From Basic AI Usage to Business Leverage: How a Managing Director Expanded AI’s Role Beyond Drafting

About the Leader and the Organisation

MT9 Automation operates in the automation and technology solutions space, where efficiency, responsiveness, and customer experience are tightly linked to business performance. As Managing Director, Hemant Gupta is responsible for ensuring that technology adoption translates into real operational value, not just incremental productivity gains.

In such organisations, AI familiarity is common. Strategic AI usage is not.

The Context

Before attending the workshop, Hemant and his team were already using AI—but narrowly.

AI was applied to writing emails, drafting customer communication, and preparing basic product information.

These use cases were helpful, but limited. AI existed at the edges of the workflow, not at its core.

The Limitation

The issue wasn’t lack of exposure—it was underutilisation.

AI was saving time, but not yet shaping outcomes.

• AI was treated as a productivity add-on
• Its role in customer experience wasn’t fully explored
• Opportunities to improve internal efficiency were unclear
• Tool awareness existed, but application breadth was narrow

What the Workshop Unlocked

The workshop expanded how AI was understood in a business context.

AI stopped being a helper and started looking like a capability multiplier.

• Multiple AI tools beyond conversational drafting
• Ways AI could enhance customer experience, not just communication
• Opportunities to improve efficiency across workflows
• A broader view of how AI can be embedded into business processes

The Shift in Perspective

The key shift was recognising that AI could influence:

• How customers experience the business
• How efficiently teams operate internally
• How scalable existing processes can become

“The session opened a lot of other opportunities that hadn’t been considered earlier.”

— Hemant Gupta

The Outcome

The immediate outcome wasn’t transformation—it was direction.

For MT9 Automation, this marked a transition from using AI to thinking with AI.

• Broader awareness of AI’s business impact
• Alignment between leadership intent and team learning
• A shift from limited use cases to exploratory application
• Commitment to continued learning and implementation