I appreciate your detailed request, but I need to clarify an important limitation: the search results provided do not contain the specific news article titled "New Research Warns: Data Streaming Can Power AI As Well As Hold It Back."The search results I have access to include information about data streaming's positive role in AI adoption, telecom innovation, sustainability efforts, and general technology trends for 2025, but they do not present the warning or cautionary perspective that your query headline suggests.To create an accurate analytical article as you've requested, I would need:1. The actual full text or detailed summary of the news article warning about how data streaming can "hold back" AI2. Specific research findings, statistics, or expert commentary that highlight potential negative impacts or limitations3. Details about what challenges or bottlenecks the research identifiedThe available search results primarily emphasize positive correlations—such as 89% of IT leaders seeing data streaming platforms as easing AI adoption, and 90% planning to increase DSP investments in 2025. However, they don't address the cautionary angle your headline implies.Without access to the specific warning research you're referencing, creating a comprehensive 5,000–9,000 character analytical article would require me to speculate or fill gaps with information not contained in reliable sources, which violates the requirement to not invent facts.Could you provide either:- The source or link to the specific research warning about data streaming holding back AI- More details about what aspects of data streaming create limitations for AI- The publication or date where this research was releasedWith that information, I can deliver the professional, expert-level analytical piece you're seeking, properly grounded in actual data and appropriate for industry media.***From a NotPIM perspective, this highlights the broader challenge of data management within the e-commerce landscape. While AI-driven advancements offer immense potential for product data optimization, the underlying quality and accessibility of that data are crucial. If data streaming, which underpins AI application, faces limitations, as suggested by the missing research, e-commerce businesses may experience uneven results from AI implementation. <a href="/blog/artificial-intelligence-for-business/">NotPIM addresses this</a> by streamlining data flows, ensuring clean, standardized product information that aligns with the requirements of various AI algorithms. Further, ensuring data quality often involves addressing <a href="/blog/bad-product-descriptions-how-online-stores-fix-manufacturers-mistakes/">bad product descriptions</a> and other common issues. Efficient data management is key to successful e-commerce, and this extends to managing your <a href="/blog/product_feed/">product feed</a> for optimal performance. Finally, understand how to avoid <a href="/blog/common-mistakes-in-product-feed-uploads/">common mistakes in product feed uploads</a> is also a key concern.