How AI is Making it Easier for Marketers to Create Videos

It’s easier to create high-quality video content more efficiently, all with the help of Adobe Sensei.

There’s no question that artificial intelligence (AI) is contributing to the evolution of video content. Video is arguably the go-to platform that the vast majority of businesses use for content marketing — and it’s growth will continue to skyrocket.

That said, this powerhouse content type isn’t without its challenges. For starters, producing quality video content requires a significant investment in time, talent, and costs of video production — costs that can easily eclipse other content development processes and platforms.

Second, with 60 percent of consumers considering brand-generated content as pointless clutter, content creators are under tremendous pressure to deliver engaging and high-conversion customer experiences to an audience who may or may not be so receptive.

Fortunately, advances in AI and machine learning are empowering marketing teams to streamline and accelerate video production workflows and create more targeted content, in less time and with fewer resources. Here are some of the ways Adobe’s AI-infused video creation features are driving success for marketers:

#1. Eliminating wasted time with intelligent search

For video creators, the sheer volume of footage collected can become unwieldy. With gigabytes of footage, wading through and watching video files to find the perfect shot can take hours, if not days or even weeks. To limit this inconvenience, many content creators sacrifice hours of time manually tagging videos (with attributes that describe the footage) — time that could be spent on content development.

AI can help. At Adobe, our Video Auto Tag Adobe Sensei service automatically tags attributes for each segment of each video — think colors, faces, locations, actions, products, or corporate logos. AI provides a searchable taxonomy for finding not just the right video file, but the right cut of the video, in a fraction of the time.

Video Smart Tags for user generated content.

The Video Auto Tag process allows for natural language search of video files, even when multiple conditions are present. For example, if you searched for a video containing “two dogs playing in the water at the lake,” AI-powered tools would retrieve videos meeting all five of those conditions, providing an unprecedented level of specificity for videographers and editors on tight timelines.

#2. Predicting greater video memorability

If you’re creating marketing videos, you’re likely looking at insights from past videos to try to predict future performance — or, possibly, you go with your gut to come up with a content strategy that will get you the most views.

However, both approaches can be frustrating and time consuming, while yielding unpredictable results. This, again, is a challenge that Adobe Sensei can help with — specifically, the technology that we “sneaked” at Adobe Summit last March: #VideoAdAI

#VideoAdAI is an exploratory technology that uses a deep neural network to automatically generate metadata, such as categories and tags for video ads. To do this, AI “reads” the ad’s video, audio, or other available information and identifies demographic segments and subjects relevant to a given platform. This makes it easy to line up the right video ad with the right ad platform. #VideoAdAI then employs a second deep neural network to assign a “watchability” score to the ad.

Similarly, the AI-driven Auto Curate feature powered by Adobe Sensei in Premiere Elements can view an entire video catalog, identify the best footage, and surface it for use in a project, saving videographers and editors the hassle of browsing through endless file folders of footage.

#3. Streamlining the post-production process

The traditional video production process is filled with repetitive tasks that can be easily automated with AI. For example, many content creators develop a series of different thumbnails, flash cards, and summaries to match the varying requirements for different video platforms like Facebook or Instagram.

With #ProjectSmoothOperator, another experimental technology that we previewed at Adobe MAX, marketers and editors can automate platform-specific video optimization. This eliminates the need to manually optimize content for different social media platforms, mobile, tablet, and other devices.

What’s more, using Adobe Sensei technology, Project Smooth Operator examines the video content to generate a heat map that syncs with each subject, and its action, in frames. From here, a global camera path is determined, automatically shifting the frames to capture the core action of each shot.

AI can also help with color correction, another time-consuming and costly part of the video editing process. Adobe Premiere’s AI-powered Color Match feature applies color correction settings from one shot to all the others in a scene, taking special care to identify faces and match skin tones. Editors, though, can still manually adjust color correction settings using the color wheels to ensure the right color every time.

#4. Seamlessly integrating video and audio

Few parts of the traditional post-production process are as tedious as syncing audio with video. Whether it’s manually adjusting sound levels, tweaking the timing of dialogue to match actors’ mouths, or trying to balance musical and sound effects, the process can be extremely time consuming and resource-heavy. Here, also, Adobe Sensei is improving the process, while simultaneously improving video quality.