Agentic AI is the buzzword of the moment. According to The Future of Enterprise AI Agents report by Cloudera, 96% of enterprise IT leaders plan to expand their use of AI agents within the next 12 months — with half aiming for organization-wide deployments.
But before jumping on the AI bandwagon, it’s important to cut through the hype and ask yourself a few critical questions:
✅ Is the task complex enough?
→ If the task is structured, repetitive, and well-defined, a rules-based workflow might deliver faster and more reliable results.
✅ Is the task valuable enough?
→ High-volume, low-value tasks (like simple data entry) may be better served by Robotic Process Automation (RPA) bots rather than AI agents.
✅ Are all the steps feasible?
→ While full automation is ideal, it’s often more practical to reduce scope or introduce human-in-the-loop validation where needed.
✅ What’s the cost/implication of error?
→ If errors are costly or hard to detect, prioritize safer use cases first. AI agents work best where risk is low and recoverability is high.
💡 AI agents aren't a silver bullet. Applying them to every use case is like wielding a hammer and seeing every problem as a nail. Use the checklist above to make sure your use case is both technically sound and commercially viable before investing time and resources.
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