MIT AI Technology Review·
In finance departments that have long been defined by precision and control, AI has arrived less as a neatly managed upgrade than as a quiet insurgency. Employees are already using it while leadership races to impose structure, governance, and strategy after the fact. The result is a paradox: one of the most tightly regulated functions…
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How enterprises scale AI: from early experiments to compounding impact through trust, governance, workflow design, and quality at scale.
NATO allies are openly questioning whether the US should still lead the alliance following Trump’s decision to launch strikes on Iran without consulting them. NATO allies are questioning US leadership after Trump launched strikes on Iran without consulting the alliance,…
As agents move past demos and into enterprise workflows, organizations are confronting the governance, infrastructure and operational problems posed by more autonomous AI systems.
Former Polkadot insiders report lack of direction and support from leadership, treasury overspending, and even failure to pay contributors for their work.
Enterprises are experimenting with AI agents internally first, using smaller testing teams and strict governance before deploying customer-facing applications.
When it comes to AI adoption, some institutions lead with executive strategy, others with faculty experimentation, but all are working through governance, curriculum updates and faculty training.
AI helps businesses become more efficient. But does it make leaders less connected?
