Editing Making Money with AI Automation

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If you’ve been learning AI for a while, you’ve probably wondered: how do I actually make money with this? That was the exact question I asked myself when I first started building AI projects. The good news? You don’t need to invent the next ChatGPT to earn. What worked for me — and what will work for most developers — is focusing on automation projects that save time for businesses and individuals.
Here are 8 practical, battle-tested ways I’ve used AI and Python to generate income. Each section includes code and the reasoning behind it.



1) Resume Optimization as a Service
Job seekers pay for help tailoring resumes. With AI, you can do this at scale.
<pre>
from openai import OpenAI

client = OpenAI(api_key="your_api_key")

def optimize_resume(resume_text, job_desc):
    prompt = f"""
    Adapt this resume to better align with the job description. 
    Highlight relevant skills, experiences, and use keywords.
    Resume: {resume_text}
    Job: {job_desc}
    """
    response = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": prompt}],
        temperature=0.2
    )
    return response.choices[0].message.content

print(optimize_resume("Python dev with 3 years experience", "Looking for ML Engineer"))
</pre>
Monetization idea: offer resume tailoring on Fiverr/Upwork. Charge per resume.



2) YouTube Video Summaries for Creators
Creators need quick content summaries for SEO and engagement. You can build and sell tools that auto-generate them.
<pre>
from youtube_transcript_api import YouTubeTranscriptApi
from openai import OpenAI

client = OpenAI(api_key="your_api_key")

video_id = "Ks-_Mh1QhMc"
transcript = YouTubeTranscriptApi.get_transcript(video_id)
text = " ".join([t["text"] for t in transcript])

summary = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": f"Summarize:\n{text}"}]
)

print(summary.choices[0].message.content)
</pre>
Monetization idea: sell it as a subscription service for YouTubers.



3) Automating Business Reports
Small businesses often struggle with monthly reports. Automating Excel + AI analysis is worth real money.
<pre>
import pandas as pd
from openpyxl import Workbook

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

summary = df.groupby("product")["revenue"].sum()

wb = Workbook()
ws = wb.active
for row in summary.items():
    ws.append(row)

wb.save("sales_report.xlsx")
</pre>
Monetization idea: set up recurring reporting systems for businesses. Charge monthly.



4) PDF Sorting for Professionals
Lawyers, researchers, and consultants sit on mountains of PDFs. Offer AI-based organization.
<pre>
from sentence_transformers import SentenceTransformer
from sklearn.cluster import KMeans
import fitz

model = SentenceTransformer("all-MiniLM-L6-v2")

def extract_text(path):
    doc = fitz.open(path)
    return doc[0].get_text()

abstracts = [extract_text("contract1.pdf"), extract_text("contract2.pdf")]
embeddings = model.encode(abstracts)
labels = KMeans(n_clusters=2).fit_predict(embeddings)

print(labels)
</pre>
Monetization idea: build a SaaS to organize PDFs by topic.



5) Social Media Automation
Content scheduling and auto-captioning are goldmines. With AI, captions basically write themselves.
<pre>
from openai import OpenAI

client = OpenAI(api_key="your_api_key")

caption = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Write a fun caption for a travel photo in Paris"}]
)

print(caption.choices[0].message.content)
</pre>
Monetization idea: sell content automation packages to agencies.



6) AI-Powered Chatbots for Websites
Businesses are always asking for “customer support automation.” Delivering it is simpler than most think.
<pre>
import gradio as gr
from openai import OpenAI

client = OpenAI(api_key="your_api_key")

def chat(message, history):
    res = client.chat.completions.create(
        model="gpt-4o-mini",
        messages=[{"role": "user", "content": message}]
    )
    return res.choices[0].message.content

demo = gr.ChatInterface(fn=chat, title="Customer Bot")
demo.launch()
</pre>
Monetization idea: charge businesses a setup fee + maintenance.



7) Localized Translation Tools
AI translation tools are strong — but niche, industry-specific ones are more valuable.
<pre>
from openai import OpenAI

client = OpenAI(api_key="your_api_key")

text = "This is a medical research document about heart disease."
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": f"Translate into Spanish:\n{text}"}]
)

print(response.choices[0].message.content)
</pre>

Monetization idea: create translation services for healthcare, legal, or finance.



8) AI Personal Assistants for Freelancers
Freelancers love productivity hacks. Offer personal AI dashboards that integrate notes, tasks, and summaries.
<pre>
from sentence_transformers import SentenceTransformer
from sklearn.metrics.pairwise import cosine_similarity

docs = ["Meeting notes on client A", "Proposal draft for project B"]
model = SentenceTransformer("all-MiniLM-L6-v2")

query = "Show me project B notes"
query_embed = model.encode([query])
doc_embeds = model.encode(docs)

print(docs[cosine_similarity(query_embed, doc_embeds).argmax()])
</pre>

Monetization idea: sell custom “personal assistants” for freelancers.



Closing Thoughts

The easiest way to make money with AI isn’t building the next OpenAI. It’s finding boring, repetitive tasks people hate and automating them.
Pro Tip: People don’t pay for “AI models.” They pay for saved time and reduced stress.

If you want to monetize your skills, start by asking: what’s costing someone time right now? Then build a quick AI-powered solution. That’s your first paycheck.

Read the full article here: https://medium.com/write-a-catalyst/making-money-with-ai-automation-ded9e87f8f13