The gains in employee productivity promised by AI can seem almost too incredible to believe. For example, PwC found that AI could add up to $15.7 trillion to the global economy by 2030. At the same time, generative AI tools are already increasing business users’ throughput by 66%.
For those working in especially iterative roles — like the 33.4% of people working in marketing who spend around three weeks each year just searching for pictures, videos, and other digital files — these efficiency gains bring a particularly strong sense of relief.
More broadly, AI is poised to improve productivity and efficiency across the visual media workflow, for marketers, creatives and developers alike. That’s because delivering quality, visual experiences takes a lot more work than just uploading new images and videos; it requires a staggering amount of behind-the-scenes effort to optimize every asset for both a high-quality, consistent user experience and great site performance across multiple devices, browsers, and viewing formats.
Let’s take a closer look at some of the innovations making it easier to create the dynamic and optimized user experiences that drive revenue growth.
Among all the applications the AI revolution has surfaced, perhaps the biggest is its ability to identify and automate repetitive, manual processes. The tedious, intricate, and time-consuming tasks that were considered “productivity” in the past are now being handled by AI and machine learning to great effect.
One great example comes from Neiman Marcus, one of the most well-recognized luxury retailers in the United States. As part of its digital experience transformation strategy, they deployed AI-powered image and video editing and optimization capabilities that automatically select the optimal format, size, and quality of each asset. This ensures customers view every image and video at the highest possible resolution while ensuring pages load fast and teams can get products to market faster. Their designers no longer spend their time on manual tasks, pages load 3x faster, and time-to-site for new assets has been cut in half.
Similarly, live-entertainment discovery platform Fever turned to AI to help them ensure cross-functional alignment and consistency as it navigated its global expansion. By delegating the routine but critical tasks of analyzing and tagging around 10,000 images and videos per month to AI, they were able to instantly put the days of losing assets in the depths of Google Drive behind them, while saving considerable time and resources at the same time.
The way Minted uses automation and AI is powerful, and there are thousands of companies finding similar efficiencies with this technology. But there’s no time to rest for innovative brands looking for a new edge.
Generative AI is the most promising development for those committed to working smarter, not harder. The pace of innovation in this area is astounding, but there are a few visual media use cases that promise to have the most immediate impact on internal efficiency, consumer engagement, and converting sales:
- Generative Fill. Empowers users to intelligently resize an image, transform it from vertical to horizontal and replace backgrounds without any manual effort.
- Generative Recolor. Eliminates the need to manually retouch photos for color adjustments by manipulating colors in images at scale.
- Generative Remove. Users can remove unwanted elements from images and automatically add a matching, branded background.
- Generative Replace. Allows users to easily detect, change, and replace unwanted elements via natural-language prompts.
- Generative Restore. Revitalizes images that have become degraded through repeated processing and compression, in addition to enhancing old images by improving sharpness and reducing noise.
- AI-Powered Image Captioning. Intelligently creates image captions for galleries, user-generated content, and product descriptions at scale, resulting in better SEO and accessibility.
While many people associate “generative” AI with from-scratch asset creation, issues with brand consistency, copyrights, and more mean it might not be quite ready for business primetime. On the other hand, developers can use generative AI to turn any base image into a perfect, customer-ready asset in an instant. Look for this technology to catch on quickly among the brands committed to delivering hyper-engaging digital experiences at the scale of modern commerce.
Prioritizing innovation while maintaining efficiency is attainable. By leveraging AI and automation, pursuing generative AI use cases that make the biggest impact, and fostering collaboration between developers and marketers, new opportunities for growth are guaranteed to present themselves. It’s crucial to embrace these technologies and tactics to stay ahead of industry trends, and build an agile organization that creates delightful, and profitable, customer experiences.