The use of AI tools in marketing departments, creative agencies and newsrooms is up year-over-year. Today, over 60% of marketers are using AI in their program activities, according to Influencer Marketing Hub. However, less than half are using AI for content production. What’s behind this hesitancy? At least in part, because 75% of people fear AI-generated content will misinform them.
Below we’ll cover best practices to help marketers alleviate their fears and begin to smartly embrace generative AI in their content marketing strategies.
Where AI excels in content marketing
From ideation to final finessing, AI can benefit each stage of written content production: 1) content development, 2) editing & refinement, 3) adapting & syndicating
During content development, marketers can save loads of time by using AI to research topics, cull together data points, find previous quotes, and dig up background with ease. Then, they can jumpstart the writing process by using AI to deliver outlines or rough drafts. AI also helps put on the finishing touches. For example, at Alloy, our writers use AI to generate multiple headline options quickly.
Once marketers move to the editing and refinement phase, passing the content through an AI tool can eliminate typos and errors and alert writers to issues before a draft ever hits a human editor. By using custom rulesets and style guides, the AI editor can also ensure the content tone matches brand preferences. And finally, AI tools can alert writers to unconscious bias in language so they can be more intentional going forward.
Finally, adapting and syndicating content is a primary strength of gen AI. From tailoring content to unique audience needs and challenges to repurposing content in multiple formats to SEO optimization, AI is a key tool in building up your content arsenal.
The limitations of AI in content
AI tools are trained on previous content, therefore, they are solid at recapping established ideas. However, they fail at taking a new opinion or premise and fleshing it out. Simply put - the need for great writers and thought leaders isn’t going away.
And that’s not the only pitfall of AI in content generation. Other, notable risk points include:
Plagiarism: Nearly 60% of AI-generated content contains some form of plagiarism. (Copyleaks)
False Information: In the 2nd half of 2023, websites hosting AI-created false articles increased by more than 1,000%. (NewsGuard)
Bias: AI systems often produce results that reflect & perpetuate human biases within society. USC researchers find bias in up to 38.6% of “facts” used by AI.
Lack of Nuance: AI tools have limitations in their ability to understand context, tone and nuance, resulting in lack of depth & meaning.
Timeliness: Recent news may be limited to premium users, meaning the information you reference could be outdated.
Privacy & Security: Remember, you’re giving AI tools the rights to everything you put in them …and then some.
But marketers who keep these limitations top of mind stand to maximize AI’s potential in content. At the most basic level, here are the do’s and don’ts we follow at Alloy when using AI in content:
Do:
Have human oversight over every generative AI tool you use.
Use AI tools for ideation, thought-starters and for refinement.
Double-check that any ideas that make it into your final draft are properly vetted and cited.
Save the output of your AI to compare to the final version
Don’t:
Publish anything directly from an AI tool.
Include any proprietary info into prompts (e.g., private company financials, news that has not been made public, etc.).
Publish translations created by AI.
Use generative AI tools to create imagery, likenesses, or avatars that create the appearance of diversity.
Use AI-based recording tools to capture conversations where private data is shared.
Interested in more ways to integrate AI into your MarTech Stack? Read my colleague Jennifer’s latest blog entitled AI’s impact on web design & development today.