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.

Decision guide for assessing whether an AI agent is the right solution

💡 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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