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AI Career Risk For AI Red Teamers

Will AI Replace AI Red Teamers in 2026?

Also known as: Red Team Member, AI Security Specialist (Artificial Intelligence Security Specialist).

AI red teamers stress-test AI systems for safety, security, and misuse vulnerabilities. The role is new and growing fast; the durable work is senior adversarial-testing judgment, methodology design, and the named accountability for safety-and-security findings inside an organisation's AI-deployment programme.

Exposure ScoreLow Exposure
20/ 100
Rank: 76 of 91 in TechnologyCategory avg: 39/100All roles avg: 39/100
This is the role's AI exposure (0 to 100, lower is safer), not your personal AI Career Index (0 to 1000). Get your own score.
Median pay: $129,180 / yr· BLS OEWS, May 2025 · occupational category
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At a Glance

AI Red Teamers at a glance

A quick read on AI Red Teamers: the AI risk band, where the role sits inside Technology, and the headline numbers worth knowing before reading more.

Exposure Score
20/100
Tasks AI can do
33%
Median wage
$129,180
AI Adoption
49%
Category rank
76of 91
Role Overview

How AI is reshaping AI Red Teamers

AI Red Teamers hold a structurally appreciating role at the frontier of AI safety, evaluation, and adversarial testing. The work is judgment-heavy, creative, and inseparable from the human capacity to anticipate misuse, jailbreaks, and emergent failure modes. AI tools support the routine probing and standard-eval layer, but the creative adversarial work, the policy judgment, and the model-release decision support remain entirely human. Demand is rising sharply with frontier-model investment and the regulatory expansion around AI safety, and the role is one of the fastest-appreciating in the entire technology category.

The work depends on accountability, licensure, complex judgment, or being physically present in ways AI tools cannot match. AI is absorbing the layers around the role, the coordination, the paperwork, the reporting, and that tends to make the role more valuable, not less.

The reading below covers the specific AI exposure rating for AI Red Teamers, the tasks AI can already do today, the authority band the role typically operates at, and a six-month plan tied to where the role actually sits. Same framework used for every role in the index.

Exposure Profile

AI exposure profile for AI Red Teamers

How AI Red Teamers stack up against other roles. How much of the work is routine, how much depends on judgment, and where the role sits compared to the Technology average.

Exposure Score
20OUT OF 100
Ranks 76 of 91 in the Technology category, among the most insulated
How this role compares
AI Red Teamers20
Category average39
All roles average39
Estimated task composition
Routine21%(AI-substitutable)
Strategic44%(judgment work)
Relational35%(trust-bearing)
Exposure trajectory
Holding steady

Holding steady: the role is anchored by judgment and relational work current AI tooling cannot absorb.

Modelled direction of travel from the role's task mix, not a measured year-by-year series.

202420252026 (now)2027
Career Simulator

What moves the score for AI Red Teamers?

This starts from a typical profile for a low exposure role. Drag any of the five dimensions to see how a structural shift would move the AI Career Index, using the exact weighting behind every reading on the site.

The AI Career Index (0 to 1000) measures your personal structural positioning. It is a different measure from this role's AI exposure score (0 to 100) shown above, which rates the role itself.

Career Simulator

Model the impact of structural shifts

A typical starting profile for ai red teamers. Move any dimension to model the impact on the AI Career Index.

AI Career Index
714/1000
Tier
AI Competitive Professional
Authority band: Strategic
01000
Strategic Clarity· 25%72Advanced
AI Adaptability· 20%70Advanced
Income Leverage· 20%68Transitional
Skill Resilience· 20%74Advanced
Market Alignment· 15%73Advanced
This is a model. Run the real reading to simulate on your own scores.Run my real reading

This simulator applies the same dimension weighting used in your structural reading to estimate directional movement. It does not alter any stored assessment. Actual outcomes depend on implementation quality, sequencing, and market conditions.

Open the full Career Simulator to model all five dimensions from scratch, or see how the score is built in the structural framework.

