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Beyond Automation
AI-Enhanced Workflows for PDF/UA Remediation Aligned with ISO Standards
Excerpt: PDF professionals are increasingly expected to deliver accessible, standards-compliant content at scale—while minimizing cost, turnaround time, and error rates. As AI tools evolve, they offer powerful capabilities for automating parts of the remediation process. However, full compliance with ISO 14289-1:2014 (PDF/UA) and ISO 32000-2:2020 (PDF 2.0) still demands expert oversight to ensure semantic fidelity, proper document structure, and digital security. This session will explore how artificial … Read moreAbout the presenter(s)
Description
PDF professionals are increasingly expected to deliver accessible, standards-compliant content at scale—while minimizing cost, turnaround time, and error rates. As AI tools evolve, they offer powerful capabilities for automating parts of the remediation process. However, full compliance with ISO 14289-1:2014 (PDF/UA) and ISO 32000-2:2020 (PDF 2.0) still demands expert oversight to ensure semantic fidelity, proper document structure, and digital security.
This session will explore how artificial intelligence is transforming PDF accessibility workflows, with a focus on advanced tagging logic, automated structure recognition, and conformance validation. Using case studies and demonstrations from tools like Grackle PDF, we will show how AI can generate accessible content directly from source authoring environments such as Google Workspace, while aligning with ISO-based output expectations.
We will also examine the limitations of AI in handling complex documents—such as those with nested tables, dynamic content, or custom scripting—and the continued necessity for human QA to ensure robust compliance with standards like WCAG 2.2, ISO 14289, and PDF/UA-2. Discussion will include metadata integrity, artifact tagging, form field semantics, and maintaining digital security in the context of automated remediation.
By the end of this session, participants will be able to:
- Interpret and Apply ISO Standards: Demonstrate working knowledge of PDF/UA (ISO 14289-1), PDF 2.0 (ISO 32000-2), and their practical implications for document remediation using AI.
- Evaluate AI Tooling in Context: Critically assess how AI-powered platforms map to ISO compliance requirements for structure elements, reading order, and tag accuracy.
- Design Hybrid AI-Human Workflows: Build and optimize remediation pipelines that integrate AI automation with human validation to ensure both compliance and usability for assistive technology users.
- Mitigate Risk in Automated Workflows: Identify areas where automated remediation may introduce non-compliance or security vulnerabilities, and apply best practices for manual correction and review.
- Anticipate Future Standard Evolution: Prepare for updates in ISO 14289-2 and PDF/UA-2 by understanding emerging trends in document accessibility and AI integration.