Enterprise leaders have spent two years and hundreds of billions of dollars on AI. The results have been uneven. According to McKinsey’s 2024 global survey, fewer than one in three companies report that their AI investments have generated meaningful, sustained business value. The demos tend to impress, and production tends to disappoint. The diagnosis offered…
If you’ve been following BigDATAwire coverage, you would have noticed the data and AI industry leaning toward real-time systems. Aligned with that trend, the enterprise intelligence platform Starburst has launched a new AI data assistant called AIDA that connects AI to governed enterprise data across distributed systems. The aim is to replace delayed reporting with…
According to the State of Analytics Engineering 2026, the modern data stack is scaling fast, but unevenly. It is also growing faster than the trust and governance mechanisms designed to support it. AI is no longer experimental. It is embedded. 72% of teams now prioritize AI-assisted coding, and more than 77% of leaders are already…
The hidden costs of traditional databases often force developers to create custom infrastructure for managing workflows. This is a critical resource conflict. Instead of focusing on building new products or advancing AI initiatives, the developers spend more time solving operational problems. As enterprises move deeper into AI, this issue is pushing data teams outside their…
A recent report from Precisely highlights an interesting paradox: 87% of organizations believe they are ready for AI, yet at the same time, 40% of the leaders reported that data, skills, and infrastructure remain the biggest obstacles. Precisely’s fourth annual State of Data Integrity and AI Readiness report reveals a growing disconnect in how organizations…
