How to Create Better Content with AI

We’re now in Part 3 of our series on how EM Marketing marketing experts are putting AI to work in their own practices. This installment covers Content, Creative, and Editorial Quality, including the full production lifecycle – long-form guides, blog operations, social content, video, and AEO/GEO. Read on!

How to Get Cited in AI Answers while Sharing Human Stories

Milly Skiles built a repeatable content framework for a mental healthcare client aimed at answer engine optimization (AEO) and generative engine optimization (GEO). The goal was to build content that achieved AI visibility, but also provided what humans want – real stories and lived experiences. Every piece follows the same blog recipe: an answer capsule at the top, question-format subheadings with their own mini-answers, expert quotes, a case study, and an FAQ.

AI wrote every first draft, and Milly used her background in journalism to challenge AI and thoroughly edit every piece before it shipped. She connected Claude directly to her Ahrefs account for keyword research, which keeps the framework grounded in real search data. She compares her role to why people go to legendary music producer, Rick Ruben. Although he claims to have no musical ability, what an artist pays him for is taste. That’s how she uses AI.

A Human and AI Cooperative Intelligence for Content Editing 

Larice Addamo serves as a human-in-the-loop expert evaluator to oversee AI-written content. In her example, a client had produced a 180,000-word industry guide written by multiple contributors to establish authority for their niche. Larice conducted an “eagle eye audit” in two editorial phases. She started with AI editing tools to clear mechanical, syntax issues at scale. Then she did a manual pass to establish proper cadence, data continuity, and a cohesive, high-end leadership voice.

The process compressed a project timeline by roughly 60%, work that would have been impossible to hit on a standard manual schedule. Larice frequently applies this “cooperative intelligence” to other projects such as e-commerce and digital storefronts. When managing multi-page campaigns or long-form content, running a data contradiction audit through AI can result in a pristine consumer experience.

A Scalable Content System for Multiple Microsoft Business Units

Tai Freligh, a writer and content strategist, worked as a Senior Copywriter at Assembly Media, where he supported Microsoft’s blog team. Each business unit had its own voice, cadence, and platform requirements. There was no unified process behind any of it, which meant uneven quality and missed deadlines. Tai built an AI-assisted process to standardize the workflow and scale the system across units. The intake form gathered the appropriate details from stakeholders, then fed those into a structured prompt framework that generated copy drafts with three tone variations.

He split the work across four different AI tools by function: Claude for structure, Copilot for internal research, Gemini for data validation, and ChatGPT for content repurposing. Most importantly, in the end a human edited everything. Turnaround dropped from days to hours, even while supporting multiple business units at the same time. Tai built a scalable system that allowed the team to plan proactively and to accelerate execution without sacrificing quality.

Enhancing a Video Team of One after Budget Cuts

Creative strategist Molly St. Louis had to rethink video production for a startup that was newly acquired by a Fortune 500 company. External video agencies were eliminated, forcing her to rebuild the pipeline herself. Molly turned to Adobe Firefly for on-brand imagery, Runway to animate stills into directed clips, and ElevenLabs for voiceover. To avoid the flat, robotic AI-voice problem, she performed every voiceover herself with real emotion, then converted it to the specific voices needed.

Molly says working with art directors is always better, but in order to produce quickly with a one-person team, using AI was a good solution. Her prompting approach was to direct AI the way a filmmaker directs a shoot, specifying camera angle, motion, and emotion. The resulting videos outperformed some of the company’s own expensive conference videos, and the teams got what they needed within their quick timeframe.

Building a Content Machine for a Resource-Strapped Startup

Audrey Tracy was the second hire at a local-business marketing agency startup and used AI to stand up an entire content function starting from a half-written marketing plan. The deliverables included strategy, an editorial calendar, brand guidelines, as well as blog and social content. She also built a custom content agent, trained only on the company’s own marketing documents, to keep output on-strategy.

Another vivid example came from customer success stories at Pinterest. She could feed raw customer information into AI and get the success story that could be dialed in as much as needed with the Pinterest brand voice. She describes AI as a partner that can help with quick content work and strategic business questions.

Redirecting Hours of Production Time Into Strategy Work

Stephanie Maassen-Deason built a social content system for a multi-location local service business. Each stage of the customer funnel – awareness, consideration, conversion, and post-purchase – got a reusable prompt framework. The prompts were encoded with brand voice, audience psychology, and a specific conversion goal. AI generated first drafts, then it had to pass Stephanie’s editorial review before going into Canva for graphic production.

Stephanie trained Claude to create social posts at scale, based on an understanding of the client’s photos and sample content she had written herself. The system freed up roughly 87% of the time spent on production, cutting 10 to 15 hours a month down to under two. The client got more on-brand content, more consistently.

Want This Kind of Thinking on Your Team?

EM Marketing’s experts know how to put AI to work on everyday marketing problems. Just as importantly, they know where their own judgment still has to lead. If your team needs that kind of thinking, on a project or full engagement basis, let’s talk about which of our consultants is the right fit for what you’re building next.

This is Part 3 of a four-part series. Catch up on Part 1: Strategy, Positioning & Research and Part 2: Demand Generation & Paid Media. Next up: Marketers Who Build AI Tools, where we look at EM consultants shipping real software with no formal engineering background.