The effect of AI will not be equal
It depends what certain industries have been doing for the last 15 years.
I was flying to NYC last week when I noticed about 15 different airport wall display ads talking about AI. Various companies, such as IBM, monday.com, Cognizant, and others were claiming to revolutionize processes with AI. However, their campaigns never mentioned any industries that they were focused on, and it’s tough to understand the varying degrees of helpfulness per industry without booking a demo.
If that was intentional, so be it, I’m not trying to say that the VP of marketing at each of those companies is categorically wrong. It did get me thinking, though.
There is a common joke in the data science community that before LLMs 90% of “artificial intelligence” claims in products from companies was just linear regression. It’s obvious AI is a moving target, and it always will be. What AI was yesterday is not what it is today. Hell, people were probably calling Excel macros “AI” at some point.
How to tell who will change and who will not
Historically, not all industries have seen the same kind of transformation in data science.
As an example:
Finance
Retail
Manufacturing
Telecom
Healthcare
All industries have been radically changed by data science, and there is a commonality between them: the quality and amount of data that is available.
These industries:
Construction,
Hospitality
Agriculture
Have been slow to adopt meaningful change with process automation and artificial intelligence.
Why is that?
Looking at a commonality between the bottom 3 industries, these are largely manual labor industries with limited data on processes.
If you subscribe to the idea that artificial intelligence, automation, and robotics is process automation on steroids, then there just isn’t enough data to make informed decisions on opportunities to automate parts of their businesses. These decisions are usually expensive, and combined with the lower margins that these three industries tend to have, it’s a recipe for slow movement.
Artificial intelligence and automation will flourish in data-rich (on both quality and quantity) environments. So until better data capture methods can be created, these industries will be slow-moving.
There is promising movement, however!
The products transforming industries
Procore - Is a huge player that tries to make the project management portion easier. Hopefully, their product will evolve to collect data about on-the-job activities.
LEAF - in the Ag industry is trying to unify farm data to build and scale products quicker.
And PreciTaste in the hospitality/food service industry is trying to gather real-time insights for inventory and order accuracy.
It’s a promising space to be in, and if you think that data platforms are a saturated market, then it’s time to focus on niche industries that are struggling or slow to transform.
See you in 2 weeks to build your own bootstrapped resume analyzer!
— Prompter