To build on Michi Trota's excellent point about using genAI, and to zoom out:
I question anyone who screams that people will be "left behind" for not adopting genAI.
Seriously. How could they possibly know this?
They might feel AI's potential. They can want it to take off. But that's as far as it goes. Time will tell.
No one knows for sure which companies will benefit from genAI in the long run, nor do we know specifically how they'll benefit.
I've worked in the tech sector since the Dot-Com era, with a focus on (The Field We Now Call) AI since the early days of Big Data and predictive analytics. Based on my career experience and decades of emerging-tech history, it stands to reason that the gains from genAI will be unevenly distributed. Some companies will win big, some will lose big, and many will sit somewhere just beyond "it's made things slightly better."
And this is an even bigger question mark with genAI, since the technology has seen far more excitement than actual, concrete results.
So no, you won't necessarily get "left behind" because you didn't rush into genAI. But you might hurt yourself if you rush into that dark room just because someone is yelling at you. Hasty, haphazard genAI adoption may give you the illusion of progress while actually setting yourself up for failure.
Now, would I encourage companies to explore genAI? Under the appropriate circumstances and frameworks, yes. That would mean:
developing AI literacy (to understand what this technology can/cannot do)
mapping those genAI capabilities to your business model and challenges (devising a detailed AI strategy), and
evaluating AI projects for upside opportunities and downside risk exposures
treating those projects like the experiments they are until they've proven themselves out
(Longtime followers will recognize these as the same tips I post every few months. And I'll keep posting them as long as they still add up.)