14 AI experts in Publishing discuss 14 use cases. The AI Special by InPublishing.

InPublishing organised their second AI Special with 14 experts who have hands-on experience with AI implementations in their respective businesses. The experts wrote short articles for the AI Special which you can read here.

Here is an overview of the various AI use cases the speakers have put forward:

Data Products and Insights:

Using AI to repackage existing content into new data products, combining sources like finance data, journalism, and historical trends to offer deeper insights.

Interactive Chat and Directories:

AI-powered interactive tools built from well-maintained directories enhance user engagement, supporting queries and delivering real-time, valuable content.

AI-Generated Graphics:

Creation of compelling, visually arresting images to replace stock art. Examples include AI-crafted medical illustrations, humorous depictions (like cartoon slugs), and composites for front-page visuals.

Content Tagging:

Using AI to auto-generate relevant tags with systems for managing redundancy, prioritizing impactful tags, and refining contextual relevance through human oversight.

AI Chat Discovery Tools:

Tools leveraging sample conversations, iterative refinements, and user feedback loops to provide better content discovery and engagement experiences.

Productionizing AI:

Embedding AI into workflows for speed, consistency, and scalability, including tailored AI applications like podcast repurposing and RAG models for safer, more effective content generation.

Content Strategy Enhancement:

Applying AI to analyze user needs frameworks and optimize content strategies while involving editorial and tech teams collaboratively.

Editorial Workflow Efficiency:

Streamlining tagging, topic assignment, and indexing to enrich search engines and improve multilingual publishing, including fully AI-generated foreign language versions.

Specialized Tools:

Using purpose-built tools (e.g., for OCR, translation, or PDF extraction) alongside general AI to achieve accuracy and scalability for niche tasks.

Image Automation:

Automating tasks like image enhancement, cut-outs, and keyword tagging, significantly reducing manual effort and time while improving image quality.

Automated Article Creation:

Leveraging AI to generate articles from press releases with optimized prompts and centralized prompt management systems.

Productivity Tools:

Employing AI to improve tasks like XML validation, podcast editing, and technical operations, reducing dependency on specialists and enabling faster, more autonomous workflows.

Advertising and Lead Discovery:

AI-powered local business directories and tools to analyze advertisers’ needs (e.g., identifying businesses with underperforming YouTube channels) for highly targeted sales strategies.

Copyfitting Assistance:

AI-supported suggestions for editing and shortening text to improve efficiency while maintaining editorial control.

And finally, a prediction for the future of AI in Publishing:

The last speaker envisioned a transformative shift in user interaction with publishing. Traditional web layouts with lists of articles will evolve into dynamic, conversational experiences powered by AI.

These interfaces will merge content with chat capabilities, allowing users to read, listen, or watch seamlessly. The prediction emphasized a rapid transition where AI and human collaboration redefine workflows and content delivery, heralding a dominant conversational and multimedia-driven approach within just a year.