March 2026 AI Insights

Last month we said the constraint wasn’t the technology, it was organizations. 

Now, the conversation has shifted again. The question we keep hearing isn’t what can AI do, but how do we deploy it at scale? Not pilots or experiments, but real adoption across the entire organization. 

The reason is simple, it’s because the capability line has already been crossed. 

AI systems are now completing real work, navigating tools, producing outputs, and in some cases improving themselves. This is no longer theoretical; it’s already happening in production. 

Organizations are responding on multiple fronts: investment in AI is accelerating, alongside clear shifts in organizational structures and approaches to performance measurement. 

However, most are running into the same issue. While individuals are becoming significantly more productive, organizations aren’t. One part of the system speeds up, the rest doesn’t and new bottlenecks appear. 

This gap is now the defining challenge. 

The full March AI Insights explores what this means in practice, from the move to agentic work, to how organizations are restructuring and why scaling beyond individual productivity is proving harder than expected. 

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