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The AI Briefing is your 5-minute daily intelligence report on AI in the workplace. Designed for busy corporate leaders, we distill the latest news, emerging agentic tools, and strategic insights into a quick, actionable briefing. No fluff, no jargon overload—just the AI knowledge you need to lead confidently in an automated world.
Today, I do a lot of work in
the RegTech field and helping
and advising companies when it comes to using
AI or digital transformation inside
of regulated environments,
FinTech, HealthTech, all those types of things.
One thing that I wanted to be able
to discuss with you today just briefly is
the use of AI inside of your organization
because there is a lot that we have
to think about when it comes to leveraging
AI on a regular basis, especially
when it comes to confidentiality agreements and who
owns the data.
Now, of course, when it comes to leveraging
AI models, everyone would like to be able
to think that they can just chuck a
spreadsheet full of company data
into your favorite chat GPT, clause, whatever,
and ask for a quick summary.
But as soon as you have done that,
if you don't have the right agreements in place,
you've suddenly breached a whole bunch of laws
and confidentiality clauses in
potentially many different customer contracts
because you've uploaded the data and
you no longer own the data.
It has gone to your favorite AI vendor
and at that point, you
basically own a copy of it because your
AI vendor now is going to train their
stuff from your model.
This is not new, of course,
for these vendors to be able to make
their money, they need more data.
And so depending on your agreements with
the AI vendor, you
will get different levels of confidentiality and
their commitment to not train off your data as an organization.
So what can you do about this?
Of course, there are many different things you
can do about this, but you have to
make sure that you have the right procedures
and policies in place.
One thing is when you're dealing with the
bigger vendors is making sure that you read
the contract properly because step
number one is read the contract.
Step number two can be like make sure
that if you're using a vendor but you
don't have a sort of global team
setup is to make sure that if there
is a switch to be able to switch
off vendors training off your data,
switch it off because last
time I checked, that was a pretty good
way of asking them to not do it
was by disabling it.
But of course, again,
you're still beholden to a vendor, that vendor
may or may not train off your data,
but also people inside your organization may not
switch and then you're still at risk of
capitulating to the
laws and regulations.
So the third option is using a framework
or a function that allows you to either
host a model or leverage a model that
is more under your direct control.
So when it comes to internal
use of LLMs, it may not be as
simple as signing up to anthropic
.com or chat GPT
and opening an account because what you might
want to be able to do is leverage
those models, but in a more constrained environment.
So we're talking about Microsoft
Foundry, AWS Bedrock, GCP Vortex,
and Databricks, for example.
If you're already a Databricks user, you can
leverage those models inside a Databricks and they're
not going to train the model
off your data because they're bringing the models
from external providers.
Of course, going back to what we were
saying the other day, you can, of course,
if you would so choose, then train models
off of your data so that it can
become more intelligent and answer more pertinent questions.
But that becomes something that you own and
a process that you manage.
And it is not an organization training
their own model off of your data for
no additional value to yourself.
And so, you know, if you're working in
regulated technology, just make sure before
you start uploading customer information to
your favorite AI model for a quick
summary, a quick check or any of that
type of stuff, just what happens to the
data that you upload, because
believe it or not, as soon as you
upload it, you may not own it.
So there we go.
A bit of food for thought, a bit
of something to do, a bit of homework
and go and check your own models and your agreements.
If you enjoyed this, I will be back
tomorrow with another AI briefing.
Thank you very much for joining me.
My name is Tom.
I will see you all soon.
Bye for now.