4 Predictions for the Future of AI in Marketing
Artificial intelligence (AI) advancements are showing no signs of slowing down. With new developments coming on the market daily, there’s now a decent amount of options for businesses to get a helping hand with many tedious and administrative tasks.
From the marketing perspective, the area with the largest room for productivity gains come from the creative side. Working with hard-to-manage visual assets, which have very little “data” associated with it comes with a wide set of challenges. But, as AI progresses, I anticipate we’ll see major advancements in how AI can help marketing teams make the most of their visuals.
Here are 4 predictions on how AI will enhance visual marketing.
For many organizations, change is a constant — branding updates, acquisitions, mascot updates, product launches, etc., lead to small, but continuous design changes. This can be a major pain for marketing and creative teams, who are responsible for making those updates across all pieces of content — website pages, PDFs, print materials. Not only is this incredibly tedious, it also leaves the organization susceptible to human error that can lead to market confusion and brand deterioration.
As AI begins to understand design files, like InDesign and Photoshop, AI models will be able to learn to make these kinds of updates instantaneously. Similar to the find-and-replace feature available for Word documents, AI will be able to recognize a new version of an asset — for example, a logo — and replace the previous version across all design files. These revisions could then automatically be replaced in the organization’s digital asset management system as a new version.
Outdated Collateral Identification
Managing discontinued products is another thing that can take up a significant amount of time for marketers. While this is often most associated with the retail industry, it’s also applicable across many more industries. The hospitality, technology and manufacturing industry, for example, all handle their own form of closures, discontinuations or “sunsets” of products. When a product is discontinued, so begins the painful task of hunting down and removing the product from each and every piece of collateral. It can be tireless and thankless work, but very necessary.
In the not too distant future, it’s likely that AI models will be trained to identify and flag pieces of collateral that contain discontinued items. Using the advancements already being made with customized AI capabilities, AI models would understand how to recognize the product by its physical characteristics, as well as associated SKU number, name and price. When a product is labeled as discontinued, the model could then quickly scan all advertisements, catalogues, pricing sheets, etc., and notify the marketing team of which pieces need to be updated.
Content personalization is already a well-known application of artificial intelligence — one that’s being taken advantage of by many marketers today. Using customer data, history and preferences, AI models can predict which pieces of content will resonate with each individual customer and serve up that content. While this is applicable for blog posts, videos, ebooks and other text-based content, AI is still yet to offer content personalization for images.
This will likely change in the coming years. Artificial intelligence has had a huge impact on images as of late, enabling the auto-tagging of images with critical information like object, colour and text recognition. Using these additional pieces of information, there’s no reason that an AI model couldn’t surface images in each customer’s preferred style, colors, etc. When connected to a digital asset management system, it would also open up the AI model’s ability to select from each and every image available in the organization.
Suparman Widjaja, technology manager for Verizon’s creative marketing group, shared his insights on how artificial intelligence could help optimize campaign success.
“There are so many opportunities to use artificial intelligence in our industry — specifically, to expand into more marketing and creative use cases. For example, AI could help our team predict the success of certain assets based on campaign goals, and identify assets that would be more successful based on campaign attributes, target segments, season, etc. As we measure the outcomes of these campaigns, we could feed the output back into the AI engine to continually improve its accuracy.”
He continued, “I’d like to be able to train models to analyze our copy and assets to help identify a strategy for each campaign. These kinds of output, while unable to replace human creativity, can significantly reduce the time we spend deciding on the focus for our creative work.”
Artificial Intelligence for Digital Marketing
While artificial intelligence still has a long way to go, there are plenty of ways to infuse AI into your digital marketing strategy today. Download your copy of 8 Ways AI Can Power Your Digital Strategy to see how you can get started.