The AI Advertising Podcast: S1

Episode 12

AI and Culture: What It Really Takes to Build an AI-First Company

About This Episode

Aug 13, 2025

What does it really mean to be an AI-first company? And how do you bring your team and your culture along for the ride?

In this episode, we have three industry leaders who are building AI adoption from the inside out:

Ashwin Navin | Co-founder & CEO, Samba TV

Vitaly Pecherskiy | CEO, StackAdapt

Ryan Nelsen | CMO, StackAdapt

00:00

Transcript

Diego Pineda (00:00:00)

In a recent survey published by StackAdapt, 39% of advertising agencies said AI is now a core part of their workflow, and those with deeper integration report significantly higher satisfaction with their tech stacks and stronger campaign performance overall. The survey results show that AI transforms more than just workflows—it transforms the people who use it, the teams who adopt it, and the leaders who champion it.

This episode unpacks how AI is reshaping company culture, from experimentation and leadership to hiring and performance. I sat down with Ashwin Navin, Co-founder and CEO of Samba TV; Vitaly Pecherskiy, StackAdapt’s Co-founder and CEO; and Ryan Nelsen, CMO of StackAdapt.

Each of them brings a unique perspective on how AI adoption intersects with company values, strategy, and people. Let’s hear what they have to say.

Podcast Intro (00:00:59)

Welcome to the AI Advertising Podcast, brought to you by StackAdapt. I’m your host, Diego Pineda. Get ready to dive into AI, Ads, and Aha moments.

Diego Pineda (00:01:13)

Creating a culture that embraces AI doesn’t start with software. It starts with leadership. Here’s Ryan Nelsen on how he’s building a marketing team that embraces innovation through AI.

Ryan Nelsen (00:01:24)

We try to create a culture of learning, a mindset of curiosity, and we hire for that as well. I want to make sure that we’re bringing in individuals who are naturally curious, naturally great learners, fast learners, and have a curiosity to be better at what they do. I think it’s fun. We’re doing something on Fridays, called AI coach that we just kind of named it that. And we’re bringing in external speakers, internal speakers. We’re having the team members talk about what they learned over the last couple weeks that has made them better at their job, what’s helped them make a bigger impact as a marketer. So, we’re starting to crowdsource some of this learning. We’re starting to bring in different sources and just trying to do our very best to take a little bit of time to pause and say, “Okay, what is truly making the biggest impact?” So, I’d encourage you all to do the same. Get with your teams. Talk about what you’re learning on this podcast or other podcasts. Talk about what new tool or download that you gathered the last couple of weeks that really changed your perception or paradigm of how you work. And then share that knowledge. And those that are sharing knowledge are going to be the ones that hold a lot of the future in terms of where we’re going.

Diego Pineda (00:02:36)

That openness to curiosity becomes even more critical when navigating uncharted territory. Ashwin Navin from Samba TV says embracing risk and experimentation is key.

Ashwin Navin (00:02:46)

For our business, there’s an intersection pretty much at every step of our product development process, in our go-to-market, in the way that our partners are interacting, engaging, integrating with us.

So it’s multifaceted for us. It’s sort of impacting everything we do. Every individual at Samba is empowered with tools. Every product manager, every salesperson, every engineer, has sort of an opportunity to imagine, reimagine their day-to-day lives, the work that they’re doing, and to be able to not only get support and assistance from the company, but also to be able to celebrate it and share it within the organization. So that’s sort of the internal view.

We noticed that the rate of evolution of tools and workflows was accelerating. And the only way that our people could keep pace, both managing and juggling their day-to-day, as well as being able to keep abreast of all the new tools was to actually have support.

And so we treated it like another support organization, just as we have IT and HR and a variety of tools available. We actually created an AI task force. We don’t, overstate what AI does. I think that the industry his a fault and is prone to hyperbole. For us, it’s just about like how can you do what you’re doing better, faster, with more time to devote to the more strategic and creative aspects of our job.

The tool proliferation is very, very significant, like rapid to the point where there’s a new flavor of something every day. The rate of change is so dramatic. It’s a tough call. We being AI optimists, erred on the side of adoption, proliferating new tools quickly to see what they could offer us. We did not jump on the brakes and say, okay, we gotta vet every single thing through some kind of process.

