In both B2C and B2B, more of the buying process is being handed to AI. Assistants can research vendors, compare options, and build shortlists before a person has reviewed a single offer.
But an AI assistant can only work with the information it can access at that moment: current stock, live pricing, service availability, customer history, and transaction data. If that information is delayed, incomplete, or trapped in disconnected systems, the AI is working from an outdated version of the business.
That is the central argument of Mimacom’s new white paper, The Data Streaming Foundation for AI. For many organizations, the limiting factor in AI is no longer the model; it is whether the right data can reach it quickly, reliably, and with enough context to make the output useful.
AI is turning data latency into a business problem
Kai Waehner, Mimacom’s Advisory Field CTO, puts it simply: “AI needs more than models. It needs context.”
Competitors can often access the same foundation models. What they cannot replicate is a company’s own operational and customer data, delivered accurately and at the moment it matters.
The data backs this up. According to the 2025 Data Streaming Report published by our partners Confluent and IBM, 86% of IT leaders now consider data streaming a top strategic investment priority, up from 51% in 2024 and 44% in 2023.
The challenge is that much of the infrastructure beneath today’s AI initiatives was never designed for this. A batch process that updates once a day may be acceptable for a report reviewed by a person. It is much less useful when an AI system is expected to recommend, detect, or act immediately.
That is why many AI pilots stall when they move toward production: the model works, but the surrounding data architecture does not.
Start with the problem, not the transformation program
Becoming AI-ready does not necessarily mean replacing everything. The first step is understanding where the existing architecture creates friction: which systems hold the critical data, and how quickly it actually needs to move. From there, the real question is where changing that flow of information would create the most value.
Mimacom’s Data Readiness Assessment is designed around that question. In around ten days, teams receive a prioritized roadmap covering their current architecture, the most relevant opportunities for real-time data, and the next steps required, within a fixed scope and price.
Mimacom brings that work together with a long-standing Confluent and Apache Kafka® delivery practice and its new status as an IBM Silver Business Partner, following Confluent’s acquisition by IBM.
The same principles are already in production environments ranging from Bühler Group’s global monitoring platform, which processes 12,000 events per second, to a major Spanish grocery retailer handling around 90 million events each day. All this expertise and case studies are covered in this new publication.
