Define the value thesis and agent fit

Before you talk architecture, vendors or model choice, you need crisp alignment on what you are trying to improve and why an agent, not just a chatbot, is the right mechanism. This prevents deploying autonomy where simple assistance or deterministic automation would be safer and cheaper.

Start with the why

Agentic AI is not a strategy; it is a capability that must be justified in business terms:

• Revenue: better conversion, faster onboarding, more effective sales coverage.
• Cost-out: fewer manual handoffs, less back-office effort.
• Cycle time: shorter lead times in incident response, procurement and approvals.
• Risk reduction: fewer compliance misses, better auditability, policy enforcement.
• Experience: faster customer resolution, better employee workflows.

Is the process agent-shaped?

A good agent candidate has four traits:

• Multi-step: it requires sequencing, branching and follow-ups.
• Tool-heavy: it depends on systems such as ITSM, CRM, ERP, BI and databases.
• Policy-bound: rules, approvals and guardrails matter.
• Measurable: success and failure can be defined end to end.

Be explicit about what you are building

• A copilot assists a human inside an app; the human remains the executor.
• An automation is a deterministic workflow or RPA with fixed logic.
• An agent can plan and act across tools, under constraints and policies.

If you can't articulate why you need autonomy, you probably don't.