Arunava Chakravarty Blog | Programme Governance & IT Insights

And the practical fixes that actually work "Projects do not collapse suddenly. They deteriorate slowly — and almost always, governance is where the rot begins." Globally, nearly one in four projects fails to meet its objectives — not because of the technology, not because of the team, but because of the governance framework holding it all together. After three decades working in enterprise technology delivery, one pattern emerges with striking consistency , the seeds of proj

In today’s business environment, complex projects cannot be managed effectively through spreadsheets, static reports, and intuition alone. Teams need faster visibility, earlier warnings, and better decision support. This is where AI-driven project risk management becomes valuable. By combining cloud infrastructure, machine learning, automation, and generative AI, organizations can move beyond reactive issue handling and build a system that continuously monitors project health

Large projects rarely fail because teams lack skill or intent. They fail because coordination does not scale. Manual follow-ups. Subjective reporting. Emotional escalations. As complexity grows, governance collapses under its own administrative weight. Automation is not about software. It is about embedding discipline into the system itself. Why traditional project tracking fails at scale In most real organisations: Follow-ups depend on individual discipline Status reporting

The Case for Strategic Transformation In many high-stakes IT environments, Communication frequency has become a substitute for governance quality. Traditional governance is based on the mistaken assumption that frequency is everything—the belief that more meetings, more slide decks, and more updates equate to better control. In reality, weekly, monthly, and quarterly forums are legacy constructs that provide a trailing, post-mortem view of performance. True strategic transfor