Many have seen this headline, or one similar to it: “AI is coming for your job.” “White-collar work will never be the same.” Perhaps you read a recent article in the The Wall Street Journal suggesting that executives are starting to treat their staff differently, less as individuals, more as placeholders, due to AI. That is the article that prompted me to want to research this topic a bit better.

Here’s the thing: Many of us work in industries where AI is increasingly embedded into the products and services we market, sell, and deliver. I’m not an AI architect or engineer; I’ve taken training for various platforms, sat through demos, and worked on go-to-market and sales strategies for solutions that claim to harness its power.

What I’ve consistently seen—across clients, partners, and internal teams—isn’t a rush to replace people. It’s a push to equip them: streamline manual tasks, speed up decision-making, improve customer targeting, manage regulatory concerns, and reduce operational drag. But you wouldn’t know that from the headlines—or, increasingly, from the way some executives are talking. Instead of treating AI like a versatile toolset, they’re wielding it like a blunt instrument.

The Research: Are Jobs Really Being Replaced?
Based on my reading up on this topic, there’s plenty of credible research suggesting that the AI jobs apocalypse just isn’t materializing—at least not yet.

According to a March 2024 report from the OECD, while AI is expected to transform 27% of all jobs in member countries, actual job displacement due to AI has been limited so far. The report finds more evidence of task augmentation than outright replacement.

A 2023 study from MIT’s Work of the Future Initiative found similar patterns: AI is automating specific tasks, not entire occupations. Think of AI drafting a first version of a document for a marketer or helping glean information from medical records, not replace the nurse doing it.

Even Goldman Sachs, whose 2023 report sparked many headlines claiming “300 million jobs could be impacted,” clarified that most of the change will occur through task transformation, not layoffs.
So if the data shows minimal job loss so far, what are people seeing?

What’s Really Happening on the Ground?
Some industries are using AI to reduce labor costs—most notably:

• Customer service: Major banks and telcos have replaced call center agents with AI chatbots for routine issues.
• Media: A few digital newsrooms are experimenting with AI-generated content at scale (with mixed results).
• Coding & Testing: Some tech firms use tools like GitHub Copilot to reduce the need for junior developers.

But even here, companies are reallocating labor rather than laying off en masse. The goal is faster and better service, not zero humans.

In contrast, in healthcare, consulting, legal, and B2B SaaS, AI is primarily used as an efficiency tool—streamlining research, customizing recommendations, or automating reporting. People are still central to the process.

So Why the Dystopian Mood?
It comes down to how leaders choose to use AI. The WSJ article I previously mentioned makes a compelling argument in one respect: some executives are viewing AI as a way to “restructure” and shift power dynamics. Not because the tech requires it, but because it creates a convenient excuse.

This isn’t about AI replacing jobs. It’s about leaders trying to justify doing what they already wanted to do—cutting headcount, reducing costs, or removing friction points between management and labor. AI provides them plausible deniability.

That’s not inevitable. It’s a choice.

What We Should Be Asking
The real question isn’t “Will AI take my job?” It’s “How will my role change, and will leadership reinvest those gains in people?”

Because another wave is coming: one where AI actually enables new roles, such as AI ethicists, customer journey designers, and model auditors. But none of that happens if the mindset is, “How can we get rid of people?”

If you’re in the trenches, you know: the most potent use of AI is when it helps people do their jobs better, not vanish them.
​
AI dystopia should not become a self-fulfilling prophecy.

Source Material
1.     OECD (2024) – The Impact of AI on the Labour Market: What We Know So Far
https://www.oecd.org/employment/impact-of-ai-on-jobs-2024.pdf

2.     MIT Work of the Future (2023) – Exploring the Future of Work with Generative AI
https://workofthefuture.mit.edu

3.     Goldman Sachs (2023) – The Potentially Large Effects of Artificial Intelligence on Economic Growth
https://www.goldmansachs.com/intelligence/pages/ai-could-boost-global-gdp.html
​
4.     Wall Street Journal (May 2025) – Companies Are Starting to Treat Workers Differently Because of AI
(Note: This article sits behind a paywall. I have Apple News, so I read it there.)

Finding a new job has never been easy. But in today’s environment — with AI systems controlling the first gates of opportunity — it feels more like running an obstacle course in the dark. I’ve been living this firsthand since late last November when I was part of a larger lay-off at my last company. I started what I thought would be a focused, determined job search. What I didn’t realize was just how much the rules had changed since the last time I had to do this.
​
This is a look at what I’ve learned — the frustrations, the pitfalls, and a few ways forward that might help others going through the same thing.​

The First Wall: AI as the New Screener
One of the biggest shifts in the job search is that AI filters almost everything now. Resumes aren’t first seen by a recruiter; they’re parsed by an Applicant Tracking System (ATS) or an AI matching tool. The goal of these systems is to “streamline” the flood of applicants. The side effect? Strong candidates may never even get a human glance.

