AI alt text

Role in discovery and ranking

Alt text helps search engines understand what an image depicts and how it relates to the surrounding content. For Google Images and other visual discovery surfaces, it contributes to relevance signals alongside filenames, structured data, captions, and page context. In general web search, its influence is indirect: clearer image context can support the page’s topical focus, but alt text alone does not elevate rankings when the page itself is thin or off-topic.

AI-generated descriptions can increase coverage where manual authoring is impractical, which may improve image indexation and click-through from image search. However, generic or overly promotional captions offer limited value and may be ignored. Keyword stuffing in alt attributes is treated as spammy and harms usability for screen reader users. Treat alt text as a functional description: keep it specific, reflect the image’s purpose on that page, and use empty alt (alt="") for decorative images so they are skipped by assistive tech.

Accessibility compliance

WCAG 2.2 Success Criterion 1.1.1 requires text alternatives that serve the equivalent purpose of non-text content. That means the description must match user intent and context: if the image functions as a link or button, the alt should describe the destination or action; if the image is informational, it should summarise the salient information; if purely decorative, the alt should be empty so screen readers skip it. Complex images (charts, diagrams, infographics) often need a short alt paired with a longer, programmatically associated description elsewhere on the page.

AI can assist with compliance, but responsibility remains with the publisher. A robust process includes human-in-the-loop review for critical images, confidence thresholds that suppress low-trust output, role detection to distinguish decorative from functional content, and policies for sensitive attributes. Organisations operating under legal frameworks (e.g., Australia’s Disability Discrimination Act, the ADA in the US, EN 301 549 in the EU) should document how AI is used, maintain audit logs, and provide escalation paths for corrections requested by users with disabilities.

Overview

How AI alt text works

AI alt text systems typically combine vision and language. Computer vision models identify objects, scenes, and attributes; OCR extracts visible text; and vision–language models generate concise, natural-language descriptions. Strong implementations condition the model on page and asset context—surrounding headings, captions, product metadata, link targets, and filenames—so the output reflects purpose, not just pixels. Pipelines usually include role detection (decorative vs informative), captioning, brevity control, sensitive-attribute filters, and quality scoring before publishing or queuing for review.

Operational considerations

Operational design balances latency, cost, and privacy. Many teams generate alt text at upload or build time and cache it in the CMS or CDN rather than calling AI services during page render. Multilingual sites may generate per-locale output or translate trusted source descriptions. Privacy reviews are essential when sending images to third-party APIs, especially if assets contain personal data or regulated information. Rate limits, queueing, and observability (coverage, acceptance rates, edit rates) help maintain reliability at scale.

Accessibility accuracy and harm

The most common harms are inaccuracy and verbosity. Hallucinated details erode trust and can mislead, particularly for medical, safety, or instructional imagery. Overlong alt text increases cognitive load and time-to-content for screen reader users. Good defaults avoid boilerplate like “image of” and keep to the essential purpose in context, often within roughly 80–125 characters where practical. Images that convey no information (decorative dividers, ornamental backgrounds, repeated icons) should have empty alt so they are skipped entirely.

Sensitive attributes demand restraint. Avoid guessing gender, age, ethnicity, or mood unless the page explicitly provides that information and it is necessary to the task. For people, neutral phrasing such as “a person” is safer than “a man/woman” unless known. OCR can expose private data (IDs, addresses, bank details); apply redaction or blocklisting rules so such text is not transcribed into alt. Dataset bias can surface stereotypes, so test with diverse content and involve disabled users in evaluation to uncover issues automated metrics miss.

Implementation notes

Treat AI alt text as an assistive workflow rather than a fire-and-forget replacement for authoring. Role awareness is crucial: for linked images and buttons, generate text that reflects the action or destination (e.g., “View summer shoes”) rather than a visual description. For charts and diagrams, generate a succinct alt and provide a longer description nearby via figure captions or aria-describedby. Apply confidence thresholds; when the model is unsure, leave the alt blank for decorative candidates or route to editorial review for informative images.

• Ingest context: headings, captions, product names, link URLs, and ARIA roles to steer purpose-driven output.
• Set guardrails: length targets, banned terms, sensitive-attribute filters, and language style guides per locale.
• Implement decorative detection: size and role heuristics, CSS background detection, and repetition checks to default to alt="".
• Store output in the CMS or CDN; avoid client-side generation that delays rendering or exposes private assets to browsers.
• Track metrics: coverage, edit rate by humans, error reports from assistive tech users, and impact on image indexation.
• Localise responsibly: generate or translate per locale, and align with regional accessibility and privacy requirements.

Comparisons

AI vs manual authoring

Manual alt text offers the highest reliability when authors understand the image’s intent, audience, and domain. It is, however, costly to maintain across large libraries and can suffer from inconsistency. AI scales coverage, standardises style, and can capture obvious details quickly, but it lacks organisational context and may omit nuanced or purpose-critical information. A pragmatic approach combines both: AI drafts with human review for key templates (homepage, commerce, editorial), and automated acceptance for low-risk decorative suppression.

Captioning vs alt attributes

Image captioning models can produce longer, narrative descriptions that read well to sighted users but may be too verbose for alt attributes. Captions are visible content and can complement alt text; they do not replace the need for a concise, purpose-driven alt. For complex visuals, pair a short alt with a visible caption and a longer description linked via aria-describedby or a nearby summary. Structured data and EXIF/IPTC metadata can support discovery but are separate from the semantic requirement of the alt attribute.

FAQs

Does AI-generated alt text improve SEO rankings?

High-quality alt text can help images be indexed and matched to relevant queries, especially in Google Images. It also clarifies on-page context. However, it is not a shortcut to higher rankings in general search. Thin, generic, or keyword-stuffed alt text offers little benefit and can degrade accessibility. Focus on accurate, purpose-driven descriptions and strong overall content quality. Measure impact via image impressions, clicks, and coverage rather than expecting broad ranking lifts.

Should every image have AI alt text?

No. Decorative images should have empty alt (alt="") so screen readers skip them. Informative images, controls, and linked images need meaningful alt that reflects their purpose in context. AI can help determine whether an image appears decorative based on size, repetition, and semantics, but edge cases require oversight. Establish rules per template so the system suppresses alt where appropriate and flags uncertain cases for review.

How long should AI alt text be?

There is no strict character limit, but concise is best. Aim to convey the essential purpose in roughly one short sentence—often about 80–125 characters is practical for many screen reader configurations. For complex visuals, keep the alt succinct and provide a longer description elsewhere. Avoid boilerplate, adjectives that do not aid understanding, and redundant phrasing like “image of”.

Can AI handle multilingual alt text at scale?

Yes, either by generating in the target language or translating trusted source descriptions. Quality varies by language and domain, so include locale-specific style guides, banned terms, and evaluation sets. Ensure the CMS can store per-locale alt attributes and fall back predictably when alt is missing. Avoid client-side translation at render time to prevent flicker and inconsistent indexing.

Is it safe to send images to AI APIs for alt text?

It depends on the data and vendor. Review privacy, data retention, and regional processing options; prefer providers that support encryption, zero-retention modes, and data residency where required. Avoid transmitting images that contain sensitive personal information, or apply redaction before processing. Maintain an audit trail of when and how AI was used, and provide a path to correct or remove descriptions on request.