Wait… Really? How AI Workflows Automate Email, Data, and Scheduling

Most organizations don’t have a data problem. They have a translation problem.
Information lives in spreadsheets. Communication happens in email.
Scheduling lives in calendars. And every time something needs to happen, someone has to manually connect the dots.

Open the spreadsheet.
Filter the rows.
Copy the emails.
Draft the message.
Schedule the meeting.

It’s not difficult work.

It’s just unnecessary friction.

In this video, I walk through a simple AI-powered workflow that shows what happens when we let people express intent in plain language—and let systems handle the coordination behind the scenes.

The Core Idea: From Tools to Flow

The goal of this workflow isn’t automation for automation’s sake.

The goal is flow.

Instead of asking people to navigate multiple tools, the system listens for natural language requests like:

• “List the people with the title Marketing Director”

• “Email people in NYC about the upcoming event”

• “Schedule time with Jamie at 2 PM New York time”

Each request triggers a real business action—without opening a spreadsheet, email client, or calendar.

What changes isn’t the data.

What changes is how work moves.

What the Workflow Enables

In the video, I demonstrate three common business scenarios:

1. Conversational Data Access

A spreadsheet becomes something you can talk to.

Instead of building reports or filters, the system interprets natural language, understands which fields matter, and returns only what’s relevant.

This turns static data into an active resource.

2. Targeted Communication in One Step

A single sentence can:

• Filter contacts by location

• Pull the right email addresses

• Generate a message

• Send it automatically

What normally takes multiple tools and several minutes becomes one clear expression of intent.

This is where AI moves beyond writing assistance and starts supporting real operations.

3. Scheduling Without Back-and-Forth

Scheduling often looks simple—but it involves a lot of hidden complexity:

• Finding the right person

• Parsing dates and times

• Handling time zones

• Creating calendar events

In this workflow, all of that happens from a single natural language request.

The result is a real calendar event—created accurately and immediately.

The Software Behind the Scenes

While the video focuses on what the workflow enables, here’s a high-level look at the tools working together behind the scenes:

• Make.com
  Acts as the orchestration layer. It connects systems, interprets intent, and coordinates actions across tools.

• OpenAI (ChatGPT)
  Interprets natural language input and translates it into structured actions the workflow can execute.

• Google Sheets
  Serves as the data source for contacts and attributes like role, location, and email.

• Telegram
  Provides a lightweight, conversational interface for interacting with the workflow using plain English.

• Gmail
  Handles automated, targeted email delivery based on filtered data.

• Google Calendar
  Creates real scheduling events with correct dates, times, and time zones.

What matters most isn’t the individual tools—it’s how they’re designed to work together as a system.

Why This Matters for Real Teams

This pattern solves a problem many teams struggle with:

How do you let non-technical users:

• Ask questions of data

• Communicate with the right people

• Coordinate schedules

Without forcing them to become tool experts?

The answer isn’t more dashboards or more training.

It’s designing systems that respect how people already think and communicate.

My Approach to AI Workflows

I don’t design AI workflows as demos or experiments.

I design them as delivery systems—practical, reliable, and grounded in how work actually happens inside organizations.

AI works best when it reduces friction, not when it adds complexity.

When done well, it doesn’t replace people.

It supports them—by keeping their focus on judgment, decisions, and outcomes.

If you’re interested in seeing how this kind of workflow could apply to HR systems, CRMs, support operations, or sales workflows, the same pattern holds.

Plain English in.
Real business action out.

That’s how I think about AI in real delivery environments.

— Nan Ross