I think we’re now at a point now where there’s there are so many tools in our company that we’re in the process of um whittling down to the ones that we think have the most potential, the most resource behind them, the most IP protection, thinking about tools not from a pure consumer angle but also from an enterprise angle. Like that’s happening right now. And we’ve always had a strong sort of posture towards data privacy, data protection. So we’re vetting these tools to make sure they comply with our policies and procedures and making sure that they’re aligned before we put any of our sensitive data, user data or partner data. We’re not going to put any of that at risk.

Diego Pineda (00:05:11)

Culture can empower AI adoption, but systems make it operational. Leaders need to build workflows that support testing, learning, and improvement. Here’s Vitaly on how to approach implementation of AI inside your organization.

Vitaly Pecherskiy (00:05:26)

The way I think about it is that, like you cannot just have a blanket approach to saying, you have to use AI, it’s going to become part of, you know, your performance reviews and so forth. Because the truth is, every function is very unique. And it has to be treated with a fair amount of attention. Because if you’re just forcing people to use AI… it needs some thought put into it. You know, like proofreading grammar, to me, that’s not an AI case. Like if a team says, oh yeah, we use AI, you know, we do spell checking. To me, that’s not a tremendous value. It’s a distraction.

So I think it does require a thoughtful approach of implementation of AI. So for example, you know, you take a team, you need to first and foremost understand, how do you measure the output of that team? What constitutes a good output? And then can use of AI, first of all, increase the output and also not increase the error rate, for example. So defining exact, sort of a scorecard for how AI should be evaluated, I think is very important because if you give a blanket direction to use AI, without the right sort of framework, I think it can go sideways pretty quickly. So the way we’re thinking about it is just taking incremental steps and focusing on certain functions or certain key areas of the company, maybe with the largest team or the largest use cases, and try to solve for that.

Make sure that people have a very clear understanding of how AI is going to increase their productivity or output, be able to actually measure it. Without that, I think, you know, it’s just gonna be very soft in a way that people can articulate the value of AI.

Diego Pineda (00:07:17)

While many companies are using AI as an efficiency play—that means saving time and automating processes–there’s also the opportunity of using AI as an innovation catalyst.

Ashwin Navin (00:07:28)

Everything has an opportunity to be reimagined with an AI acceleration, an AI amplification. So I’ll give you a few examples. Often people, when they think of Samba, they think about the video analysis that we’ve done over the years. The fact that we monitor thousands of linear networks, hundreds of thousands of shows, millions of ads. We’re doing that in many countries now, 24/7. We wouldn’t be able to do that without AI. Imagine a human-only effort to do that.

Machine learning has been built into the company’s history from day one. What we’re able to do now, given the evolution in the models, is actually go deeper into the video and understand it in new ways that we didn’t have the ability to even three years ago or two years ago to be able to monitor millions of ad creatives and know what are the messages in market from every industry, every advertiser in multiple countries and languages. To be able to provide that insight back to any one stakeholder, whether that’s the media agencies that are trying to support those brands, the brands themselves were trying to differentiate themselves against their competitors and really understand where they stand in terms of share of voice and their level of investment and reach compared to the industry and their competitors.

These are all things that we can generate, in real time, with no um actual manual effort at this point because we’ve instrumented that monitoring infrastructure and extracted a lot of value and meaning from the video that’s out in the world right now.

Diego Pineda (00:08:58)

The real advantage of AI comes when teams move beyond just using it to thinking with it.

Ryan Nelsen (00:09:04)

I think the very best marketers, they know their audience better than anyone and they understand how their products and solutions add value to that specific use case. And so with AI, I’m very excited about the personalization, incredibly excited about the speed and the ability to speed up the creative process specifically, I think it’s a really powerful area, where we can then spend more time making decisions and having AI push us insights, data, results, and then spend more time connecting with humans and people to make decisions that are going to make the biggest impact possible.

