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With AI agents becoming an increasingly hot topic, I’ve shared several reports and articles on this subject over the past few months, including my previously curated list of five resources. While many of these resources delve into detail, it is helpful to have easy-to-read versions that distill common questions and answers about agentic AI. In this new article, the authors briefly answer nine key questions using excerpts from two recent MIT Sloan Management Review pieces: what AI agents are, how they differ from traditional AI tools, whether companies are seeing ROI, how agents communicate, what security gaps emerge, what data poisoning is, what prompt injections are, how organizations can strengthen security, and how accountability can be ensured when agents make critical decisions. As HR leaders and their teams learn more about AI agent capabilities, I suggest starting with foundational questions before diving into use cases by asking: What business problems are we solving where AI agents can help us perform work more effectively in our function and deliver stakeholder value? What evidence suggests an AI agent is the right solution? What business metrics or organizational outcomes (e.g., revenue, efficiency) would be most impacted? Will ROI be realized in the near term or over a longer period, and what value will be captured each year? One helpful tactic is to illustrate a side-by-side comparison of how a process (e.g., job requisition approval workflow) works today versus how it could look with AI agents. This visual makes the business case more compelling by showing the potential impact of AI agents on important business outcomes.
