7 steps to scale your content creation process in the world of AI

With Google’s increased focus on reducing low-quality content in search results, marketers are questioning the role of AI-generated content. However, regardless of how it’s created, Google’s primary concern is content quality and helpfulness to users. As long as the content provides value, expertise and a good user experience, the creation method doesn’t matter. 

This article presents a seven-step process for scaling content production by strategically integrating AI while ensuring the output meets Google’s standards for high-quality, audience-centric content.

Google’s stance on content and AI

Google’s stance on content prioritizes user-centricity, emphasizing its quality, helpfulness and authority. This approach is reflected in Google’s algorithm updates, which focus on enhancing user experience and relevance. Content creators should prioritize crafting valuable, expertly crafted content that provides a seamless on-page experience. 

While Google’s guidelines don’t dictate specific creation methods, they stress the importance of user value. Effective content strategies can leverage AI alongside human insights to produce high-quality, people-first content. 

Dig deeper: Google’s shifting approach to AI content: An in-depth look

A 7-step process for scaling content with AI

How can you create great content that adheres to these guidelines while using AI as a tool to do it at scale? It starts with building the right foundation and understanding your audience. Crafting high-quality, user- and search-engine-friendly content that boosts business revenue is now more complex.

As generative AI models like Gemini, ChatGPT, LLaMA and others continue to learn from the content published on websites, creating the right helpful content that will answer user queries is paramount. Identifying the right topics for the content, creating it in a consistent brand voice and targeting the right end audience(s) takes time and resources.

We’ve outlined seven steps for brands to create effective content plans using AI. These steps cover everything from brainstorming ideas to measuring success, ensuring content is valuable to users and performs well in search.

• Knowing what to write (content intelligence).
• Mapping the brand voice, tone and journey for content.
• Generating content with topics and brand voice.
• Optimizing content for entities and related topics.
• Establishing content distribution workflows.
• Ensuring page experience, technical foundation.
• Measuring and analyzing performance (content analytics).

Step 1: Knowing what to write (content intelligence)

Content intelligence aims to provide data-rich information to the user that helps them make informed decisions. The biggest hurdle for content creators is knowing what content will resonate with the audience and perform well. 

Creating a high-impact content strategy requires research, data and time. Begin by identifying your customers’ problems and crafting compelling topics and sub-topics. Analyze existing content, competitor content and search trends with AI assistance to pinpoint gaps, strengths and opportunities.

With this information, marketers can develop a content roadmap, prioritizing what performs well, what needs improvement and what new content is needed.

Step 2: Mapping the brand voice, tone and journey for content

Ensuring a uniform brand voice across various content platforms like web, email, social media and paid campaigns poses a challenge for any brand.

Ideally, AI initiatives should analyze and understand your brand’s voice and audience preferences, creating a concise guide outlining tone, language and audience personas.

This becomes the blueprint for content creation, guiding teams to produce on-brand and audience-aligned consistent content across all channels.

Step 3: Generating content with topics and brand voice

Writing and editing for brand consistency is time-consuming yet essential. By identifying content gaps and a clear brand voice, AI can rapidly incorporate ideas, targeted phrases, insights from authoritative sites, audience interests and relevant data, such as events or pricing, to generate content outlines or drafts in seconds. 

This approach saves time, shifting the focus to refining and enhancing the content for consistency and impact.

By leveraging AI, creators can generate a wide range of content tailored to their audience’s needs. Here are several vertical-specific examples:

• Some use cases for the hospitality industry include suggested travel itineraries, promotional materials, blogs, social posts and landing pages about local events and things to do.
• In healthcare, AI can assist in creating patient education materials, research summaries and health advice articles.
• Banking content creators can use AI to demystify financial concepts through informative articles, market updates and personalized investment advice.
• Automotive content creators can leverage AI to produce detailed car reviews, maintenance tips and industry news articles.

The goal is to ensure all AI-powered content is contextually relevant by introducing custom variables such as topics, keywords, brand voice, target audience, etc. 

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Step 4: Optimizing content for entities and related topics

Content is only effective when it is discoverable, relevant and offers expertise to your target audience. Establishing prompt guidelines helps ensure your output meets best practices, like content quality, length, meta information, topics, subtopics and entities. 

Running through a robust checklist simplifies the process to quickly check against what AI tools have gotten right and what elements need to be enhanced by human editors. 

Ideally, AI tools should have a prebuilt advanced prompt, an SEO checklist and workflows to optimize the content generated so that authors can build better quality output.

Step 5: Establishing content distribution workflows

Once good quality content is created, you must ensure a rock-solid experience across all channels and locations. 

AI-assisted content should seamlessly go through the distribution workflow, which could involve directly publishing to your CMS or exporting it in various formats for integration into standard workflows. 

Ensure that all media assets, like images and PDFs, are included to maintain a consistent and high-quality user experience across platforms. Workflows to translate content in various languages should also be part of content distribution journeys.

Step 6: Ensuring page experience, technical foundation

A website’s page experience directly affects user satisfaction. Slow-loading pages increase bounce rates and harm engagement.

Pay attention to your Core Web Vitals and improve your site’s performance. A solid technical setup ensures a secure and user-friendly site. Together, these elements enhance user retention, engagement and conversions.

Step 7: Measuring and analyzing performance (content analytics)

If you can’t measure it, you can’t improve it. Identifying the right KPIs before publishing content is important to ensure the analytics data layer is in place to see and validate the impact. Analyzing content reach and effectiveness is essential for creating a feedback loop for content intelligence.

By closing your content gaps, you’ll gain valuable insights into what topics or types of content you should focus on next. This lets you keep moving the needle on discoverability and revenue.

Integrating AI into each part of this strategic seven-step approach to content creation allows for scalability in this evolving landscape. From identifying the most impactful ideas to generating rich, optimized content to publishing and measuring results, integrating AI allows for efficient, targeted and measurable, qualitative content creation.

Dig deeper: How to safeguard your content strategy in an AI-driven search landscape