AI Automation in My Workflow

When I first started experimenting with AI automation, it was just about writing scripts that could predict outcomes. But soon I realized the real power: letting AI take over repetitive workflows — email responses, lead qualification, content generation, daily reporting.

Photo by Xu Haiwei on Unsplash

Here’s the step-by-step journey of how I turned small AI experiments into full-blown automation pipelines.

1) Setting Up the AI Automation Environment I started by combining Python for logic and AI APIs for intelligence.

mkdir ai-automation && cd ai-automation
python -m venv venv
source venv/bin/activate
pip install openai schedule pandas smtplib

2) Automating Email Responses With AI

Instead of answering routine inquiries, AI drafts my replies.

import openai
import smtplib
from email.mime.text import MIMEText

openai.api_key = "YOUR_API_KEY"

def generate_reply(email_text):
    response = openai.Completion.create(
        model="text-davinci-003",
        prompt=f"Write a professional reply to: {email_text}",
        max_tokens=150
    )
    return response["choices"][0]["text"].strip()

def send_email(to, subject, body):
    msg = MIMEText(body)
    msg["Subject"] = subject
    msg["From"] = "[email protected]"
    msg["To"] = to
    
    with smtplib.SMTP("smtp.gmail.com", 587) as server:
        server.starttls()
        server.login("[email protected]", "APP_PASSWORD")
        server.sendmail("[email protected]", to, msg.as_string())

incoming = "Can you share the pricing details?"
reply = generate_reply(incoming)
send_email("[email protected]", "Re: Pricing Inquiry", reply)

3) Automating Lead Qualification AI helps me decide whether a lead is worth pursuing.

def qualify_lead(lead_info):
    response = openai.Completion.create(
        model="gpt-3.5-turbo",
        prompt=f"Classify this lead as 'hot', 'warm', or 'cold': {lead_info}",
        max_tokens=20
    )
    return response["choices"][0]["text"].strip()

lead = "CEO of mid-sized software company looking for AI consulting"
print("Lead Score:", qualify_lead(lead))

4) Automating Daily P&L Reports Instead of crunching numbers manually, AI and Python summarize my trading results.

import pandas as pd
from datetime import datetime

df = pd.read_csv("trades.csv")

summary = df.groupby("symbol").agg({
    "profit": "sum",
    "volume": "sum"
}).reset_index()

summary.to_csv(f"daily_report_{datetime.now().date()}.csv", index=False)
print("✅ Report Generated")

5) Automating Content Generation AI now helps me generate blog drafts, captions, and even code snippets.

def generate_content(topic):
    response = openai.Completion.create(
        model="gpt-3.5-turbo",
        prompt=f"Write a LinkedIn post about {topic}",
        max_tokens=200
    )
    return response["choices"][0]["text"].strip()

print(generate_content("AI in small business automation"))

6) Automating Data Cleaning AI can clean and normalize datasets before I even analyze them.

raw_data = "Customer names: J. Smith, John Smith, Jon Smyth"
response = openai.Completion.create(
    model="text-davinci-003",
    prompt=f"Clean and standardize this data: {raw_data}",
    max_tokens=100
)
print(response["choices"][0]["text"].strip())

7) Automating Social Media Scheduling

With AI-generated captions and a scheduler, my social accounts run themselves.

import schedule, time

def post_to_social():
    caption = generate_content("AI tips for entrepreneurs")
    print("📢 Posting:", caption)

schedule.every().day.at("10:00").do(post_to_social)

while True:
    schedule.run_pending()
    time.sleep(60)

8) Combining All Into a Single AI Automation Pipeline Now, I have a master script that:

• Replies to emails
• Qualifies leads
• Generates P&L reports
• Writes social posts

And it runs daily on autopilot.

Final Thoughts

AI automation has moved me from working in my business to working on my business.

• Emails don’t drain me
• Leads are filtered before they reach me
• Reports are always ready
• Social media runs on autopilot

And the best part? Each automation I add makes the whole system smarter.

Read the full article here: https://ai.plainenglish.io/ai-automation-in-my-workflow-55c45e45f734