Artificial intelligence is reshaping the entire creative workflow, not just photo editing. In this session, Richard Harrington draws a clear line between assistive AI that helps creators capture, organize, search, edit, caption, deliver, and manage the work they actually made, and generative AI that fabricates content that was never captured in the first place. That distinction matters because it affects authorship, trust, ethics, and the long-term value of creative skill. The session looks across real-world tools and apps — from camera and phone software to cataloging platforms, DAM systems, enhancement tools, plugins, and workflow utilities — and shows how AI can support faster, smarter work without quietly replacing the photographer’s or creator’s role. 

Just as important, this class expands beyond features and hype to show how to set up AI tools safely so they use data properly and respect privacy. Attendees will learn how to evaluate whether an app processes files locally or in the cloud, what permissions it requests, how image libraries are synced and stored, when metadata and uploads leave your control, and how to build workflows that protect client work, family archives, and personal image libraries. Using examples from privacy-first and local-first platforms, the session shows how responsible AI can improve search, organization, enhancement, and delivery while still respecting ownership, consent, and user control. 

Key Takeaways

Understand the practical difference between assistive AI and generative AI
See how AI is used across tools and apps for capture, organization, search, editing, delivery, and asset management
Learn how to identify where helpful automation ends and synthetic fabrication begins
Understand how to safely set up AI-powered tools so they handle files, metadata, and permissions responsibly
Learn what to look for in local processing, cloud processing, syncing, storage, and data-sharing policies
Recognize privacy risks when using AI with client images, personal archives, or family photo libraries
Evaluate tools based on authorship, transparency, privacy, and user control
Build a practical framework for using AI responsibly across the full creative pipeline
Understand how software and app developers can design AI-powered products more ethically and transparently.