Cloud & AI for the Enterprise
AI and cloud investments do not fail for the same reasons. Truly understanding their differences helps executives anticipate risks, prioritize interventions, and protect value. Why AI ROI fails AI initiatives are highly dependent on people, process, and data quality. Common failure points include: AI ROI is fragile early in the lifecycle and requires careful adoption … Read more
Enterprise AI and cloud initiatives often fail not because of technology, but because critical value drivers are overlooked. Understanding these failure patterns helps executives avoid common pitfalls and increase the likelihood of measurable ROI. 1. Misaligned Objectives Many initiatives start without a clear connection to business outcomes. Common issues include: Without alignment, even technically successful … Read more
Cloud initiatives often fail not because the technology is flawed, but because value is not captured across the full lifecycle of investment. The Cloud Value Loop shows the continuous cycle through which cloud spend drives measurable outcomes, and where inefficiencies or misalignment can erode ROI. Stage 1: Investment Planning Every dollar spent on cloud should … Read more
Enterprise AI and cloud investments rarely fail because the technology does not work. They fail because value is measured incorrectly. When metrics are misaligned, organizations mistake activity for progress, scale initiatives that never pay off, and lose confidence in programs that could have delivered real returns. Measuring AI and cloud ROI is not about documenting … Read more
Enterprise leaders are investing heavily in cloud and AI — yet many still struggle to answer a basic question: What measurable business value is this spend delivering? Not projected value.Not pilot success.Not vendor promises. But outcomes that can be defended in budget reviews, board discussions, and long-term strategy decisions. The Enterprise AI & Cloud Value … Read more