There is an eye-watering amount of AI content released on a daily basis, and you’re probably getting numb to the deluge of postulations and grand suggestions on how AI will change the world. But there’s far less insight into how AI is actually being applied to advertising creative. I reached out to an old friend of mine, Alexei Chemenda, CEO of Poolday.ai — a company that’s actually using generative AI (GenAI) at scale — to understand a little about what’s working (and what’s not) in the industry.
This article builds on insights from our recent webinar “The Role of AI in Creative: The Current and Future State of How Companies Leverage AI for Marketing Creative.”
Thanks for joining us, Alexei. Today we’re diving into how AI is shaping creative in advertising, and you have a ton of experience here. Can you share a bit about yourself and what your company does for clients?
Poolday is an AI-enabled platform that allows advertisers to produce a high volume of videos and iterations in minutes, whether it’s AI user-generated content (UGC) or general videos for performance advertising. Our goal is to quickly and cheaply create videos for marketing to help companies scale their advertising creative.
One thing worth highlighting — you didn’t just come up with this idea, right? You actually built this based on need?
Yes, I run a mobile app studio, and as part of our user acquisition (UA) efforts, we were creating a high volume of social media ad videos with content creators to market our apps. This was a super important part of our growth strategy. Last year, when AI started making big strides in effectiveness, we began building and incorporating these tools into our processes. After seeing their impact, we built a self-service platform to help businesses all over the world.
AI is already proving its value by making advertising creative better, faster, and cheaper — especially for performance advertisers. While gaming companies are the most obvious adopters of this technology, what other performance-focused companies are exploring this space? And what results are they seeing?
Mobile gaming customers are at the forefront of adoption for most advertising, especially on mobile-dominant social media platforms. This is largely due to their ability to drive performance in a closed-loop system and scale at no incremental cost. So, it’s no surprise that many of our earliest and largest customers are gaming studios.
However, we’re seeing interest and traction from other leading-edge companies — what I’d call “next-gen” performance advertisers. These are companies well schooled in the performance buying practice and hungry for the performance gains from cheap, fast creative iteration.
Something that not every customer understands is that initial results may vary. But that’s by design. The purpose of using GenAI for creative purposes isn’t to press a button and instantly create a winning video. It’s about rapid iteration, constantly refining creative to find what performs best over time. Many advertisers already know creative is one of the most effective ways of increasing campaign performance; if you can produce better creative faster and at a lower cost, you can scale your campaign success in the same way.
If you were a marketing leader at one of these forward-thinking performance advertisers and looking to explore how GenAI can benefit your business, what key fundamentals would you consider? Or put simply — where would you start?
We see inbound interest from a wide range of people — everyone from C-level executives looking to build an AI strategy to video editors on large teams and founders of small companies. There’s no single “right” approach to AI within a company. What matters most is having a team that’s flexible, intellectually curious, and results-driven.
It’s also important to note that AI is not a magic bullet. If it were, everyone would already be using it successfully. It’s important to step back and look at AI as a significant shift in your processes. How can you integrate it to improve your existing workflows? Remember that any AI platform requires calibration to produce great outputs. If someone expects perfect outputs on day one with no effort, they’re setting themselves up for failure.
The companies seeing the most success on our platform are using AI to address bottlenecks, streamline iteration, and move faster.
In our webinar session, you mentioned the downsides of AI: While it can remove bottlenecks in traditionally impacted workflows like asset generation, it can completely overwhelm other parts of the business, such as asset management, testing, and legal approvals. For companies just starting this process, how should they identify and circumvent these challenges up front? Put another way, how do you avoid future issues?
We’re constantly finding new ways to break existing systems. It’s really not surprising: When creative has traditionally been the slowest-moving bottleneck within an organization, you stress test the entire system when you turn the bottleneck into the largest producer. A great example is simple asset management: A creative team may suddenly need to upload and test up to 100 times more videos than before. Do you have the budget, time, personpower, or tagging mechanisms to do this effectively?
The short answer is you need to figure out how to introduce this into your existing systems in a way that enhances them without breaking them.
I recently read an article arguing that AI, for all of its interest, skipped some steps in achieving product-market fit — suggesting that while exciting, we have yet to see a truly world-changing application. Since you started Poolday as a GenAI creative company, you obviously disagree. Why?
Our biggest challenge right now is keeping up with inbound demand. Last year, we produced over 100K video ads for a single major platform, and we’ve already surpassed that this year. We recently had a customer post about producing 15 videos for under $7 each in under an hour — four of which tested as winners. To some organizations, this may not be interesting. For others, it absolutely is game-changing.
One key to our success has been taking a more vertically integrated approach. If you try to use OpenAI as an out-of-the-box video production engine for your campaigns, you’ll run into major challenges and spend a ton of time just learning. Instead, we started building AI mechanisms into already-working campaign optimization workflows. While AI can seem difficult to integrate, we’ve found that when applied within well-bounded workflows and tuned tools, it delivers amazing work for our customers.
You projected that we’d see GenAI applied at scale to performance media in around 12 months, and that the future leaders should start learning about it today. If a marketing executive asked where to begin, what would you tell them?
I’ve seen enough success with advertisers to know this shift is inevitable, and forward-thinking leaders are already figuring out how it works. You could wait six months, but the companies investing in early learning now will have a massive advantage in accelerating and outpacing the competition. By 2026, I foresee every major brand having some type of AI interaction with consumers — allowing them to rapidly test formats and messages, adapt to new environments, and customize messaging. This is a major change, and those who start learning early will be best positioned to leverage AI at scale as it reshapes the industry.
Speaking of the future, I have a strong hypothesis that over the next decade, we’ll see a new wave of industry leaders — those who learn to harness AI, much like the rise of internet-driven direct-to-consumer (DTC) brands that mastered retargeting. What do you think will define the companies leading the AI race? Put another way, when we look back 10 years from now, what will be the obvious strengths of those who successfully leveraged AI?
We’re already seeing these traits emerge, even in the smallest ways. For example, we’ve seen many cases where a single word in a video can impact performance. With AI-generated content, these adjustments are faster, easier, and cheaper — allowing companies to iterate at unprecedented speed. And that’s the key: fast-acting companies.
Companies looking to quickly iterate and explore how to use AI to augment their workflows are seeing real, tangible results today and will undoubtedly continue to expand their use of AI. The winners of this new phase will be companies that invest in rapid iteration, leveraging AI to achieve true personalization for their customers.
Thank you, Alexei! How can people get in touch with you?
Thank you, Adam! You can find me on LinkedIn or get in touch at Poolday.ai.