why AI Hits a Wall: Every AI Problem Is a Data Problem

The stark truth is that one issue is at the root of every AI challenge: data. This isn't just a hypothesis, and the 2025 Data Streaming Report reveals the main culprits:

• 68% cite fragmented data ownership.

• 65% struggle to integrate new data sources.

• 61% lack real-time processing infrastructure.

AI’s effectiveness is directly tied to the speed, freshness, and trustworthiness of its data. 

Organizations like yours struggle with fragmented data spread across clouds, apps, and legacy systems, plagued by broken integrations and latency. Data quality and governance are constant headaches. These data hurdles don't just slow progress; they actively erode competitive advantage, inflate operational costs, and prevent your brightest minds from focusing on what matters most: innovation. The result? Your AI underperforms, your customers are frustrated, and your teams are stuck fixing data instead of innovating

This is where a data streaming platform (DSP) becomes indispensable.

The real barrier to AI’s potential isn’t the AI itself. It’s the underlying data infrastructure.

Beyond the Data Wall

We've seen how data fragmentation and latency cripple AI. But how are industry leaders breaking through and unlocking AI’s full capabilities? The answer lies in transforming their data approach. 

Data is no longer just a strategic asset. In today’s AI-powered world, it’s the fuel for instant, intelligent action. Only real-time, trustworthy data enables you to make smarter decisions and delivers business value directly to your operations. The most forward-thinking leaders aren’t just analyzing the past; they’re shaping the future with real-time data. 

Traditional business intelligence (BI) was built for retrospective analysis—dashboards and reports on what already happened. But in the AI era, historical data is too slow for the split-second decisions you need to make today. Whether powering chatbots, detecting fraud, or personalizing experiences, your AI needs data that’s fresh, contextual, and instantly accessible. Batch updates and stale information will slow you down and cripple your AI’s potential.

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Data streaming is more than a tool upgrade. It’s a paradigm shift that delivers tangible results: an average 5x return on investment (ROI) that includes faster AI adoption and development, thanks to cost reductions and revenue boosts driven by accelerated innovation and market entry.

Read Full Report

From Models to Agents: Why a DSP Is Key

Let's explore how a DSP specifically addresses the challenges outlined earlier and unlocks transformative business benefits. According to the 2025 Data Streaming Report, 89% of IT leaders see DSPs easing AI adoption by helping them directly address hurdles in the areas of data access, quality assurance, and governance. And most agree that DSPs will increasingly provide AI with real-time, contextual, and trustworthy data.

By implementing a DSP, your organization can make smarter, faster decisions, achieve greater efficiency, deliver personalized experiences, realize rapid ROI, and gain future-proof flexibility to adapt to any AI evolution.

To bridge the real-time data gap for AI, a DSP should offer you:

• Universal data integration across all environments

• Real-time AI pipelines for models, large language models (LLMs), and agents

• GenAI-ready vector data for the freshest RAG applications

• Flexibility to integrate new AI tools and models

• Enterprise-grade security and governance

See how forward-thinking companies like Citizens Bank are already transforming with real-time data:

Without instant access to fresh, reliable information, your AI is effectively blind. Leading organizations aren’t just talking about data; they’re transforming it. According to the 2025 Data Streaming Report, those using DSPs see:

• 90% faster innovation

• 84% quicker time to market

• 84% increased revenue

• 82% happier customers

These aren't just numbers. They represent a fundamental shift in how leading organizations harness AI. Are you ready to join them? Download the 2025 Data Streaming Report or see how Confluent can help you get there.