AI Is Your Bridge to Smarter Content Operations

As a content operations leader, you know a strategic investment in content is a powerful lever for delivering better customer experiences and preparing your organization to be resilient to change. 

But if your team is just getting started and has limited resources, how can you figure out where artificial intelligence (AI) fits without feeling overwhelmed? You’re navigating siloed workflows and inconsistent content processes; scaling feels slow and clarity is distant. 

You need to move from chaos to confidence so you can sustain, scale, and thrive, and I believe that AI is a major part of that journey, even during the early content ops days. How can you incorporate AI before you feel ready? The answer is a hybrid content operations approach.

This article explains my journey toward a hybrid content operations approach and a few key lessons learned along the way.

Our Content Ops Opportunity

Calix is the leading provider of cloud and software platforms, systems, and services for internet service providers. When I joined their customer success team in January, content operations was unstructured and not embedded across teams. Customer enablement content was abundant but lacked strategic oversight and discoverability. Performance-based content review was novel, and our content management muscles were underdeveloped.

I quickly saw an opportunity to introduce scalable, data-informed practices to elevate content relevance, improve the customer experience, and foster cross-functional alignment. Recognizing the importance of planting seeds of change early, I aligned with stakeholders in Marketing, Product, Customer Support, and Technical Documentation to build momentum and shared ownership. Knowing we weren’t ready for complex, centralized activities, I tested a hybrid approach.

Meet Hybrid Content Ops: A Step Between Early and Mature

The hybrid content operations model offers a clear, flexible framework that blends structure with adaptability. By combining shared standards and tools with AI support, teams can work efficiently, test ideas, and mature their content operations without sacrificing trust or quality. 

The hybrid mindset embraces “fail-fast, learn-faster” because you’ll gain insights even if individual projects fall short in the beginning. If you want to grow confidently and deliver better experiences with AI-supported activities now, not years from now, consider these three practical examples from my team’s playbook to inspire your own path.

A Glimpse into Our Hybrid Content Ops Playbook

Throughout 2025, we explored resources from Content Science—including their research-backed content operations maturity model—Gartner, Zendesk, and Marketing Profs to create our own hybrid playbook. We combined proven best practices from content ops, marketing, and post-sale customer enablement to build a system that supports collaboration and calibrates to meet our evolving team needs. These examples are especially helpful if (like us) you’re dealing with tool limitations, minimal data support, and limited creator bandwidth.

1 Confidently Communicating Content Ops Value

A new content operations team succeeds only when colleagues and customers understand its purpose and value. This is critical during early manual content activities that involve tough change management conversations. To showcase our team across Calix, we created a domain-specific AI assistant to:

• Describe our work in ways that reflect Calix culture and strategic priorities.
• Reframe our goals and outcomes using discipline-specific language.
• Connect our first-half vision to second-half results to show intentional impact.

If possible, you should start this project early so the assistant learns alongside your team and grounds big ideas in proven paths toward maturity.

2 Smarter Content Cleanup Before a Content Management System

To simplify content cleanup even without dedicated content tools, we paired Excel with Copilot to get the job done. Instead of manually building Excel formulas, we used Copilot to draft VLOOKUPs and Pivot Tables to match our content filtering needs. This made it easier to review content data and identify outdated ownership and product names. 

Then, we manually validated results to build trust at each step. Now, with a few clicks, we can easily find hundreds of customer-facing assets that underperform and no longer require customer visibility. We implement governance quickly and direct limited bandwidth toward low-effort, high-value batches of content for our Quarterly Review.

3 Responsive Content Templates Before Dynamic Content Features

For this project, we created a generative AI (gen AI) and natural language processing (NLP) assistant in Copilot to analyze high-performing content and generate templates that streamline creator output. In the long term, this will support dynamic content creation; today, we delivered ten new templates that:

• Are reusable, brand-aligned, and in Word doc format (our creators’ preferred tool).
• Combine similar sections to cut template volume by 75%.
• Include tips to add helpful links from other content channels.
• Provide AI-supported recommendations to match creator intent with the best template choice.

The fourth bullet reflects the “responsive” aspect because we trained the assistant to recommend the ideal template based on goals, audience, length, and similarity to high-performing assets. This assistant:

• Teaches creators how to use the templates in real-time.
• Reduces duplication because every template fits distinct customer needs.
• Tracks creator trends and provides feedback to our team on how to improve the agent and the templates.

We believe this project has major potential to scale, such as training the assistant on our entire content inventory to eliminate redundant content and recommend template changes based on customer behavior.

Summary: Sample Steps in Hybrid Content Operations

To move from no content operations to level two (piloting) in the Content Science maturity model, we took steps like these. Consider such steps in your own journey.

Need: Create and Share Your Team’s Vision

• Build a domain-specific AI assistant to help you define vision and strategy, align with industry best practices and business priorities, and communicate intent with executives.
• Add stakeholder details, progress, roadblocks, timelines, and more to enhance your domain-specific AI assistant and evolve it into your personal historian.
  

Need: Faster Content Cleanup / Maintenance

• Select a manageable content group and export to Excel.
• Use GenAI to support rapid creation of formulas, VLOOKUPs, and Pivot Tables to streamline cleanup.
  

Need: Start Content Governance

• Gather creator feedback, use AI to condense high-performing content into fewer impactful templates, and test with creators.
• Collect feedback on template usage, refine the assistant for real-time recommendations, and analyze creator behavior for continuous improvement.

Our Guiding Principles Moving Forward

The hybrid content operations model works because it relies on three pillars: a clear content vision, cross-functional strategies, and white-glove onboarding that empowers our stakeholders to succeed. Our team is growing, and we’ve helped roles across Calix stay agile by embracing these guiding principles:

• AI supports, but will never replace, your human-led strategy.
• AI tools need regular care just like any other system.
• Content quality will always matter more than the technology behind it.
• Reliable results can only come from clean data.
• If you prioritize progress over perfection, you’ll probably enjoy the journey more.

Your team’s AI journey doesn’t have to be seamless; it just has to begin. Hybrid content operations can help you mature faster without sacrificing excellence.