The No-Hype AI Report

You’ve heard the hype. You know the truth: AI has real creative potential, but it takes work and human expertise to be effective. It’s not as simple as clicking a button.

That’s why while 96% of creative leaders know AI will speed creative production, only two percent of in-house teams have cracked the code on total integration.

The rest? Stuck in the in-between: High hopes, low bandwidth, unclear next steps.

We’re here to help. Since launching Superside’s AI-powered creative services in 2023, we’ve learned a thing or two. Today, we have a fully trained, global creative team, a growing set of AI-enhanced workflows and a proven track record of efficiencies:

• 95%+ of creatives trained on the latest AI tools
• 5,000+ AI-powered projects completed for many of the world’s top brands
• 45+ creative workflows enhanced by AI
• 40% reduction in design time on average when using AI
• $4.5 million in creative costs saved for our customers in two years
  

But this isn’t about us, it’s about you.

This report unpacks what we’ve learned firsthand—working alongside hundreds of enterprise creative teams—so you can turn those insights into impact for your team, your creative workflows and your brand.

This isn’t theory. It’s what actually works with the data to support it. Ready to see how AI fits into the creative process, driving efficiency, innovation and ROI?

When you’re running multiple campaigns across dozens of channels around the world, visual requests stack up fast.

Before GenAI (yes, there was a before time), brands had limited choices for visuals: Go stock or go custom with all the overhead a photoshoot or complex illustration project entails. Now, AI image generation gives brands another, faster, more cost-effective option to create visuals for ads, websites, internal comms, product launches and more.

When a brand uses AI image generation to create assets there are two core approaches, each suited to different stages of production and levels of scale:

• Standard image generation. Crafting visuals in batches by prompting generative AI image tools is fast, flexible and ideal for one-off campaigns or testing new visual directions.
• Custom AI image models. Training a model on a brand’s imagery to generate consistent, high-quality visuals is ideal for teams looking to scale production.

Based on in-house data from 5000+ AI-powered projects, Superside has found both approaches offer tangible, time-saving benefits:

Standard image generation efficiency gains

*Efficiency gains based on a comparison to traditional approaches without AI tools.

Custom AI image model efficiency gains

So, based on this data from 5000+ projects, how can teams decide what kind of projects are well-suited to image generation? When is batch creation appropriate? And when should you shift to a custom AI image model to scale?

Let’s take a look at some real-life examples that demonstrate both approaches.

Sailun Tire Americas: From single-use to scale

Not that long ago, stock and brand photography were Sailun Tire Americas’ go-to. Following a traditional design workflow, creatives would take those images and add the company’s products as needed.

But Sailun Tire Americas wanted to elevate their photography and make it more distinctive. Dare we say, make it “pop.”

During a branding workshop, they raised this desire with their Superside team who were quick to mention the potential of AI. Superside explained how they often use AI tools to help brands generate a greater variety of consistent, high-quality images faster and more cost-effectively.

But talk is one thing. Sailun Tire Americas’ brand team needed to see what this would look like in practice to really grasp the possibilities. So, Superside developed a concept board showing how AI could evolve their brand photography, demonstrating how to prompt for product type and environment, complete with examples of raw and post-produced output. The brand team was so impressed, they approved the use of AI for image generation going forward.

Starting with the benefits of batch creation

This was the start of Sailun Tire Americas’ AI journey.

As a trial run, Superside mocked up a first project with stock imagery versus AI imagery. The brand team loved the AI imagery, leading to a complete shift towards using this technology.

When you’re trialing AI, have a single use case for the assets, or you’re building out a dataset for a custom model, producing individual collections of images makes perfect sense.

Though they may not have realized it at the time, Sailun Tire Americas was both validating AI as an approach and creating the foundations for their future Custom AI Image Model—all while saving countless design hours.

Scaling with a custom AI image model

Batch creation is a good place to start. But it’s not ideal for scale.

When you generate image libraries on a case-by-case basis, AI tools don’t actually learn your brand. That means, each time you produce a new library, you need to retrain the tool on the nuances of your brand aesthetics, making iteration and consistency a challenge. The solution? You guessed it:

Custom AI image models—essentially a specialized bundle of code trained on a dataset of your imagery—deliver on-brand visuals, every time.

Now, the key to creating a custom image model is a high-quality dataset: A library of refined, perfectly on-brand visuals. Given their shift towards using AI image generation for all projects, Sailun Tire Americas had just that. So, when Superside’s AI team reached out looking for custom image model candidates, their name rose to the top of the pile.

