Which Company Systems Make Money When You License Data to AI Companies?
AITrainingDataBroker.com
Which systems
make money
from AI?
Email, files, chat, your CRM and accounting: which ones AI companies want.
Jimmy Lin
Which systems make money from AI?
Hello, everyone. Your company runs on a handful of systems, and AI companies do not value them equally.
In this video, I will show you which of your systems can make money, what 3 studies say about them, and what to export first.
The video
Full script
Hello, everyone. Your company runs on a handful of systems, and AI companies do not value them equally.
In this video, I will show you which of your systems can make money, what 3 studies say about them, and what to export first.
Open your laptop and look at the tabs you use all day: email, shared files, team chat, your CRM, and your accounting.
Each one holds a piece of how your company works, and side by side they tell one job, from the first request to the final payment.
That is what AI companies are shopping for, and it is why some of your systems earn far more interest than others.
I'm Jimmy. I have worked in data at Fortune 500 companies, as a data analyst, a data engineer and a software engineer, and I am trained in data science. I am also a Canadian military veteran, where I specialized in data analysis and reporting.
Are you selling your data? We are your broker and technical advisor. We get you the best price, and we guide your team through the technical side, so your data stays private.
Are you buying data for an AI lab? We find the right data for you and see it through to delivery, so you can focus on advancing AI research.
First, an honest point: not every system pays the same.
A system that is just a list of facts, like a price list or a contact list, shows very little about how people think.
A system that shows the back and forth and how it ended, like an email thread or a support ticket, shows how the work really gets done.
So the question for each of your systems is how much of the story it holds.
Start with email, because that is where most decisions get made.
A 2012 report from the McKinsey Global Institute found that knowledge workers spend up to 28% of their week on email.
Researchers have also used email this way for 20 years: the Enron email collection, about 500,000 emails from roughly 150 mostly senior managers, was described in a 2004 study by Klimt and Yang, and it has been used in research ever since.
A thread keeps the request, the pushback and the final answer in one place.
Next is team chat, which shows problems being solved one step at a time.
In 2015, Lowe and colleagues published the Ubuntu Dialogue Corpus: almost 1 million 2-person chats, with more than 7 million messages, where people helped each other fix technical problems.
It was built to train and test AI that holds a conversation.
Your own team chat is the same kind of material, with the problems of your trade in it.
Shared files are your paper trail: quotes, specifications and contracts.
The most useful part is often the versions, because when version 2 replaced version 1, the change shows what the customer pushed back on and what you agreed.
A final file only shows how things ended, while the earlier versions show how it got there.
Your CRM, the system that tracks your customers and deals, holds something hard to find anywhere else: why a deal was won or lost.
The stage and the amount are just facts, but a note that says the customer left because the second quote came a week late is the part an AI company can learn from.
We strip out the personal details first, and the deal story stays.
Accounting closes the story, because it shows what was finally agreed and what got paid.
On its own, an invoice is a list of numbers.
Next to the email, the quote and the CRM note, it shows whether the work ended well, which is a lesson an AI company can not get any other way.
Payroll and bank details are another matter, and those are never shared.
Now put the 5 together.
A customer emails a request, your team talks it through in chat, the quote goes through 2 versions in your files, the CRM marks the deal won, and accounting shows the payment.
Any one system is a piece, while all 5 together are one job told from start to finish, and that is the version AI companies look for.
You do not need all 5 on day one.
On your side, the main job is exporting what you have, and we guide your team through it.
Before any AI company sees anything, we strip out personal details, and payroll, bank details and private messages are never shared.
I work through what to include with you, and you make the final call.
So, which of your 5 systems tells the best story? Now you know where to look first.
If you run a company with 30 or more people, the data you already have could become a new revenue stream. You can find out if yours qualifies, for free, at AITrainingDataBroker.com.
If you have further questions, leave them in the comments, and I will answer them in the next video.
Thank you for watching, and I will see you next time.
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