How I Would Pivot within Cybersecurity If I Got Laid Off Today (AI Edition)

If I Got Laid Off Today: My AI-Cybersecurity Pivot Plan

Let’s imagine something scary but real: What if I got laid off today?

If you’ve been following the tech industry lately, you’ve probably seen the headlines:
“Massive tech layoffs.”
“AI replacing jobs.”
“Cybersecurity not immune from AI disruption.”

And let’s be real: It’s not just headlines.

I’ve personally seen friends, former colleagues — even people in senior cybersecurity roles — suddenly find themselves jobless.

So, today’s video (and this article) isn’t about fear. It’s about having a game plan.

If I lost my job today, here’s exactly how I’d pivot my cybersecurity career in the AI era — and how you can too.

Step 1: Emotionally Reset — No Shame, No Panic

First things first.

If I got laid off, yeah — it would sting. Ego would take a hit. Self-doubt would creep in.

But I wouldn’t let that last longer than 48 hours.

Why?

Because the cybersecurity industry isn’t dying — it’s transforming.

The demand for cybersecurity professionals who can work with AI, secure AI systems, and adapt to automation is skyrocketing.

So after a short sulk (and probably a few cups of karak chai), I’d switch to problem-solving mode.

Step 2: Ruthlessly Audit My Current Skill Set

Next, I’d sit down and take an honest, brutal inventory of my skills.

I’d ask myself three questions:

1. How much of my current job could AI do right now?
   Am I doing repetitive tasks like alert triaging, writing basic reports, or following playbooks? If yes… bad sign.

2. Do I have skills in AI-relevant areas?
   Like AI risk management, AI threat modeling, GenAI security, AI governance, or cloud-native security? If no… time to fix that.

3. Do I have any visible proof of my expertise?
   LinkedIn posts? GitHub projects? Public speaking? Courses? If not… that’s priority #1.

This self-audit would tell me exactly where I’m vulnerable — and where I can double down.

Step 3: Pick a Pivot Lane (One of These 5)

Here’s where I’d choose a specific direction — fast.
AI is disrupting generic cybersecurity roles. But specialized, high-impact roles are still in demand.

If I had to pick today, I’d go all-in on one of these:

1. AI Threat Modeling
   Helping companies identify and mitigate risks in their AI pipelines. Think: LLMs, RAG systems, Agentic AI.

2. AI Governance & Compliance
   Helping organizations comply with the EU AI Act, NIST AI RMF, or ISO 42001. Especially valuable for GRC people

3. Agentic AI Security Engineer
   Focusing on securing autonomous AI agents, building guardrails, and monitoring AI decision flows.

4. AI Red Teaming / Prompt Security
   Ethically hacking AI models to test for vulnerabilities like prompt injection, data leakage, and model jailbreaks.

5. Cloud Security Architecture for AI Workloads
   Designing secure cloud environments for hosting GenAI apps. AWS Bedrock, Vertex AI, Azure OpenAI… all hot right now.

If you’re reading this and thinking, “I’m not an expert in any of these,” don’t panic.

Nobody was an expert in GenAI security 12 months ago.
The key is choosing one lane and going deep — fast.

Step 4: Build One Public Proof Project (Minimum Viable Evidence)

Next, I’d immediately build and publish one AI-security-focused project.

Doesn’t need to be perfect. It just needs to exist and be visible.

Here’s what I’d do (choose based on your pivot lane):

• Threat Modeling Pivot? → Publish an AI threat model for a fake chatbot application. Share on LinkedIn and GitHub.

• GRC Pivot? → Create an AI governance checklist for ISO 42001 compliance. Write a Medium post.

• Engineering Pivot? → Publish a tutorial showing how to apply guardrails to a Bedrock GenAI endpoint.

• Red Team Pivot? → Document a prompt injection test against an open-source LLM.

Why?
Because when you have public proof, two things happen:

1. You attract recruiters and hiring managers who are already desperate for AI-security talent.

2. You get talking points for interviews and networking conversations.

Even if you only get 100 views on LinkedIn, it signals that you’re taking action and positioning yourself as part of the solution — not part of the obsolete.

Step 5: Leverage My Network — Quietly but Aggressively

I wouldn’t start with “Hey, I’m unemployed!”

Instead, I’d do this:

• Message 10 people in my network saying:
  “Hey, I’ve been diving deep into [chosen AI Security topic]. Let me know if you hear of any opportunities around this space.”

• Join relevant Slack groups, Discord servers, and LinkedIn communities focused on AI security.

• Post value-driven content at least once a week (case studies, lessons learned, mini-tutorials).

Visibility + Value = Opportunities.

Step 6: Apply Smartly (Not Mass Applying)

I wouldn’t shotgun apply to 100 generic roles.

I’d target:

• Companies actively hiring for AI-related security positions

• Cloud providers, AI startups, GenAI consultancies

• Cybersecurity firms pivoting into AI risk management

And I’d tailor every application to highlight:

• My AI-security pivot

• My hands-on projects

• My thought leadership (via LinkedIn posts, blogs, or GitHub)

If I had to, I’d even pitch freelance or contract gigs around AI security while job-hunting.

Step 7: If All Else Fails… Launch My Own Thing

Worst case ?

I’d start offering micro-consulting services in my chosen lane.

Maybe helping small startups with AI risk assessments.

Maybe doing training workshops on AI security basics.

Maybe launching a low-cost SaaS security tool using vibe coding.

Because in 2025 and beyond, solopreneurship in cybersecurity is a real, scalable, AI-leveraged career path.

Final Thought

If you’re feeling nervous about layoffs, or you’ve already been hit

Understand this:

You don’t need to become a machine learning PhD.

You don’t need to know everything about AI overnight.

You just need to pick one lane, build one project, and make yourself visible.

That’s what I’d do. Starting today.