Using the bank of fully refined, representative images the company had built up, Superside’s AI team trained a custom model for the brand, testing and tweaking until the outputs were just right. But the final deliverable wasn’t just a bundle of code—it was a custom Figma plug-in that generates on-brand images within the platform, integrating right into their creative workflows.

On average, this speeds up image creation 10x, translating to 75% less time and 85% reduced cost per image. In addition to efficiency, the consistency these models offer make them ideal for producing large volumes of quality, on-brand creative. In other words, Sailun Tire Americas is all set for scale.

Beyond the numbers, custom models give creative teams more time to explore and pour energy into high-impact projects. And of course, they can fuel these projects. A great example of end usage, Sailun Tire Americas incorporated images generated by its custom model into a recent product sizzle reel.

Given these benefits, custom AI image models are catching on quick. Here are two more examples of brands tapping into the power of image models to scale high-quality creative.

Maven Clinic: Bringing life to life

Maven Clinic was rebranding—shifting towards warm photography showing candid, family moments. With multi-page booklets, conference posters, internal documents, reports and more to design, Maven Clinic had a large need for high-quality images.

Going the traditional photoshoot route would’ve been time-consuming and expensive. Not to mention, once an image bank gets stale, you have to start all over again. So, during a creative workshop, Superside pitched the idea of developing a custom AI image model for them instead.

• Step one: Put together a high-quality data set.
• Step two: Train the model.
• Step three: Deliver the Figma plugin and instruct Maven’s team on its use.

Today, Maven Clinic uses their custom AI image model extensively. Decks, marketing booklets, social content, you name it. And those dense, 100-page, text-based booklets? They look phenomenal laid out with custom imagery.

Now, Maven Clinic is still considering doing a traditional photoshoot to further define their brand style. But their custom model has provided a bridge, filling their creative needs until they have the time and resources to invest in additional photography.

Sisense: AI-powered from front to back

As an AI-powered platform, Sisense was always enthusiastic about incorporating this tech into creative workflows. This made it an easy decision for Superside to use AI to support their brand refresh and website update, generating on-brand, photography-style imagery, quickly and efficiently.

This initial project served as the foundation for Sisense’s Custom AI Image Model. With upwards of 60 AI-generated images and photography guidelines developed, their Superside team had everything they needed to train a model—and once again, Sisense was eager to give it a try.

Their enthusiasm only grew when they got their custom Figma plug-in. With very minimal input, they’re now able to generate assets ready for immediate use. They shared “even the hands look good,” answering a common concern for brands: “Will this look too ‘AI-y?’”

Now, a weight has been lifted from Sisense’s creative team’s shoulders. They don’t have to worry about sourcing free images with all the time, consistency and post-production challenges that entails. They prompt in Figma and get ready to ship assets instead.

Picture this: The power of AI image generation

These stories from Sailun Tire Americas, Maven Clinic and Sisense show a clear pattern: When a brand has a strong vision and a large-scale use case, custom AI image models are invaluable. They also show the value of starting with batch creation to refine brand imagery and develop a dataset.

To recap, both approaches save time and costs:

• Batch producing image libraries and illustrations is 50-90% faster with AI.
• Creating images is 10x faster with a custom AI image model, cutting time by 75% and costs by 85% per image.

You’ve got less than two minutes to get your brand message across—go!

Your best go-to? Short-form video. But traditional turnaround times are anything but short and production costs can sink great ideas faster than your will to pivot yet again.

Enter image generation’s complicated sibling, video. From pre- to post-production, integrating AI into video workflows can help teams move faster, while getting more creative and keeping big ideas off the cutting room floor.

When brands use AI for video production, here’s where they can find efficiencies:

1. In pre-production: LLMs speed scriptwriting while image generation accelerates storyboarding.
2. In production: creating video clips, animations and still imagery can all be done with generative AI.
3. In post-production: generating voiceovers saves time and increases flexibility, while adding motion and editing footage go faster with AI tools.

In fact, Superside has seen a reduction in video production time of 40-60% when working with AI.

Video production efficiency gains

*Efficiency gains based on a comparison to traditional approaches without AI tools.

So, what does this look like in practice? Where does AI video generation excel? And what’s possible right now?

Let’s take a look at a few real-life stories that demonstrate how AI can amplify video production.

Johnson Controls: Where HVAC meets imagination

How do you make an ad for HVAC monitoring feel fresh, creative and exciting?

For Johnson Controls, the answer was AI. A leader in smart building systems and technology, the company was introducing an AI tool to help monitor and detect HVAC issues, and they wanted a 30-second video to promote this product on LinkedIn Connected TV (CTV).

