AI Adoption Specialist · E2M Solutions

AI tools are easy.
Adoption is the work.

I help agencies and companies turn AI tools into systems their teams actually use—by connecting the workflow, technology and people around the work.

See how I work Read my field notes

Ahmedabad, India · Working with teams across the US, UK, UAE and beyond

The work, simplyAI adoption · E2M

What I walk intoMessy work.Scattered tools. Repeated effort. Unclear ownership.

My roleTranslate → Align → Enable

What we createAI people use.A clear workflow, a reliable system and a team habit.

I connect the business problem, the build and the people around it.

5+years building production AI

50+AI and automation projects delivered

200+government professionals trained

Sep ’25AI Adoption Specialist at E2M

01Who I am

I’m not a pure builder.
I’m not a pure strategist.
I sit in between.

My edge is translating between clients, business problems, internal delivery teams and engineers.

I have spent more than five years building production AI and automation across agencies, fintech and operations-heavy businesses. Today, my job is wider: choose the right problem, shape the workflow, guide the build and make adoption real.

The fuller story behind the role

02Leadership & impact

I lead the system
around the work.

My responsibility is not only to shape what gets built. It is to create clarity, develop ownership, maintain the delivery standard and help useful change stick.

01Direction

Direction

I turn broad opportunities into priorities, useful scope, success criteria and a next move the team can act on.

02People

People

I hire, mentor and give people the context they need to grow into confident, independent owners.

03Delivery

Delivery

I make risks visible, remove blockers and keep quality, security and production readiness part of the conversation.

04Adoption

Adoption

I connect the system with ownership, operating practices, training and feedback so the change becomes daily work.

Recognition

E2M Black Label Award

Recognized for leadership, execution and meaningful impact.

I see the award as a standard to keep earning through stronger decisions, better support for the team and work that creates lasting value.

03The career arc

Four layers that shaped
how I work.

015.5 years

Build

Co-Founder · MindX Advisory

I learned to turn business problems into working automation systems—and to stay accountable for what happened after delivery.

022.5 years

Ship

AI Automation Engineer · Finanshels

I built production document-processing, consolidation and transaction systems where accuracy, exceptions and reliability mattered.

03200+ trained

Explain

Visiting Faculty · NFSU

I train Income Tax officers and visiting government officials on AI in investigation. It taught me that clarity is a technical skill.

04Now

Adopt

AI Adoption Specialist · E2M

I connect client needs, delivery teams and engineers so AI becomes part of the work—not another subscription beside it.

04What I do

When AI has to survive
past the demo.

I work across discovery, workflow design, rapid prototyping, production thinking and team enablement.

Find the real friction

I map the work as it actually happens: repeated effort, slow handoffs, scattered knowledge and decisions that depend on one person.

A focused problem worth solving

Design the better workflow

I define the trigger, inputs, judgement points, ownership, review path and outcome before choosing the technology.

A workflow people recognize

Make it tangible

I prototype early, guide the build and expose the boring production realities—permissions, cost, security, exceptions and maintenance.

A useful version teams can test

Help it stick

I connect the system to SOPs, training, shared context, clear ownership and feedback so usage can become a habit.

Adoption that survives day 30

05Selected field notes

Specific lessons from
real implementation.

The useful truth usually appears after the impressive part—when cost, context, permissions, habits and ownership enter the room.

01Team adoption

The 11-person agency that did not need another AI tool.

Access was not the problem. The reset was shared Claude Projects, client context, SOPs, reusable Skills, one adoption owner and a weekly review.

Same subscription. A different operating system.

02Knowledge systems

RAG worked better when it disappeared into a tool the team trusted.

Instead of adding another dashboard, the team could query Drive knowledge, reuse SOPs and generate stronger drafts through MCP-based retrieval inside Claude.

The best interface can be the one already open.

03Decision support

A Warboard turned conversations into leadership visibility.

Heat level, services, funnel stage, client status and notes became one decision layer for agency and prospect conversations—not another pile of transcripts.

AI’s deepest value is often a better decision.

04Production reality

A small API detail changed the commercial answer.

A SEMrush site-health query could consume roughly 10K API units. Across 29 sites, the technically possible solution needed a financially sensible design.

Production decides whether a demo survives.

06What I believe