So as a marketing leader, it’s fun. At StackAdapt, we market to marketers and so we understand, have empathy for what you’re going through. And ultimately, at the end of the day, you’re trying to build impact, you’re trying to drive conversions end-to-end in the funnel and a lot of times marketers take a lot of heat because leads is the end outcome of… we generated a leads but the end of the day leads in B2B company is just the beginning step. And we certainly want to get to MQLs and Sales Qualified Leads (SQLs) and beyond that into opportunities and then seeing visibility and using AI tools to be able to manage and watch the optimization and the conversion path through each area of the funnel is where I think we’re going in a bigger way. And I don’t think we’ve gotten there yet as most marketers. We’re getting sort of monthly reports or even bi-weekly or weekly reports on, hey this is what’s working or this is what worked three weeks ago. We need to get much faster much better at being proactive with AI insights to go drive daily and hourly decisions. I think that’s where the sweet spot is.

Diego Pineda (00:10:54)

That shift in mindset also separates leaders from laggards. Ashwin says your organization’s future depends on how willing you are to be fearless and take advantage of the opportunities AI offers.

Ashwin Navin (00:11:05)

I think we, as humans, as leaders, as managers, have to be optimistic. And our industry right now is in a state of fear, almost paralysis. We’ve been monitoring the sentiment among our organization towards AI. We’ve been monitoring the industry’s sentiment and feelings about AI. And there’s a lot of fear out there. And now is not the time for leaders to play the clickbait game of painting dark and ominous futures. Like we don’t have to be Pollyannish, we don’t have to be unrealistic, but at the same time, people don’t produce great work when they’re in fear. They aren’t gonna be their best selves. And every organization needs every human operating at their highest potential, as much as we possibly can inspire them to be their best selves.

So that, in my mind, is a sort of management necessity that, let’s just take some comfort in the fact that humanity has faced like sort of the ominous threat of technology putting us out of work for centuries. This is not a new thing. We’ve always had a fear of new. And if we think about it like the economic growth will present new opportunities, and humans have an amazing way of fulfilling those opportunities with their own ideas and solutions.

Diego Pineda (00:12:21)

With the rise of Generative AI and the promise of General Artificial Intelligence, there’s a new phrase making it into the mission of many tech companies today: Being an AI-first company. I asked Vitaly about his take on this trend.

Vitaly Pecherskiy (00:12:35)

There’s no doubt that AI will continue transforming and disrupting industries and businesses and functions. It already does. I think value in putting, going out and saying we are AI first is in part aspirational for so many companies. You need to in some ways, in order to for organizational transformation to happen, you need to have some kind of North Star for the organization to work towards.

So I would not necessarily look at companies that say AI-first and imagine that everything they do suddenly is AI, and suddenly they’ve gone through this transformation and they’re ahead of everybody else. I think for most organizations, it’s a bit of a North Star to try to move companies to think in a way of how businesses in the future will operate.

By that logic, I would sort of expect most companies to be AI-first companies at this point or in the near future. But it doesn’t mean that, you know, if you look under the hood, you know, they don’t have people and it’s all like artificial general intelligence doing everything. It’s just more of sort of guiding principle for how they want to continue evolving.

I could see the world in which, in the very near term, nobody’s going to say I’m an AI-first company because it will just be every company. Right? It’s, you know, just look back 10 years ago and everybody said, well, we’re cloud-based. Nobody says that. It’s sort of the assumption. So I think it’s going to be table stakes, if not now, in a very near term.

Again, AI is just a how. AI first doesn’t automatically mean it will create better value for the customer. It doesn’t automatically mean that. so So I think in the near term, a lot of that terminology will start fading towards what is that the company does that is valuable to the customer?

Diego Pineda (00:14:38)

Let’s pull together a few takeaways. First, culture sets the foundation for successful AI adoption. It’s a people issue before it’s a tech one. Second, leaders must model curiosity, experimentation, and transparency. Third, systems should support fast feedback, experimentation, and integration. Fourth, mindset matters more than the number of tools. Being AI-first means rethinking how your entire organization operates. And fifth, AI can speed up execution, but only if teams are empowered and aligned.

Podcast Outro (00:15:14)

Thanks for listening to this episode of The AI Advertising Podcast. This podcast is produced by StackAdapt. Visit us at stackadpat.com for more information about using AI in your advertising campaigns. If you liked what you heard, remember to subscribe, and we’ll see you next time.