Why 92% of Companies Lack AI-Ready Data
In her recent ERP Today article, Radhika Ojha highlights a surprising statistic: while 97% of organizations feel pressure to deploy artificial intelligence (AI) quickly, a whopping 92% aren’t ready. The reason isn’t lack of talent or infrastructure—it’s messy, siloed data. Finance, sales, HR, manufacturing, and supply chain systems often live in separate platforms that don’t communicate, making it nearly impossible for AI to deliver meaningful insights.
The Cisco AI Readiness Report shows that data is the weakest pillar for most companies. AI models need clean, unified data to work, but many organizations focus on hiring data scientists or investing in algorithms while ignoring the fragmented data in their ERP systems. Without consolidating and cleaning decades of historical records, AI initiatives can stall, and predictive insights—like customer churn or supply chain forecasting—remain out of reach.
The first step toward AI readiness, Ojha states, is aggregation. Platforms like JiVS IMP from Data Migration International can consolidate, clean, and structure data from across legacy systems, creating a single, AI-ready foundation. For ERP leaders, this means that any system migration—like SAP S/4HANA—should focus not just on moving data, but on making it usable for AI. In short, before AI can start providing real value, organizations must ensure their core ERP data is structured, accessible, and ready for intelligence.
Retiring Lawson, PeopleSoft, or Oracle? APIX archives the entire application — every table, every year, attachments and security included — into your own AWS account in about 30 days, so you can decommission the legacy system and keep full access to the history.
