Was GenAI was useless until Agentic AI ?

For the last few years, I’ve been deeply involved in bringing AI into real, day-to-day enterprise workflows. And if I’m completely honest, the early days of GenAI inside corporate environments were… underwhelming.

Not because the technology wasn’t impressive.
But because businesses couldn’t see a path to real value.

When I first started proposing GenAI-powered workflows inside our organization, the reaction from stakeholders was predictable:

• “It sounds cool, but what business value will it actually create?”
• “Will this justify the integration effort?”
• “Can we trust a large language model with real decisions?”

And I understood their concerns.
Early GenAI — as powerful as it was — stopped at conversation.

It couldn’t pull live data from cross-functional systems.
It couldn’t understand deep business rules.
It couldn’t execute tasks autonomously.
It couldn’t take responsibility for decisions.

In the enterprise world, every critical decision still needed a dashboard, because dashboards collect real data, enforce governance, and give decision-makers control.

That limitation shaped my early thinking:
GenAI alone is not the solution.
GenAI plus real-world context is.

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The Real value geneartor: Agentic AI

Everything changed when I began exploring Agentic AI frameworks.

For the first time, we had a way to:

• connect GenAI to ERP, CRM, pricing tools, and market feeds
• let AI read rules, constraints, and internal guidelines
• enable reasoning across multiple trusted sources
• allow AI to take actions, not just generate text
• create traceable, auditable decision paths

This was the missing link.

Agentic AI transformed GenAI from a “smart assistant” into a business interface.

And this is where my leadership journey took a sharper direction:
I realized that Agentic AI wasn’t just enhancing GenAI — it was enabling the part of GenAI that businesses actually needed.

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A Real Example: Autonomous Pricing Decisioning

One of the use cases I championed internally was pricing intelligence.

Without Agentic AI, determining the best price for a deal required:

• scanning market demand
• analyzing supply constraints
• interpreting company margin targets
• checking competitor benchmarks
• reviewing customer history
• reading regional economic signals

All of this existed — but scattered across dashboards, sheets, and systems.

A manager had to manually stitch everything together
and still make an incomplete decision.

When we plugged this workflow into an Agentic AI approach:

1. The system pulled all data automatically.
2. It ran profitability simulations.
3. It checked internal pricing rules.
4. It validated competitor trends.
5. It generated a recommended price with explanation.
6. It could even execute the next action — create a quote or notify the sales team.

For the first time, AI didn’t just give answers; it took responsibility.

That’s when leadership started to see GenAI — finally — as a true value creator.

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What I Learned Leading These Transformations

Through these journeys, I’ve realized something important about GenAI in the enterprise:

✔ GenAI is intelligence.

✔ Agentic AI is impact.

GenAI is the brain,
but Agentic AI is the body that interacts with the world.

Without the ability to retrieve data, take action, and reason across systems, GenAI becomes a highly creative — but isolated — thinker.

As soon as we connected it to pipelines, business rules, and operational systems, GenAI became:

• trustworthy
• useful
• measurable
• scalable
• and strategic

Exactly what enterprises have been waiting for.

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Why This Matters Now — and Why I’m Writing About It

We are at the start of a new technological era where:

• Workflows become conversations.
• Dashboards become optional.
• Decisions become faster and data-backed.
• AI becomes a collaborator, not a tool.

From my experience driving these transformations, I believe that Agentic AI is the key that finally unlocks GenAI’s true enterprise potential.

This isn’t a future prediction.
I’ve seen it happen in real workflows, with real business stakeholders, solving real problems.

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Final Thought

If GenAI was Phase 1 — excitement, experimentation, and curiosity —
then Agentic AI is Phase 2:

The era where AI becomes a decision-making interface for the enterprise.

And as someone who’s been building and advocating for this shift, I can confidently say:

We are finally entering the stage where AI moves from being a “nice to have” to a core driver of business value.