It’s 3 p.m. on a Tuesday, and you’re staring at your content calendar absolutely paralyzed. Before Friday, you have six blog posts to publish, an e-book to produce, two newsletters to ship, and you’ve been promising your CEO you’ll update the website copy for months.

Oh, and did we mention you need to do all this with a scrappy team of two, plus Jeff the intern?

If this scenario hits a little too close to home, you’re not alone. Across industries, marketing teams are shrinking while content demands balloon. B2B companies now juggle an average of 10 channels in their buyers’ journeys — double what they handled just eight years ago. Meanwhile, 78% of marketers report having small teams of just one to three people, and almost one-third (28%) have lost team members to resignations in the past year alone.

But here’s what’s interesting: Some teams are actually thriving in this environment. They’re producing more content than ever while maintaining quality (and staying sane to boot). These are the teams that’ve learned to leverage a smart combo of AI automation and human expertise — a formula we’ve seen work consistently here at Contently.

Here’s the five-step playbook helping marketing teams break out of the hamster wheel.

Step 1: Map Your Content Chaos (And Find the Time Vampires)

Before you automate anything, you need to know where your time actually goes each week. Many teams discover they’re spending hours on tasks that feel productive but don’t move the needle (that 45-minute Slack debate over “use” vs. “utilize” comes to mind).

Start by tracking everything for one week — every brainstorming session, research deep-dive, and approval process. You might uncover patterns like:

• Research rabbit holes: Wasting hours researching a single blog post
• Approval ping-pong: Content bouncing between 4-5 people for weeks
• Format wrestling: Spending hours adapting one piece of content for different platforms

Once you see these patterns, set specific, concrete targets like:

• Cut research time from three hours to 45 minutes per piece
• Reduce approval cycles from two weeks to three days
• Increase monthly output from eight to 12 pieces of content

Step 2: Outsource the Grunt Work to AI

Once you’ve mapped out your content-related bottlenecks, you’ll have a clearer idea of where AI can help. This might include tasks like:

• Brainstorming and generating blog topics
• High-level research
• First-draft writing for straightforward content like landing page copy, SEO-focused blog posts, product descriptions, or email templates
• Headline optimization, metadata, and social media captions
• Content reformatting across platforms
• Competitor analysis and trend identification

Instead of spending half a day researching industry trends for a thought leadership article, you can have AI compile the initial research in 20 minutes. Your human expertise then goes into analyzing those trends, teasing out unique insights, and giving the piece a punchy, snappy voice (that you can then train the AI to replicate for future content).

Step 3: Hand Human Editors the Reins

AI can write, but it can’t think like your brand. This is where human editors are more valuable than ever. They can step in for high-value tasks like:

• Strategic direction and messaging
• Brand voice refinement
• Thought leadership
• Complex storytelling
• Judgment and critical thinking
• Fact-checking and final quality checks

Think of your editor as a brand translator. They take AI’s efficient (but often generic) output and transform it into something that sounds distinct and authentic.

And for regulated industries, this editorial layer is non-negotiable. If you work for a healthcare or financial services company, it doesn’t matter if AI cuts your content production time in half if hallucinated claims in a blog post lead to expensive, arduous regulatory reviews.

This is where Contently’s Managing Editor model shines; our editors are trained to work alongside AI tools from the get-go, ensuring every piece meets enterprise standards for accuracy, brand voice, and compliance while maintaining the speed advantages that make AI so appealing.

Step 4: Track Metrics That Actually Matter

Don’t just measure AI success by how much content you’re pumping out. Track the metrics that tie back to real business results.

Efficiency metrics to watch:

• Time from concept to published piece
• Hours saved per piece of content
• Content pieces published per team member per month

Quality metrics that matter:

• Average time readers spend on your content
• Share and comment rates
• Conversion from content to leads or sales

Step 5: Launch a 30-Day Pilot Program

Don’t overhaul everything at once. Pick one content type where you can easily measure success, like blog posts, social media updates, or email newsletters.

Then, run a 30-day test with clear parameters:

• Week 1: Set up your AI instance and begin simple writing tasks. Upload 1–2 strong brand voice samples and create detailed briefs for each content type to give the AI clear guidelines.
• Week 2: Start generating first drafts for straightforward content (e.g. landing pages, SEO blog posts, product descriptions). Use your brand voice samples, style pillars, and editorial briefs to train the AI on your tone and messaging.
• Week 3: Review AI drafts, provide structured feedback, and refine output quality. Expand into more complex content types and begin experimenting with repurposing (e.g. blog-to-social snippets, newsletters-to-LinkedIn posts).
• Week 4: Use AI for optimization tasks (headlines, meta descriptions, CTAs) and begin exploring more strategic uses based on what you’ve learned — such as competitor analysis or content gap research.

During the trial, get feedback from everyone involved: writers, editors, designers, and the execs approving content. Ask specific questions about which parts of the process feel smoother, and where AI outputs need the most human intervention.

Turn Content Challenges into Opportunities

At Contently, we’ve seen this playbook’s effectiveness in action: An online K-12 provider ran a 30-day sprint trial following this rough outline. Partnering with a Contently Managing Editor, they combined AI-powered content efficiency with human editorial oversight — and jumped from 3% to 55% visibility in AI search results, claiming the #1 spot across multiple AI platforms for eight of their ten target queries.

By strategically integrating AI with editorial expertise, even small teams can significantly boost output while maintaining both quality and compliance. This five-step process provides a measured approach to combining creative insight with clear, tangible results — and turns content calendar panic into a manageable, scalable system.

Ready to expand your content operation?

Discover how Contently’s AI Studio can empower your team to generate a high volume of quality content with your existing resources. Schedule a personalized demo to see our AI + editorial workflow in action.

Frequently Asked Questions (FAQs)

How does integrating AI with editorial oversight benefit my content strategy?

Combining AI with editorial oversight enhances productivity by automating resource-intensive tasks while ensuring that the final content upholds the highest possible quality, maintains brand consistency, and meets compliance standards — allowing teams to focus on nuances that require human judgment or expertise.

What types of content workflows are best suited for AI automation?

Workflows that involve repetitive, time-consuming tasks such as data aggregation and drafting initial versions are well-suited for AI automation. This allows human editors to add value through creative storytelling, strategic planning, and detailed refinements.

How can I measure the success of an AI-driven content strategy?

Success can be measured by tracking key performance indicators (KPIs) like total content output, cycle times, engagement rates, conversion metrics, and overall return on investment (ROI). Contently’s analytics dashboard provides real-time insights to compare performance before and after integrating AI into your content creation process.