Category: AI governance
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AI Governance Is Becoming a Reputation Issue. Where Are Communications Leaders?
AI governance shapes more than compliance. Katherine Morales, APR explains why communications leaders must help protect trust, credibility and reputation.
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Stop Building AI Agents Until You Understand the Work
Everyone wants an AI agent. But automating a workflow you don’t fully understand can simply make a bad process faster. Before organizations deploy agents, they need to determine what should remain human, where AI should assist, what should be automated, and how teams will actually work inside the new system.
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65% of Employees Want to Roll Back Workplace AI. The Tech Isn’t the Real Problem.
Employees are adopting AI faster than companies can adapt. Learn why AI change management, workflow redesign, governance and training must come next.
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Your AI Policy Is Just the Beginning. Now, Design How Work Gets Done.
AI governance goes beyond policies. Learn how teams can embed governance into Human + AI workflows through dialogue and intentional decisions.
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Top 10 Things Your AI Policy Should Include
An effective AI policy should help employees make sound decisions when AI shows up in real work. Here are 10 areas organizations should address—from tools and data to AI agents, transparency, records and human accountability.
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The Emerging AI Data Custody Problem: Why an AI Policy Isn’t Enough
Every time an employee uploads a document, analyzes data or asks AI to improve a draft, organizational information moves into an AI system. The question isn’t simply whether employees can use AI. It’s who has custody of that information, what happens to it next, and whether your governance practices follow the work.
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AI Governance Cannot Stand Still When AI Doesn’t
AI is changing faster than most organizational policies. As new models, AI agents, disclosure requirements and regulations emerge, organizations need to move beyond static AI policies toward a living governance practice that evolves with the technology and the work.