Crain Communications scaled AI across 26 publications using Cassidy

Crain isn’t just any other media company experimenting with AI. 

It’s a century-strong institution that oversees more than two dozen respected publications including Ad Age, Modern Healthcare, Pensions & Investments, and Automotive News. Crain has long been a company rooted in storytelling, reporting, and editorial rigor —building authority over decades, not chasing it. Its brands are trusted, its audiences niche and influential, and its standards unshakably high.

So when artificial intelligence started to hit the market Crain didn’t jump in headfirst. They were curious, but cautious. 

In an industry often skeptical of automation and fiercely protective of editorial standards, the idea of AI meaningfully contributing to editing, formatting, and brand consistency required more than enthusiasm. It demanded structure, transparency, and buy-in from teams (and their leaders). 

Enter Cassidy.

What began as a limited experiment soon evolved into a company-wide initiative. One that touched everything from headlines and metadata to internal training and editorial workflows.

Today, Cassidy powers AI-assisted work across 26 Crain-owned brands not as a replacement for creative thinking, but as a multiplier for operational efficiency, editorial scale, and brand-specific customization. 

“We weren’t trying to get people to adopt AI just for the sake of it,” said Marisa Marcinkowski, Strategist for Enterprise AI Enablement at Crain Communications. “Cassidy let us show people: here’s how it works, here’s how it’s safe, and here’s how it actually helps you do your job better.”

This is how they made it happen.

Crain’s Approach to AI: Start Simple, Scale with Intention

Crain didn’t approach AI with a sweeping transformation plan. Instead, they focused on a practical, trust-first rollout that met teams where they were.

When Marisa’s team introduced Cassidy, the goal wasn’t to overhaul editorial workflows. It was to make the platform accessible to both skeptics and early adopters. Editors and audience teams were encouraged to explore at their own pace, build simple use cases, and learn by doing.

What stood out most was how quickly non-technical team members got started. 

“We were able to take an editor who started his journalism career on a typewriter,”
Marisa recalled, “and he built an entire editing assistant that he now shares with other editors.”

There was no need for prompt engineering, scripting, or backend setup. Instead, Assistants were created using familiar workflows and structured documents, often with just a clear goal and some editorial context.

Writers, editors, and newsroom leads who had never worked with AI before were suddenly creating tools that mirrored their day-to-day tasks. Cassidy made it easy to layer in brand voice, house style, and usage guidelines. The Assistants they built weren’t just functional.

They felt familiar and aligned with how each team already worked.

Crain didn’t need an army of engineers or a months-long implementation. They just needed a platform that made sense, a few clear ideas, and people who were open to trying something new. Cassidy proved that AI doesn’t need to be complicated. It just needs to work.

The Foundation: A Scalable Assistant-Building Framework

Crain’s approach to scaling AI started with what they call the “sourdough method” — a way to build new value on top of what’s already working, instead of reinventing the wheel every time. 

They developed internal frameworks that turned repeatable tasks into scalable Workflows. It gave teams a simple way to create Assistants they could refine, reuse, and share.

“We encourage people to become architects of their own Workflows,” Marisa said. “If a task has four phases and two of them can be AI-supported, that’s a candidate for an Assistant.”

That mindset unlocked a range of practical applications across their editorial teams. Instead of centralizing every decision, Crain empowered writers, editors, and audience managers to build tools based on the way they already worked.

And they didn’t stop at building Assistants. They optimized everything around them.

Different Use Cases 

Once a story was written, the team could immediately spin up extensions of that work across multiple formats and platforms.

Some of the most used Workflows included:

• Headline variants: Creating multiple title options aligned with each brand’s tone and use case.
• Editing support: Reporters built their own editing Assistants to streamline structure, readability, and style alignment before the editor’s review.
• Metadata and SEO summaries: Generating optimized summaries for search and syndication.
• Social media captions: Translating long-form reporting into channel-ready posts.
• Content format translation: Turning event FAQs or editorial recaps into different article types, perspectives, or audience formats -— including promo-friendly copy that helps drive event awareness and registrations.
• Newsletter blurbs: Quickly pulling story summaries into email-ready text.
• User needs model support: Classifying stories based on a 16-need framework across publications and helping teams apply that framework more consistently to improve story focus and audience relevance.
• New task adoption: When teams were required to add new story takeaways or formatting, Assistants were introduced alongside those tasks to make the transition easier.