I had to research this, but in this environment, the way a resume is written really matters — but not always in a way that reflects real capability. It’s about keyword optimization, matching the phrasing of the job description, and being “AI-readable.” Clear formatting, simple structures, and matching terminology can mean the difference between being seen and being screened out.

​It can be discouraging — I knew I could excel in a role, if only someone would talk to me.

The Volume Problem (and Horses with Horns)
I found that every job posting now gets hundreds — sometimes thousands — of applicants. LinkedIn is real good at telling us how many applicants applied before you. Companies know this, and it creates another strange behavior: setting “unicorn” requirements. Instead of listing what’s actually necessary for success, job descriptions become laundry lists of every ideal skill and education credential under the sun, no matter how unrealistic.

It’s easy to get caught in cycles of self-doubt (“Maybe I’m not enough”) when the truth is often: nobody is that good.

Hiring has become aspirational on their side — and demoralizing on ours.

Networking Still Works — But It May Not Suffice
​Networking remains one of the few consistent ways to bypass the AI filters. I had many former co-workers (thank you all!) helping me through this process. A warm introduction, a recommendation, or even a comment on someone’s LinkedIn post can open doors. But what happens when your network is tapped out, or simply doesn’t align with your goals?

This is where traditional advice falls short. “Just network more” isn’t useful if the people you know may be able to point you to a door, or even open it for you, but the goals of the business you are trying to enter just don't align with yours.

That being said, I found that reaching out to old colleagues works when it is not done in desperation, but with updates on what I was working toward  — and showing a real curiosity about what they are doing. It is also important to be consistent - reaching out frequently works.

Re-skilling: Not Just Courses — Realignment
A lot of noise is made about re-skilling — endless ads for courses, certifications, and bootcamps. I found that re-skilling is not just about stacking new badges onto your profile. It’s about realigning ones personal story to where the market is going.

There is hope here - this might mean reframing existing skills for adjacent industries, not starting over from scratch.

It might mean showing how your background applies to problems companies actually have right now — not problems they had the prior fiscal year.

Scam City
Another hard reality that I encountered: scam job sites and fake postings.

These scammers prey on people’s desperation, offering interviews that never happen, asking for personal information, or dangling fake remote jobs.

Some signs I’ve learned to look for:

• Companies no one has ever heard of and vague job descriptions
• No traceable recruiter or company presence online; if there is a referenced recruiter, they look like they just got set up on LinkedIn yesterday
• Requests for lots of personal information up front
• Personal email domains (like Gmail, Outlook, or AOL Mail)
• Immediate offers without interviews

If something feels off, it usually is. Legitimate job boards usually point you to an application directly at the company you are applying to, or they have an integrated application process like LinkedIn, Welcome to the Jungle, WellFound and others.

Thoughts on "Networking Platforms”
​In my early search, I tried out several job-hunting “networking” platforms — the ones that promise a supportive community, introductions, or direct access to hidden jobs.

My experience?

• Most people on these platforms were just like me: searching, not hiring.
• Conversations were polite but rarely useful to me. Everyone needed help, but few could offer it, moderators included.
• Some platforms charged fees to access “premium” roles — most of which were either reposts from public job boards or old listings. Cross-referencing these jobs on LinkedIn or company job boards showed many of these jobs already closed out.

As I was not meeting much success with these services, I tried to understand why. The broad consensus seems to be the same: networking sites for job seekers are often echo chambers, not actual pipelines to opportunities.

I treated my stay with the networking groups for what it is: emotional support, maybe an occasional tip — but not a main job search strategy.

Lessons Learned — and the Way Forward
After months in the trenches, here’s what I’d tell anyone starting or stuck in the process:

• Write resumes for the machines — but never lose the human story.
• Don’t take unicorn job descriptions personally. After some research and talking to peers, I found many companies don’t really expect to find them.
• Treat networking like building bridges, not hunting trophies. Small, real conversations seem to work.
• Networking platforms as a main strategy did not work for me. They may work for others, but I found the focus on real-world connections to be more effective.
• Skill alignment to real-world needs, not re-skilling for imaginary job descriptions.
• Protect your mental energy. I found that not every opportunity is real, and not every rejection is about me.
• Persistence is survival. Some days I felt invisible. Some days I felt like I was really close to my next job. I have to keep moving either way.

The rules have changed, but one thing hasn’t: people still hire people — not resumes, not bots.

Stay sharp. Stay skeptical. Don't give up.