05/30/2025
I have a confession to make. 🫣
One of my guilty pleasures is... *drumroll please*
..Watching old corporate films about technology from the 50s to the 90s on YouTube.
Yeah, I know, a bit weird and super nerdy 🤓 but whatever, that's me.
Most people today don't really think about how things used to be done, they just live in the present. But I love imagining myself back in that world (minus the cigarette smoke) and how amazing the new technology was to them.
Recently I watched an IBM promo film from 1955 about one of their early computers,
the EDPM (Electronic Data Processing Machine).
*Link will be pinned in the comments if you're interested.
The story starts with the way things were (completely paper-based), and then showed how these manual tasks could be computerized and then centralized.
Sometimes we forget how bad these archaic paper-based systems were for accurate record-keeping. If you don't know how many widgets you have, and how many have been sold, how can you make any projections for the future?
Decision-makers were often working on information that was at least a few days to a few weeks out of date.
The computer they showed was revolutionary because it allowed management decisions to be made based on more up-to-date information than previously.
This got me thinking about how modern AI tools can help business leaders to make better decisions.
-> No more using gut feel to figure out how much to order
-> No more throwing darts at a board to determine demand
Business leaders can now use their own data, combined with the deep research capabilities now in many AI tools, to get more accurate answers to their most pressing decisions.
This is fantastic, and I highly recommend doing it, but when you start feeding your data into an AI, you need to make absolutely sure you know a few things:
1. Where is that data going
2. What is it going to do with it
3. Who will have access to it
Is it going to train on it and then spit it out to someone else, potentially even a competitor?
If you're using AI to help with decision-making, some of this data might contain confidential business plans, intellectual property, customer data, the list goes on.
This is why it's so important to have a well thought out AI strategy for your organization, rather than letting people have a free-for-all with an AI tool they choose.
An AI Strategy does a few things:
-> Identifies what areas of the business can benefit most
-> Defines what AI tool(s) employees are permitted to use
-> Ensures they have the right account type that protects your data
-> Trains them on how to use the tool most effectively (this is key for engagement)
-> Helps them understand why using AI the right way is important (and the risks!)
Does your organization have an AI Strategy yet?
I'd bet dollars to donuts at least some of your staff are using it already for their work, but without your approval, zero oversight, and guess what?
You're assuming literally all the risk of it.
Agree? Let me know in the comments.
^Geoff
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