Generative AI is dissolving the economic logic that made standardized enterprise software the only practical choice for most companies. What replaces it will be shaped not just by the rapidly evolving capabilities of this new technology, but by leaders willing to ask a harder question: Which workflows do we actually need to own?
Exchanges are a place where you can submit an order to buy something, letting everyone know about the price you want and notifying you when your order gets filled. They serve as financial infrastructure, providing up-to-date prices and facilitating trades.
Red Hat OpenShift on Google Cloud Dedicated is designed to address several key pillars of digital sovereignty: data residency, technological autonomy, and supply chain resilience. With isolated infrastructure, it must comply with regulations such as the GDPR and regional sovereignty rules.
Blackbox Hosting has consolidated storage from two full racks down to just 8U of rack space following migration to Everpure FlashArray hardware, achieving a 10:1 data reduction ratio and an 85% reduction in power utilization.
A North American manufacturer spent most of 2024 and early 2025 doing what many innovative enterprises did: aggressively standardizing on the public cloud by using data lakes, analytics, CI/CD, and even a good chunk of ERP integration. The board liked the narrative because it sounded like simplification, and simplification sounded like savings. Then generative AI arrived, not as a lab toy but as a mandate. "Put copilots everywhere," leadership said. "Start with maintenance, then procurement, then the call center, then engineering change orders."
The main advantage of going the Multi-Cloud way is that organizations can "put their eggs in different baskets" and be more versatile in their approach to how they do things. For example, they can mix it up and opt for a cloud-based Platform-as-a-Service (PaaS) solution when it comes to the database, while going the Software-as-a-Service (SaaS) route for their application endeavors.