Key Takeaways

Quick read on AI Red Teamers

The short version on AI Red Teamers: AI exposure, how much of the role AI can already do, what stays valuable, and the move worth making in the next six months. A quick summary before the deeper read.

Real-world signal

How AI is being used by AI Red Teamers today

Two figures for AI Red Teamers that sit outside our scoring framework. The adoption figure shows how much of the day-to-day work done by AI Red Teamers is already being absorbed by AI tools in the wild. The economic impact figure gives the macro stakes attached to the role at a national level.

AI adoption among AI Red Teamers
49%

Share of the work done by AI Red Teamers already showing real-world AI usage today, sourced from the Anthropic Economic Index (CC BY 4.0). A 0% reading means the dataset observed no measurable usage for this occupation in its sample, not that AI cannot apply to the role.

Economic impact
$24.63B

Total US economic value generated by AI Red Teamers: median annual wage multiplied by total US employment, both from BLS OEWS.

24-Month Trajectory

Where AI Red Teamers are heading by 2028

Where AI Red Teamers sit today and where the role is heading over the next two years. We don't predict an exact future score. The direction is what the data already shows. If you're in this role or considering it, this is the direction worth planning around.

Today
20/100
Low Exposure
→ ↑
Appreciating
In 24 months · By 2028
Holds and gains value
AI takes care of routine work around this role. The core skills stay in demand and tend to get more valuable, not less.
Category outlook

Over the next two years, AI Red Teamers split into two tracks. People doing the hands-on production work face the steepest pressure as AI handles more of the routine implementation. Architects, principal engineers, and people who carry security accountability are becoming more valuable, because AI takes care of the layers around them and the judgment work concentrates upward. The path forward is clear: own how the system is designed, not the line-by-line build.

What AI Can Do

What AI can and can't do for AI Red Teamers

The work AI can take over today versus the work it cannot. Where AI Red Teamers spend their time on this split largely decides whether the role grows or shrinks over the next two years.

Deprioritise

Stop investing in these

  • Standard CRUD endpoint implementation
  • Configuration file generation and validation
  • Standard unit and integration test scaffolding
  • Standard refactors and dependency upgrades
Stays human

Structurally insulated

  • Cross-team technical leadership
  • Performance debugging in complex distributed systems
  • Production incident judgment and recovery decisions
  • Security accountability and threat modelling
AI Tools

AI tools currently affecting AI Red Teamers

The tools actually reshaping AI Red Teamers work in 2026. Each one takes over a slice of the routine work; staying valuable means owning the work that sits above them.

GitHub Copilot
Inline code completion and chat across the IDE.
Cursor
AI-native IDE with multi-file edit and codebase indexing.
Claude Code
Agentic coding assistant for refactors, tests, and PRs.
ChatGPT
General-purpose code generation, debugging, and explanation.
Tabnine
Privacy-focused AI completion trained on your own code.
Sourcegraph Cody
Codebase-aware AI assistant designed for large monorepos.

Tool list is editorial, not exhaustive. Listing does not imply endorsement. Updated Methodology v3 · 2026.

Structural Reading

Where AI Red Teamers sit structurally

Where AI is hitting the work, where it cannot reach, where AI Red Teamers are heading over the next two years, and what stays durable. The cards below address each question; the per-role reading underneath them grounds the answers in this role's actual tasks and knowledge layers.

Will AI Replace

Will AI Replace AI Red Teamers?

AI will not replace AI Red Teamers as a category, but it is rapidly redrawing the boundary of what AI Red Teamers are paid to do. Routine production work in this role is highly substitutable. Architectural judgment, system-level trade-offs, and security accountability remain structurally insulated. The professionals who treat AI as a tool to amplify their architectural authority are pulling away from those who use AI only to produce more output.

Automation Risk

Automation Risk for AI Red Teamers

Automation pressure on AI Red Teamers comes from three directions. First, generative AI tooling produces routine code, tests, and configurations at near-zero marginal cost. Second, AI copilots compress the time required for standard implementation work. Third, AI-assisted review and refactoring is shifting the value proposition from writing code to designing systems. AI Red Teamers who remain at the production layer face accelerating compression. AI Red Teamers who migrate upward into architecture and strategic technical decisions retain durability.