Cassidy’s tools and extensions helped meet Crain’s team where they already worked.

• Chrome Extension: Used daily for AI-assisted writing, research, and quality review in the browser.
• Slack integration: Many team members preferred accessing Cassidy directly in Slack, especially for quick tasks and structured Workflows.
• Prompt Library and Workflows: Used by admins and editors to batch process file types, convert formats, and support heavy-lift editorial tasks without relying on engineering.
• Copilot and Document View: Editors relied on Cassidy’s document mode to cleanly input house style rules, context-setting material, and better instruction formatting for Assistant creation.

Cassidy gave Crain a way to capture the creative thinking already happening across teams and turn it into tools they could reuse, refine, and share. 

Cassidy Met the Needs For 26+ Different Brands 

Crain oversees more than 20 distinct publications, each with its own editorial voice, style, and audience. To support that complexity, Cassidy’s Knowledge Base system became the backbone of their AI setup.

Each brand has its own workspace, complete with:

• Style guides
• Voice and tone references
• A Context library (Who we are, How we work, What we cover, Where it goes)
• Assistants built for brand-specific tasks

Crain’s editors can easily switch between brands, update shared resources, and onboard new team members without duplicating work. 

“Once we kind of set up those information sharing guardrails and our house style and our style guides, we can build faster every time,” Marisa said. “We have a new idea for an Assistant—it can be done much quicker now because we already have a lot of those blueprints put in.”

As usage grew, many Assistants became intelligent enough to automatically detect which brand they were supporting. Whether it was Modern Healthcare or Pensions & Investments, Cassidy would reference the correct style guide and return brand-aligned outputs.

Support at Every Step

Cassidy fit neatly into Crain’s existing tech stack, offering direct integrations that amplified what teams were already using. It also gave them the freedom to experiment with different language models like Claude, GPT, and Gemini to see what performed best.

The Cassidy Slack integration became the default way many reporters and editors interacted with the tool. 

Instead of needing to learn how to use a new app, they could help with instructions, content, or Assistant responses without leaving their daily workflows. Editors use it to quickly check Assistant instructions against the content they’re working on, test model output, or refine inputs.

Crain’s adoption hasn’t stopped at Assistants. They’re now expanding into Cassidy’s Workflows, using the platform to automate multi-step processes.

Marisa is currently completing a Cassidy Workflows course, with plans to roll out new implementations in early 2026. The goal is to reduce dependence on dev teams for tasks like:

• Reformatting source content
• Generating batch outputs across publications
• Creating internal tools for reporting or guided analysis

At the same time, Cassidy’s prompts library has become an underrated asset for operations and admin users. Marisa describes it as a “secret weapon” for converting files, generating spreadsheets, or transforming structured content behind the scenes.

Support at Every Step

From the first day using the product, Cassidy’s team was there to help Crain get started. 

Support meant more than just answering questions. It meant showing up, helping refine ideas, and working through the details when things got tricky.

Cassidy’s support team helped Crain establish confidence with the platform early on. They made it easy to ask for help, encouraged experimentation, and offered clear, tactical advice when Workflows became complex. That approach made it easier for teams to try new things without getting stuck or slowing down.

“What I like about the Cassidy team is sometimes I’ll hop on a call and they don’t just ask what we want to solve long-term,” Marisa said. “They ask, ‘What do you need to solve today?’ Then they immediately start helping us figure it out. It’s really practical and exactly what we need.”

As more teams joined and new Assistants were created, Cassidy stayed involved. They helped Crain test models, adjust logic, and build tools that matched the way people actually worked.

“It would be really hard to pull [Cassidy] away now,” Marisa said. “It has become part of our daily workflows. It’s not just helpful, it’s essential.”

Crain didn’t choose Cassidy for a quick win. They chose it because it delivered real results, a strong partnership, and lasting impact.

Bring Scalable AI to Your Team

Whether you’re scaling content, streamlining operations, or supporting cross-functional teams, Cassidy helps you turn good ideas into repeatable systems. We don’t just deliver AI capabilities. We work with you to make them stick.

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