u/CockpitToKeyboard

I work across two quite different professional worlds, aviation and AI training, and one thing that strikes me is how differently organisations approach new technology depending on their culture and risk tolerance. But does age demographic come into it as well??

In aviation, new procedures and tools go through rigorous evaluation before adoption, which makes sense given the safety implications. But even there, AI is starting to find its way into training, operations and planning. One example is flight planning software with AI that pieces together risks/threat from the morning weather, airport notices and aircraft manuals.

In the corporate world though, particularly in project management and software, I keep hearing the same reasons for slow adoption: data security concerns, lack of senior buy-in, no clear policy on which tools are approved, and teams who are left to figure out AI on their own…no training.

From a PM perspective I’m curious what the actual blockers are in your organisations. Is it a leadership problem, a training problem, or something else entirely?

The wave of AI related layoffs in tech and project management isn’t really about AI replacing humans. It’s about organisations realising they can get the same output with fewer people when some of those people are using AI effectively and others aren’t.

This is already happening in software development, where a developer using AI assisted coding tools can review, write and debug code significantly faster than one who isn’t. In project management, where status reports, risk registers and stakeholder communications that used to take hours are being turned around in minutes. In operations, finance, marketing, the pattern is the same everywhere.

The uncomfortable truth is that AI isn’t the threat. The colleague who figured out how to use it properly six months before you did is the threat.

The good news is that the actual skill involved isn’t complicated. It’s not about learning to code or becoming a prompt engineering expert. It’s about understanding how to give AI the right context, push back when the output isn’t good enough and iterate until you get something genuinely useful. Anyone can learn that with a bit of deliberate practice.

The people who will struggle are the ones who decided early on that AI was overhyped and stopped paying attention. That window for catching up is getting smaller.

What’s your experience of this in your industry? Are you seeing colleagues pull ahead because of how they’re using AI?

The wave of AI related layoffs in tech and project management isn’t really about AI replacing humans. It’s about organisations realising they can get the same output with fewer people when some of those people are using AI effectively and others aren’t.

This is already happening in software development, where a developer using AI assisted coding tools can review, write and debug code significantly faster than one who isn’t. In project management, where status reports, risk registers and stakeholder communications that used to take hours are being turned around in minutes. In operations, finance, marketing, the pattern is the same everywhere.

The uncomfortable truth is that AI isn’t the threat. The colleague who figured out how to use it properly six months before you did is the threat.

The good news is that the actual skill involved isn’t complicated. It’s not about learning to code or becoming a prompt engineering expert. It’s about understanding how to give AI the right context, push back when the output isn’t good enough and iterate until you get something genuinely useful. Anyone can learn that with a bit of deliberate practice.

The people who will struggle are the ones who decided early on that AI was overhyped and stopped paying attention. That window for catching up is getting smaller.

What’s your experience of this in your industry? Are you seeing colleagues pull ahead because of how they’re using AI?