Many enterprises face AI adoption bottlenecks due to siloed data and legacy infrastructure. A survey of 1,200+ technology leaders by Economist Enterprise found 67% of companies with disconnected data environments cite data storage, movement, and duplication as their largest recurring AI cost. Three key infrastructure considerations are highlighted: speed (60% of companies take up to 12 months to get AI into production), data unification (breaking down silos between operational and analytical data), and elastic cost management (decoupling compute from storage to align costs with actual usage). AI-ready, open databases that support instant provisioning, unified data access, and elastic scaling are positioned as the solution to accelerate AI delivery.