The early concept: A stock image of a man, sitting at a desk, monitoring a building’s HVAC systems via his laptop.

The ask: Bring this to life—in the most compelling way possible.

Knowing Johnson Controls wanted to highlight their use of AI, leveraging AI for the creative was a natural leap. So, their Superside team explored two different AI-powered approaches for the character soon to be known as “Bob”, a photorealistic approach and a claymation style.

Embracing a claymation style gave Superside’s creatives more storytelling freedom in the way they assembled ideas, built scenes and created visual worlds. Instead of as captured on film, they leaned into as captured by imagination—an approach Johnson Controls was fully onboard with, given their desire for innovation and their tight timelines.

Even with experimentation, Johnson Controls had their completed video in two and a half weeks rather than two and a half months.

Even with experimentation, Johnson Controls had their completed video in two and a half weeks rather than two and a half months—85% faster than a traditional, shoot-based ad. These time and resource efficiencies translated to $47,000 in saved design costs.

But the even bigger picture is what came next. What started as one project evolved into a distinct brand universe, a full cast of animated characters and a repeatable, scalable video workflow for bringing Bob and the rest of this visual “clayground” to life. 

Creating a dynamic visual universe and scalable workflow

Bob’s debut was a hit. Excited to build on this success, Johnson Controls requested more short-form video ads. Over the next few months, Superside developed several new claymation characters and videos, including a clip where Rachel The News Reporter takes flight in an ode to their 1980s campaign that introduced a hot air balloon as a brand icon. (If you watch carefully, you’ll also spot a cameo from Bob.)

Each video gave Superside the opportunity to further scale quality and efficiency, learning exactly when and where to use AI.

Here’s a breakdown of those efficiencies:

• Leveraging a custom AI character model 10X’d the speed of character generation, while ensuring consistency across visual universes.
• Combined with AI-powered motion design, this accelerated work by up to 70% depending on complexity and creative freedom.
• In the videos, AI voiceovers gave each character a personalized way of speaking, while speeding up work by up to 60%.
• For this project, Superside also developed a workflow to automate lip syncing, skipping time-consuming keyframing and making everything feel more natural.
• Finally, in post-production, AI saved up to 40% of design time, automatically detecting optimal cuts and transitions.

But the real story here runs deeper than just efficiency or scalability—it shows how AI can help brands think outside the traditional video shoot, opening doors to greater creativity and untapped formats. The next two stories drive this point home.

Sawgrass Technologies: High-tech meets high-impact

Sawgrass Technologies has a highly technical product: Sublimation printing technology used to customize mugs, t-shirts and other promotional materials. And the more technical things get, the more video shines.

To showcase the durability of their products in a memorable way, they wanted to demonstrate how they can withstand exposure to water, intense light and impact through video. But to accomplish this through traditional means—by investing in live footage or complex 3D modeling—would’ve blown the budget and the timeline.

Thankfully, there was another option. To fulfill the brief, their Superside team suggested using AI for motion design. Despite initial skepticism, Sawgrass Technologies was thrilled when the first draft came through, impressed by the level of realism achieved.

In this instance, delivering a high-quality product video within the desired timeline and budget simply wouldn’t have been possible without AI. But beyond making this project viable and slashing production time by 20-30%, AI opened the door to greater creative exploration. The end result: High-impact visual storytelling.

Mojave Color: Discovering what’s possible

When your product is all about vibrancy and accuracy, your creative needs to look the part.

Mojave Color, a leader in e-commerce photography, needed a striking teaser video that conveyed the true value of their product: Confidence in color, leading to consumer trust and loyalty. As an innovative brand, they were open to AI being incorporated into the creative process from day one.

With this green light, their Superside team was able to expedite the process of crafting a teaser video from end to end, while creating a visually striking narrative. Think shifting close-ups—a rose unfurling, a gem rotating, a lens turning—paired with concise messaging. Better still, see for yourself.

From concept to scripting, motion to post-production, Superside delivered this video in just one month, achieving an 84% faster turnaround time than possible without AI.

By blending AI-generated visuals with stock footage and dynamic motion design, the team not only saved Mojave Color $8,560 in production costs but delivered a stunning video that sparked engagement.

Cut to the future: The power of AI video workflows

Johnson Controls, Sawgrass Technologies and Mojave Color didn’t just make their videos faster with AI—they made them differently. It goes to show with the right tools and workflows, AI expands creativity. And when brands aren’t bound by budget, timelines or traditional production models, imagination gets the final say.

