Multi-Agent Systems: When Splitting Work Across Agents Helps, and When It Multiplies Failure
Most tasks run better on one well-tooled agent. Multi-agent systems pay off only for parallel work, isolated context or independent checks.
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Most tasks run better on one well-tooled agent. Multi-agent systems pay off only for parallel work, isolated context or independent checks.
Where AI helps in hiring and HR, where legal risk concentrates, what NYC, the EU, Colorado, Illinois and California require, and which controls hold up.
AI spend is moving from central IT to business lines. That ties cost to outcomes but breaks controls built for an IT-held purse. The model that works.
What AI can take over in accounts payable, step by step from capture to payment, where the fraud risk grows, and which controls must stay outside the model.
The first agents trusted with company money will buy for the enterprise. Control moves from approval chains to policy as code and card-level limits.
Why AI assistants expose overshared data, how data classification fixes it, what to label first, and a 90-day plan for executives.
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