Purshottam Purswani

Most organisations don't have an AI problem. They have a clarity problem.They've invested in the tools. They've run the pilots. They've hired the talent. But somewhere between the strategy deck and production deployment, things stall — the ROI never materialises, the board loses patience, and the business quietly moves on to the next initiative.That gap between experimentation and enterprise-grade delivery is what I've spent 20+ years closing — first as an engineer and architect, then as a practice leader, and now as Head of Data & AI across Asia-Pacific, Middle East, and Africa at Atos.The outcomes I'm most proud of: 4x practice revenue growth ($5M to $20M in 18 months), a €100M cloud and AI transformation for a government health department, a granted European patent in autonomous swarm intelligence (EP 4 432 038 B1), and recognition in the 2024 CTO World 100.What makes my experience transferable isn't the title — it's the range. I've built and scaled data and AI teams across Australia, India, Germany, Switzerland, and the Netherlands, across industries including government, healthcare, financial services, and manufacturing, across technology cycles from SOA and BPM through to cloud-native GenAI architectures. The ability to take an AI strategy from a boardroom whiteboard to production systems that actually move metrics — that's the through-line.More recently, my focus has expanded into the architecture of responsible AI at enterprise scale — designing ISO/IEC 42001-aligned AI Management Systems, AI risk and controls frameworks, and governance operating models that allow organisations to move from experimentation to production without compromising regulatory trust, ethics, or accountability. AI governance isn't a compliance exercise. It's what separates AI transformation from AI theatre.