Quick snapshot from the job board this week:

Hubspot- Executive Assistant, CLO (Remote)
$96,000-$144,000

Nscale- Executive Assistant (NYC)
$115,000–$140,000

Gensyn- Executive Assistant (Remote)

These are pulled from the same system I use to track roles across 20+ platforms.

Instead of bouncing between LinkedIn, company sites, and random alerts, you can search everything in one place:

I’ve sat in a few leadership meetings over the past few months where the conversation around AI quickly turned into something else entirely, how teams are being hired and built.

Not in a theoretical “we should probably be thinking about this” kind of way either. These were real conversations about how teams are being structured, what roles need to look like moving forward, and who can actually operate in this next phase.

At one point the conversation shifted from “should we be using AI?” to “how do we make sure every team is staffed with people who are fluent in it?”

That’s when it really clicked for me. They weren’t talking about who can open ChatGPT and ask it to rewrite something, that’s table stakes now. The focus was on who understands how to use it to move work forward, to build, to think differently. Same tools, completely different bar.

If you look at where we were even a year ago, the focus was on prompting, how to ask better questions, how to get better outputs, how to use the tools more effectively. That was phase one.

Now we’re in a very different place. AI can generate headshots, help file your taxes, and build tools from scratch if you have enough curiosity to figure it out. The barrier isn’t access anymore, it’s how you think.

This is especially true for EAs. AI fluent operators are already being sought after in a market that’s competitive to begin with, same role, different expectations.

If that’s the direction hiring is going, then the role itself starts to look different. The work doesn’t disappear, but how you approach it does. Instead of starting with tasks, you start with the outcome:

Then you decide what should be handled by you and what should be handled by a system.

For example, instead of manually triaging your inbox every morning, you start thinking about how that decision gets made before you even open it, what’s urgent, what’s not, what needs your attention, what can wait. Same with meeting prep, instead of pulling context together from scratch every time, you start thinking about how that information gets surfaced automatically before the meeting even happens. Or weekly updates, instead of rebuilding the same summary over and over again, you start thinking about how that gets generated consistently without you starting from zero each time.

This isn’t just something happening in a few rooms. It’s starting to show up everywhere. More job descriptions are calling out AI proficiency, teams are being pushed to adopt it faster, and companies are investing in training not as a nice to have but as a requirement. The expectation isn’t that you’re experimenting with AI, it’s that you know how to use it as part of how you work.

Some people are still using it occasionally when they have time or when it feels helpful, others are building it into how they operate day to day. Same role, completely different output.

This isn’t just a shift in tools, it’s a shift in expectations, roles are already starting to change, EAs are being pulled into conversations around operations, systems, and how work actually flows across a team, it’s less about managing inputs and more about shaping outputs.

You’re seeing it in how work gets done day to day, inbox triage turning into prioritization systems, meeting prep turning into automated briefings, weekly updates turning into something that runs without being rebuilt from scratch every time.

The role isn’t getting smaller, it’s getting more leveraged!

And the market has already started to reflect that, according to this edX report on AI skill demand job postings requiring AI skills grew over 100% year over year in 2025, with more than 120000 postings in a single month alone.

This isn’t where things are going, this is already happening, the expectation isn’t that you’re experimenting with AI, it’s that you’re using it.

This is the part most people don’t want to hear…

You have to make time for this!

Not when things slow down, not when you get around to it, not when it feels convenient, the same way you make time for anything that’s good for you, this has to be treated the same way.

You drink water because you need it to survive, you don’t wait until you feel like it, you just do it. This is no different.

You don’t need to become an expert overnight, but you do need to start treating this like part of your job, not something extra. Because at this point it is.

And we’ll keep building on this together!

Every Wednesday, we’ll go deeper into how to actually use AI in your day to day work, what this looks like in practice, and how to start applying it. Friday issues will continue as usual.

We’re here for you. 🫶

When things start to click and flow without you overthinking it.

Full playlist linked here.