close up of vintage Maskatron action figure
PHOTO: JD Hancock

It seems as if almost every martech article these days includes a reference to artificial intelligence (AI). And for good reason — earlier this year, Gartner reported AI use in the workplace had grown by 270% in the last four years, with only more growth predicted on the horizon.

Beyond the Hype: Defining AI

Everyone is talking about AI and machine learning, but what do they actually mean? AI is technology that work, think and make decisions in a similar fashion as humans. It’s critical to driving automation and eliminating manual tasks so marketers and creatives can focus their time and energy on more valuable, strategic work. Machine learning is a subset of AI that goes one step further: machine learning means the tool continuously learns on its own so it can automate more processes and day-to-day tasks over time.

AI and machine learning are quickly becoming significant competitive differentiators in customer experience (CX). So where can you apply AI and machine learning to your own content solutions, including digital asset management (DAM), so you can work faster, smarter and better?  

Here are the top three areas where content teams can gain more value using AI.  

Related Article: The AI and Machine Learning Revolution Is Coming for Content Marketing

1. AI Cuts Down Content Creation Times

Applying AI to the content creation process can automate and streamline project management. Examples include:

  • Intelligent workflows: AI-driven content workflows can dynamically adjust to ensure work is done in the right order by the right teams. Was there a delay or extra revisions ordered on a piece of content? Intelligent workflows can automatically change and edit timelines. Was there a change in scope of the content? AI can dynamically adjust the workflows so they are routed to new teams that might need to get involved.  
  • Smart rules: Is your project manager spending too much time routing content requests to creatives and designers? Smart rules that dynamically link and associate different content requests together can help automate manual project management overhead, ensuring the quickest time to market while freeing resources to work on higher priorities.   
  • Balancing workloads: How often is there an imbalance in workload for you or within your teams? AI can help load balance content creation among creatives, copywriters and designers, so that work is appropriately routed to the right person or team.

Related Article: 12 Ways AI Has or Will Change Content Management

2. AI Makes it Faster and Easier to Manage and Find Content

A marketer once told me it takes her hours to find content because she must email, call and walk to designers’ desks just to find the right content. Content solutions with AI included can help make this easier with:

  • Automatic content tags: Many marketers and creatives spend an inordinate amount of time tagging content so that others can easily find and reuse that content. AI has the ability to understand the subject of a piece of content on its own and then automatically assign it the appropriate tags.
  • Machine learning tags: Automatic tagging is great, but it typically only tags descriptive elements of content. Imagine if you are a marketer for You don’t want to know just what type of dog is in the picture, but also which Chewy-sold product is in the picture. Machine learning tags can learn about the products and business-attributes that are specific to your business, eliminating manual tagging and making content more findable.
  • Visual searches: Like many marketers, I often spend countless hours looking for an image similar to one I have seen online, but more specific to my own brand. AI can help by automatically analyzing attributes of content, and then looking for content that’s similar within your existing brand content.    

Related Article: What it Takes to Deliver Successful AI-Driven Search

3. AI Makes it Easier to Reuse Content

Lastly, content teams can use AI to help repurpose and reuse content:

  • Autocropping images: Marketers constantly need to re-use existing content on different channels. But given different channel specs, they may need different crops and resolutions (think Facebook banners on mobile, for example). This process typically requires support from a designer to ensure accuracy and quality, which leads to longer lead times. AI can help by automatically identifying image focal points and cropping content differently based on the intended channel.
  • Analytics can lead to optimization: AI for content reuse has a lot of future potential: one area includes the use of analytics. Organizations are creating a lot of content, but very little of that content gets used — only 35% according to SiriusDecisions. Content marketers must evaluate the ROI of the content they create and, in the future, consider how they could use AI to automatically identify content trends that can inform future content strategy.

Do you currently use or plan to use AI your content teams? We’d love to continue the conversation and hear from you in the comments!