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This page explains how the Durability Score is built — the components, the evidence behind each one, and the named sources. For who this work fits and what a career path through it looks like, see the Deep Read. For your personalized match, take the free quiz.
Where the 37 comes from.

Three components - Automation Resistance, Structural Moat, and Demand - add up to the 37.

FJP Durability Score
37/100
Automation Resistance
10/40

The automation signal is severe for entry work because interface production is digital and tool-friendly; observed AI use looks moderate, but modeled vulnerability is much worse, while product judgment and research survive better than screen-making.

Sub-components
Substitution Resistance
4/30

Observed AI exposure is about 24.9%, while modeled job-loss risk is about 54.6%. That gap is the key caution: current tool use looks moderate, but vulnerability is severe because screens, prototypes, summaries, copy, and design-system assembly are digital tasks. Product judgment, research framing, accessibility, and stakeholder tradeoffs keep only a narrow core protected.

Augmentation Leverage
6/10

AI can draft screens, flows, prototypes, research summaries, copy, images, and design-system variations. The worker upside is limited because many UX designers are salaried and employers can keep much of the productivity gain by reducing production hours or raising output expectations.

Sources feeding this sub-component
Anthropic Economic Index primitives → This source gives task-level AI examples, but no dedicated value for this exact occupation.
Structural Moat
13/35

Protection is practical product trust, not formal law: UX has no license, almost no physical barrier, and a portfolio-heavy bachelor's-level path, with employer trust doing more than credentials inside real product teams and hiring decisions.

Sub-components
Physical & Environmental
1/10

UX design is mostly desk, screen, workshop, meeting, and research-session work. Occasional user interviews or team sessions create little physical barrier. The durable difficulty is cognitive and organizational: finding the right problem, handling constraints, and getting teams to act on evidence.

Sources feeding this sub-component
BLS ORS data landing page → Federal physical-demand data is limited here, so the physical read also leans on the occupation profile.
Regulatory Moat
0/12

There is no occupational license, board exam, or protected legal scope for UX or digital interface design. Accessibility and privacy rules can raise project stakes, but they do not create a profession-wide gate that protects entry into the job.

Sources feeding this sub-component
Web Content Accessibility Guidelines 2.2 → Accessibility guidelines raise the stakes for serious interface work, but they do not create an occupational license.
Robotics Resistance
8/8

Robotics is irrelevant to the main risk. UX design is screen-based product work, so substitution pressure comes from software, AI interface tools, no-code prototypes, design systems, and platform automation. The robotics score is high only because robots are not the channel.

Credential Depth
4/5

Digital interface designers often have a bachelor's degree in web design, digital design, graphic arts, or a related field, but employers may also accept strong project proof. That creates moderate credential depth without a protected ladder.

Demand
14/25

Demand is positive because digital products, accessibility, mobile interfaces, and enterprise software still need design work, but no-code prototypes, design systems, and generative UI tools pressure entry production while the ladder gets thinner for beginners.

Sub-components
Volume
6/10

The digital interface designer base has about 128,900 jobs, roughly 9,100 annual openings, and growth near 7%. The volume signal is positive, but it does not offset the severe pressure on the screen-production layer.

Sources feeding this sub-component
Source Quality
5/8

Demand comes from digital products, web and mobile interfaces, accessibility, usability, enterprise software, and product metrics. The quality is held back because no-code tools, design systems, generated UI, and platform consolidation can absorb production work that once justified junior UX seats.

Resilience
3/7

Product/interface work persists, but the active shock is aimed at the first rung: static mockups, design-system assembly, prompt-to-prototype work, research summaries, copy, and simple screen variants. Resilience is stronger only where UX owns evidence, accessibility, product tradeoffs, and stakeholder trust.

What would move the score
Scenario 1
Prompt-to-interface tools replace normal junior UX production.

The case weakens if teams routinely generate usable screens, flows, copy, and prototypes from prompts or design systems with little junior designer labor. The threshold is fewer paid entry roles and less learning work, not faster wireframes used by the same designers.

Direction
Down, material
Components affected
Automation Resistance + Demand
Scenario 2
Accessibility and regulated digital-product work become stronger gates.

The case improves if employers need recurring UX labor for accessibility, testing, documentation, and accountable interface decisions. The trigger is paid work for normal product teams tied to audits, liability, purchasing, or compliance, not optional accessibility language in portfolio projects.

Direction
Up, modest
Components affected
Structural Moat + Demand
Scenario 3
UX roles move closer to product strategy and research evidence.

The case improves if entry roles include interviews, usability testing, experiment interpretation, metrics, and cross-functional product decisions. The threshold is real responsibility for evidence and tradeoffs inside paid product teams and internships, not only cleaner screens or faster prototype output.

Direction
Up, modest
Components affected
Automation Resistance + Demand
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Last reviewed June 2026 · Next September 2026