Career Outlook

AI Career Outlook for AI Red Teamers

Over the next two years, AI Red Teamers split into two tracks. People doing the hands-on production work face the steepest pressure as AI handles more of the routine implementation. Architects, principal engineers, and people who carry security accountability are becoming more valuable, because AI takes care of the layers around them and the judgment work concentrates upward. The path forward is clear: own how the system is designed, not the line-by-line build.

Stay Relevant

How AI Red Teamers Stay Relevant

AI Red Teamers stay relevant by deliberately moving up the authority stack. Take ownership of one system design end-to-end. Document the trade-offs you considered. Become the person who decides what gets built, not just the person who builds it. Pair this with deep AI tooling fluency so you orchestrate human and AI work into a single workflow rather than competing with AI on output volume.

Inside the Work

A typical week as an AI Red Teamer

What the work looks like in practice: meetings, deliverables, tools, and the decisions that get escalated. Useful context for anyone weighing this role against the AI-exposure reading above.

Week-in-the-life
Authored by editorial · AI Red Teamer
MonTueWedThuFri

A typical week for an AI red-teamer runs on adversarial testing of AI systems: jailbreak research, capability elicitation, harm-scenario testing, and the documentation work that supports safety decisions. Most days include time prompting and probing AI systems, custom-tooling for automated red-teaming, and the cross-functional work with safety, policy, product, and research teams. The work runs on the rapidly-evolving capability frontier of foundation models and the corresponding evolution of threat models. AI tools themselves both enable and target the work. The durable layer is the adversarial-craft on novel attack vectors, the safety-judgment on what's a real harm versus a theoretical concern, and the cross-functional partnership that turns red-team findings into shipped mitigations. The accountability is the safety posture of deployed AI. Compression is limited; the adversarial-craft work is structural.

Compression and Durability

Where AI Red Teamers compress, and where they hold

A role-specific reading grounded in AI Red Teamers's actual O*NET tasks and knowledge layers. The paragraph below is the structural reading; the two columns name the specific layers where compression is hitting and where the work holds.

Structural reading

AI Red Teamers are insulated by structure rather than by skill. computers and electronics and the accountability that surrounds it cannot be shifted to AI tooling without breaking the chain. AI accelerates develop plans to safeguard computer files against accidental or unauthorized modification and the surrounding mechanics, but the human bearing the decision still has to be present.

Where compression is hitting
  • Develop plans to safeguard computer files against accidental or unauthorized modification gets accelerated by AI tooling, which gives ai red teamers more time for the judgment-heavy parts of the role.
  • Modify computer security files to incorporate new software is where AI shows up day-to-day, but the accountability and decision-making sit with the human.
Where the role holds
  • Computers and Electronics requires judgment under conditions where indoors, environmentally controlled matters, work AI tooling cannot own at scale.
  • English Language is the human-bearing layer; even when AI accelerates the surrounding production, this is where the call gets made.
  • Administration and Management compounds with experience. AI-assisted ai red teamers working at this layer get faster without the role being absorbed.
Salary & Occupation Data

Salary and occupational data for AI Red Teamers

Median annual wage, common task statements, and alternate titles drawn from O*NET 30.2 (USDOL/ETA, CC BY 4.0) · Wages: BLS OEWS May 2025. BLS reports median wages at the occupational category level, so ai red teamers and related roles that map to the same category share the same source wage. The descriptive occupational data below sits alongside the structural reading; the AI exposure score above is independent of it.

