Most companies have more AI pilots than AI systems in production. According to Deloitte’s State of AI in the Enterprise 2026, only 25% of organizations have moved 40% or more of their AI pilots into production. Respondents reported that while their AI strategy is prepared, they felt less confident on infrastructure, data, risk, and talent.
Financial services firms face a difficult technology mandate: improve digital products, make data more useful, and create room for AI while maintaining the resilience and control expected of critical financial systems. Aging infrastructure can slow that work, but cloud migration changes more than the location of an application. It changes how teams manage access, deploy software, recover services, and produce evidence that controls are working.
For ecommerce companies, pressure to improve digital experiences, absorb unpredictable demand, and launch new capabilities faster is exposing the limits of legacy infrastructure that wasn't built for the way the businesses now operate and sell.
For manufacturers, pressure to increase productivity, respond faster to supply chain disruptions and changing customer demand, and make greater use of operational data, automation, and AI is exposing the limits of aging on-premises infrastructure and driving migration to AWS.
Many Amazon Bedrock implementations start with what looks like a straightforward goal: connect structured and unstructured data sources, make them accessible to a foundation model, and enable natural language interaction. What becomes clear very quickly is that the quality, reliability, and cost of the solution depend heavily on decisions made at the data layer (not in the model or prompt design).
Seven technology leaders explain how they centralize AMI builds, manage versioning and patching, and control stale images across multi-account AWS environments.
Cloud operations teams that automate their single most repetitive, highest-friction manual task before chasing more complex systems see the fastest and most durable gains, based on strategies shared by 13 technology leaders for this piece.
Cloud operators, founders, and IT leaders share how they're managing cloud storage costs. From data-driven access audits to lifecycle automation to the forgotten capacity reservations hiding outside the standard cost report, here's what's working... and what's not.
Cloud cost optimization means getting the most business value from every dollar spent on cloud services. It’s all about ensuring that your infrastructure delivers measurable value. When teams align architecture, operations, and business outcomes, cost reduction becomes a natural outcome of efficiency.