To recap, AI can increase efficiency at every stage of video production:

• Using AI for voiceovers and storyboarding can reduce design hours by 60%.
• Scriptwriting goes 40% faster when AI is part of the process.
• For actual motion design, video and photo production, AI tools accelerate the creative process by 40%.
• Combined with the power of a custom AI model—whether it’s a character, photography, illustration, object or general model—these efficiency gains can be even further amplified.

Do you see the potential yet?

When tight timelines and budgets compete with the need to experiment, go big and get more creative to garner any kind of attention, AI gives creative teams an edge: A faster, more scalable way of not just getting the work done, but elevating it.

And that edge only gets sharper the more you’re able to integrate AI into the creative process. In fact, the greatest gains come from end-to-end integration—all the benefits we’ve seen so far get compounded when AI is incorporated from step one to launch.

What does end-to-end integration look like?

Let’s say a SaaS company needs a high volume of motion-based ads for a product launch, and they need them fast. Here’s what their creative workflow might look like when powered by AI from start to finish, including where Superside has seen additional efficiency gains:

Step 1: Strategy

The first step? Strategy, of course. An expert research assistant, AI can help translate information into meaningful insights, speeding up this stage by 40-50%.

By feeding a brief into a tool like ChatGPT, incorporating inputs like audience insights, company objectives and brand guidelines, creatives can accelerate and expand ideation—all while ensuring concepts align with strategic goals.

Better still, they can create a custom GPT trained on these brand inputs to assist throughout the project, ensuring copywriting and quick iterations are on point.

Step 2: First draft

Building on this strategic information, the next step is first drafts.

Again, an AI tool like ChatGPT can accelerate copywriting—from ads to scripting and storyboarding—especially in conjunction with a custom GPT, while an image generation tool like Krea can speed the creation of moodboards and mockups, helping creative teams get to first drafts 50% faster.

Importantly, this speed and ease also allows teams to get aligned on a direction without expending too many resources.

Step 3: Creative execution

If this were a one-off campaign, creatives could generate a batch of visuals for use in the ads 50-90% faster, depending on the style.

On the other hand, if the company had an ongoing need for imagery and a dataset of high-quality, on-brand visuals to reference, creatives could invest in developing a custom AI image model, accelerating the creation of individual images by 75%.

Step 4: Post production

In post-production, designers refine the visuals.

This is where AI features like generative fill can help create a suite of assets with more flexibility, allowing humans to focus on fine-tuning imagery until it meets brand and brief requirements instead of manual photoshopping or tweaking in other platforms.

Step 5: Scale

But wait, this SaaS company wanted motion ads.

Usually, this would involve taking the static ad assets and applying traditional motion design, which can be quite time-consuming. With AI tools like Krea and Runway, creatives can add movement to static assets 40% faster—and improve performance once the ads hit the market, leading to tangible campaign gains as well.

Step 6: Templatize

To further enable scale, these ads could be templatized.

By building templates using modular components, the creative team could make elements like the image, copy and CTA fully customizable.

Then, by linking this structure to a workflow that uses a CSV file with all the content variations, they could turn data into designs and generate multiple ad variations in a matter of minutes.

From spark to scale: AI within creative workflows

This is just one example—based on real experience—of how AI can enable, expedite and elevate an entire creative workflow. From briefing to concepting, production to scale, AI tools don’t just make the creative process faster or more cost-effective; they make bigger, bolder ideas more attainable than ever before.

With AI woven through every stage, creative teams can spend less time wrestling with resource limitations and more time making the kind of work that turns heads, moves markets and redefines what’s possible.

So, ready to get started?

We know, AI won’t magically make your creative pipeline disappear.

It takes work, expertise and buy-in to integrate AI into creative teams and processes before you can see the benefits. We hope this report will help you get the buy-in you need—because we believe AI is the technology that will finally help creative teams stop scrambling and start thriving.

The work and the expertise? There’s no magic wand, but there is always a helping hand.

A true creative partner, Superside can help lighten your workload while actioning opportunities for AI integration and passing along our expertise.

According to a Forrester Total Economic Impact™ study, Superside already delivers a 94% ROI over three years without factoring in AI, which translates to $2.01 million in benefits. With AI in the mix, we far surpassed that in just two years with $4.5 million in savings across 5000+ projects since 2023.

The growing impact of AI-powered creative services

Your creative team’s creative team™

Beyond the numbers, the value of a creative partnership with Superside can be seen across the stories we shared in this report: Greater scalability, flexibility and creativity. But perhaps most importantly, we can help you step into this new era of creative AI with clarity, confidence and vision.

And hey, we’re built to be your creative team’s creative team—so at the end of the day, you get the glory, and we’ll take the to-do list.

Looking for your shortcut to no-hype AI?

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