Occupation Snapshot · AI Red Teamers
O*NET-SOC 15-1212.00
Median annual wage
$129,180
BLS OEWS · May 2025
Junior
$97,810
Senior
$163,500
Common task statements (O*NET)
  • Develop plans to safeguard computer files against accidental or unauthorized modification, destruction, or disclosure and to meet emergency data processing needs.
  • Monitor current reports of computer viruses to determine when to update virus protection systems.
  • Encrypt data transmissions and erect firewalls to conceal confidential information as it is being transmitted and to keep out tainted digital transfers.
  • Perform risk assessments and execute tests of data processing system to ensure functioning of data processing activities and security measures.
  • Modify computer security files to incorporate new software, correct errors, or change individual access status.
Knowledge domains (O*NET importance, 1–5)
  • Computers and Electronics4.4
  • English Language4.3
  • Administration and Management3.7
  • Engineering and Technology3.6
  • Telecommunications3.6
Work context (importance, 1–5)
  • E-Mail5.0
  • Indoors, Environmentally Controlled4.8
  • Telephone Conversations4.5
  • Face-to-Face Discussions with Individuals and Within Teams4.5
  • Contact With Others4.3
Preparation level
Job Zone 4· Considerable preparation
Tools and equipment (O*NET)
Desktop computersLocal area network LAN analyzersMainframe computersNetwork analyzersNotebook computersProtocol analyzers
Related occupations (O*NET)
Information Security EngineersPenetration TestersDigital Forensics AnalystsNetwork and Computer Systems Administrators →Computer Systems Analysts →
Source: O*NET 30.2 (USDOL/ETA, CC BY 4.0) · Wages: BLS OEWS May 2025 · Descriptive occupational data; the AI exposure reading is independent.
Reviewed by AI Career Index Research · Methodology v3 · 2026 ·Read the methodology →
Common Feeders

Roles commonly transitioning into AI Red Teamers.

These technology roles are under more pressure than AI Red Teamers, and people often path out of them into a seat like yours. If you work in one of these today, AI Red Teamers is the kind of role most worth moving toward.

86/100 · High risk
Computer and ATM Repairers
Production-heavy engineering role. People often grow out of it into platform and architecture work.
Read AI risk for Computer and ATM Repairers
70/100 · High risk
Computer Network Support Specialists
Tier-one ticket handling, password resets, and routine network diagnostics are absorbed by AI helpdesk tools.
Read AI risk for Computer Network Support Specialists
71/100 · High risk
Computer Programmers
Standard implementation, boilerplate, and routine bug fixes are exactly what code-generation tools ship fastest.
Read AI risk for Computer Programmers
6-Month Action Plan

Six concrete moves for AI Red Teamers over the next six months

AI Red Teamers are structurally insulated within technology, but the coordination layer around the role is being absorbed by AI tooling. The six moves below help you reclaim hours from that layer and reinvest them in the licensed and judgment-heavy work that compounds. Each move is one month, with a week-by-week sprint inside. The downloadable PDF adds end-of-month reflection prompts in a print-friendly format.

Go deeper

Take the plan with you

The downloadable PDF gives you the full plan in a print-friendly format you can keep at your desk and check against month by month. Take the AI Career Assessment to get a plan tailored to your specific situation.

FAQ

Common questions about AI Red Teamers and AI

The reading above answers the headline question. These FAQs cover the follow-up questions AI Red Teamers typically ask: wage benchmarks, the tasks most at risk, the skills that stay valuable, and the six-month plan for this role.

Further Reading

Articles relevant to AI Red Teamers

Hand-picked AI Career Index articles on the shifts affecting AI Red Teamers and nearby roles. Useful next reads for the broader context behind the reading on this page.

Testimonials

What Professionals Are Saying

All testimonials →

"I work in a field that AI is squeezing hard. The report did not pretend otherwise. What it did was show me which part of my role is safe and how to move more of my work into it over the next six months. That honesty is what I needed."

Hannah Kowalski
Creative Director · Warsaw, Poland

"I had my whole team of twelve take it. The group results flagged two roles that were quietly falling behind and at risk of losing ground to competitors. We fixed both before it showed up in their numbers. At forty-nine dollars a person, it is the best-value spend I have made all year."

Michael Anderson
Managing Partner · Chicago, USA

"The report talks about the middle layer of jobs thinning out, and I realised that was exactly where I sat. The way out that it suggested felt obvious once I saw it, but I had been blind to it. I acted on it the next quarter."

Elena Ricci
Senior Account Director · Milan, Italy

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