Your 3-Step Agentic AI Checklist to Success

The Noise: Agentic AI is cutting white-collar roles en masse

The Signal: You Can’t Automate What You Don’t Understand

It goes like this: your organization has an AI mandate. You need to make AI “fit” a solution so you can call it AI-powered.

However, we cannot implement AI agents without understanding the business process they’re meant to execute.

It sounds obvious, but this remains the #1 reason most enterprise AI projects stall, or worse, go live with no measurable impact.

📊 88% of AI projects DON’T make it into production (CIO).

Now, zoom in on Agentic AI, where agents interact with other agents or humans to complete a process. The success rate? Even lower. CTO Magazine recently warned that Agentic AI deployments often “work just well enough to disappoint” (ctomagazine.com).

To say we’re early is an understatement.

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This actually happened this week. I participated in a multi-day Agentic AI workshop with organizations in a highly regulated sector. The twist? We started with the solution first. Build an agent-to-agent solution. It served as a forcing function to surface genuine case fit. Because here’s the truth:

Most organizations don’t know where to apply AI.
Yet almost all of them feel the pressure to do it.

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💡 How we cracked the use case challenge

Over 3 days of whiteboarding and structured iteration, here’s the winning approach:

1. Reality‑check AI literacy
   Listing “Agentic AI” associations surfaced gaps, critical before ideation.

2. Map collaborative human processes
   We targeted multi‑participant workflows, where agentic AI can truly scale human interaction.

3. Stress‑test for pain & relevance
   Asking a lot of questions is the key. At every turn, you want to ensure the processes identified have enough pain in the human interaction to make it a compelling use case for the business.

4. Shortlist 2 priority use cases
   From dozens to two.

5. Drill deep on each:

   • Clear Problem Statement

   • Defined Business Benefit

   • Documented current As-Is Architecture

   • Sketched To-Be with agent handoffs

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📌 Another insight: our participants repeatedly defaulted to tech. We had to pause and push:

“First, show me the process as it exists today. Forget AI.”

Only then could we say: “Where might an agent augment?”

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✅ Final takeaway:
Even if you’re given a hammer, don’t hunt for nails. Start with:

1. A clearly documented problem

2. The architecture that delivers it

3. Quantified business value

Then decide: Is Agentic AI the right tool? Maybe AI agents are not the answer. All comes after clarity.

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Save this if you're building enterprise AI products.
Share it with anyone starting from tech instead of process.

Let’s stop worshiping the solution and start understanding the process behind it.