Case Study: Dina Mukherjee | AI Essentials Workshop

About the Founder and the Organisation

Cininfo is a global community and incubation platform for filmmakers, bringing together creators from different parts of the world to learn from industry experts and participate in structured programs that enable them to make films. The organisation is deeply people-driven, relying on connection, collaboration, and active engagement rather than scale-through-technology alone.

As founder, Dina Mukherjee is responsible not just for vision, but for the day-to-day effort of keeping the community running—program coordination, communication, follow-ups, and operational continuity.

In such setups, time is the most constrained resource.

The Context

Cininfo had been running successfully for three years, powered largely by human effort.

The work was meaningful—but heavy. Many operational tasks were repetitive, manual, and necessary, even if they didn't directly contribute to creative or strategic outcomes. Until recently, these were simply accepted as "part of the job."

AI, in this context, felt distant—either too technical, ethically confusing, or limited to surface-level use cases like messaging and drafting.

The Real Problem

The challenge wasn't community-building—it was operational drag.

Before the workshop:

• A large amount of time went into tasks that didn't require human judgment
• Automation felt inaccessible without technical skills
• AI tools were used sparingly and superficially
• The idea of building workflows or systems felt unrealistic

As a non-technical founder, Dina assumed certain efficiencies were simply out of reach.

Why the Workshop Mattered

The workshop didn't assume prior technical knowledge.

Instead, it:

Started from first principles—what AI, machine learning, and deep learning actually mean
Removed intimidation by explaining concepts in plain language
Showed how different AI tools serve different purposes, rather than being interchangeable
Made automation feel possible without coding

The learning curve felt approachable, not overwhelming.

The Shift During the Session

The biggest shift was psychological before it was technical.

For the first time, Dina saw that:

Not everything required human effort
Certain tasks simply weren't worth her time
AI could be used ethically and selectively, without compromising values
Automation didn't require building complex systems from scratch

A simple analogy helped cement this understanding: different tools, like different cars or clothes, are meant for different needs.

"Today is the first time I felt that I don't have to work so hard—not in building the community, but in doing things which I can just automate."

— Dina Mukherjee

What Changed After

Post-session, Dina walked away with:

A clear understanding of how tools like ChatGPT, Perplexity, and Gemini differ

Confidence in using AI for automation—not just content

An understanding of prompts and how to structure them

A new belief that systems she couldn't build earlier were now within reach

AI moved from being a curiosity to a lever.

The Outcome

The immediate impact was clarity and confidence:

Time freed up for higher-value, creative, and strategic work

Reduced mental load around repetitive tasks

A shift from "doing everything manually" to "choosing what deserves attention"

Motivation to practice, build, and return for deeper learning

What stood out wasn't just learning—it was enjoyment.

Founder Takeaway

For non-technical founders, AI doesn't need to be intimidating to be useful.

This experience helped move from:

Manual effort Selective automation

Surface-level use Purpose-driven application

Assumed limitations Practical possibility

AI became a way to protect time, not replace values.

Why This Case Study Matters

This isn't a story about adopting AI for scale.

It's about recognising that not all work deserves human effort—and that clarity can be more powerful than technical depth.

For founders running people-centric organisations, that shift alone is transformative.

From Manual Effort to Meaningful Leverage: How a Community Founder Reclaimed Time with AI

Dina Mukherjee