MarTech360 Interview with Mary Gabrielyan, Chief Strategy Officer at AI Digital

C-suite leaders often expect immediate ROI after onboarding AI tools—but AI isn’t magic, it’s capability. It requires a clear strategy, operational readiness, and strong cross-functional buy-in. Otherwise, you end up with automation that no one uses or trusts. Or even worse, automation that operates with flaws and mistakes.

Mary, can you tell us about your professional background and your current role at AI Digital. Also, tell us how AI Digital differentiates itself from other companies in the same space?

I’m currently the Chief Strategy Officer at AI Digital, where I oversee our strategy and planning, as well as marketing teams. My focus is on driving scaled, AI-powered media planning solutions and aligning our product innovation and media strategies with evolving client needs. Over the past two years at AI Digital, I’ve also served as Head of Strategy & Planning and Media Strategy Architect, leading foundational work that helped us scale our planning infrastructure and deepen our programmatic capabilities.

Previously, I held leadership roles across strategy and marketing, most recently as CMO at Virto commerce and previously at Publicis Groupe, VEON, and other companies. My experience spans both agency and client sides, combining deep expertise in media strategy, digital transformation, and building high-performing global teams. What sets AI Digital apart is our Human Intelligence powered by AI. We’ve combined the unique expertise of over 250 media experts with advanced AI capabilities and stack, giving us an unmatched edge in the industry.

We’re proud to be a leader in AI innovation, particularly with our proprietary AI-powered platform, Elevate, which revolutionizes how we plan, optimize, and activate media. But beyond the tech, what truly differentiates us is our tech-agnostic approach. In today’s fragmented media landscape, where walled gardens continue to fragment consumer attention, being platform-neutral enables us to deliver best-in-class strategies, tools, and pricing tailored to each client’s specific needs.

AI Digital emphasizes ‘AI with Purpose.’ How do you ensure that emerging AI solutions are not only innovative but also ethically grounded and business-aligned?

On one hand, all the businesses are feeling the pressure of operationalizing generative AI as quickly as possible. On the other hand almost all businesses, including AI Digital, are facing the increasingly complex and ever-changing regulatory landscape and ethical concerns when it comes to AI and AI models that we use daily.

I assume most of the modern-day users have heard about copywriting infringements, AI chatbots’ toxic behaviors like bullying or gaslighting, and probably most of us cannot forget the bizarre answers that Microsoft’s CoPilot was giving while being on the SupremacyAGI prompt. First and foremost, what we have to remember is that AI is not a race. It’s a journey, and we want to go through this journey with as much safety as possible.

“AI with Purpose” is not only a slogan at AI Digital. It is a deeply-rooted framework that allows us to innovate with purpose and make sure to evaluate the trustworthiness of the models we use. We not only pay attention to these common risks but also pay attention to the environmental impact of AI and ensure to opt for less resource-intensive models wherever we can.

Most importantly, our AI automations and tools aren’t siloed. They are infused with the expertise of 200+ media professionals. AI explainability is a cornerstone of responsible AI. At AI Digital, we see it as essential for both trust and business utility. In practice, explainability means that our AI systems, particularly those within our Elevate platform, don’t operate as black boxes. For every recommendation, bid strategy, or optimization decision, we strive to provide a clear, human-readable rationale behind the output. We fact-check manually to prevent any biases. That human intelligence layer ensures we’re not just chasing the next algorithm, we’re solving the right problems, with impact and empathy.

In short, we don’t just do AI innovation because we can. We build AI tools and AI-powered platform because it matters to our clients, to their audiences, and the future of responsible media.

Also Read: MarTech360 Interview with Adi Krysler, VP of Marketing at Oktopost

As Chief Strategy Officer at AI Digital, what does your strategic vision look like for scaling AI adoption across complex enterprise environments?

At AI Digital, we believe scaling AI doesn’t start with tools, it starts with the “why.” Successfully scaling AI across an enterprise doesn’t start with technology, it starts with clarity of purpose. The most effective organizations approach AI adoption as a strategic capability, not just a toolset.

Tie each use case to a real business challenge or opportunity. From there, launch with a minimum viable product (MVP), a focused pilot that delivers measurable value quickly. This builds trust, validates impact, and gives you internal momentum.

One of the most powerful accelerators is identifying and empowering AI champions across the organization. These are early adopters who can show, not just tell, how AI enhances performance. Their example helps shift culture from skepticism to curiosity.

Equally important is investing in education and enablement. People need to understand not only how AI works, but how it will help them work smarter. That means ongoing training, clear communication, and opportunities for teams to experiment without fear.

Lastly, create space for intrapreneurship. Fund or sponsor great AI ideas. Encourage cross-functional teams to innovate with AI, reward successful adoption, and scale what works. When people feel ownership over AI success, it becomes embedded in the way the organization operates, not just another tech rollout.

In short: align on purpose, start small and with intention, prove impact, empower advocates, and build from within.

The pace of AI development is exponential. How do you balance experimentation with long-term strategic planning in such a dynamic space?

You need both the zoomed-in and zoomed-out view. On one hand, we stay agile and experimental. We run internal sprints, rapid prototype new features, and constantly test GenAI across creative and operational workflows. But we also operate from a clear strategic compass.

For us, that means filtering every AI opportunity through three lenses:

1. Does it solve a real client problem?
2. Can it scale sustainably?
3. Does it deepen our competitive advantage or client intimacy?

When something passes that test, it moves into our long-term roadmap. Everything else stays in

the sandbox until it proves its value. That structure helps us avoid getting caught up in hype and
keeps us focused on high-impact innovation.

From your perspective, what industries are currently most underleveraged when it comes to AI, and what opportunities do you see for disruption?

Despite all the headlines, retail and CPG brands remain among the most underleveraged when it comes to applying AI for media efficiency and cross-platform optimization. According to McKinsey, while retail media is growing rapidly, with global revenue expected to exceed $100B in the next few years, many brands are still struggling to unify fragmented data across DSPs, retailers, and internal analytics systems.

AI has the potential to be the connective tissue that bridges these silos: enabling real-time bidding intelligence, audience deduplication, creative optimization, and smarter attribution. Yet, most retail media strategies still rely on manual processes or black-box solutions that limit transparency and agility. There’s significant opportunity here to build AI systems that are custom-fit to each brand’s ecosystem, not one-size-fits-all.

Another high-potential space is healthcare marketing, particularly for OTC and DTC brands. While this category faces more stringent privacy regulations, it also sits on an enormous amount of intent-rich, contextual, and behavioral data. With the phaseout of third-party cookies and increasing regulatory scrutiny, AI-powered solutions-especially contextual intelligence, NLP-based creative testing, and zero-party data modeling—can help brands responsibly personalize engagement without crossing compliance lines.

In both categories, the opportunity isn’t just about automation, it’s about making AI strategically accountable, explainable, and privacy-forward. The brands that get this right won’t just run better campaigns, they’ll build more intelligent marketing organizations.

What are the biggest misconceptions C-suite leaders still have about integrating AI into their digital transformation journeys?

The biggest one? That AI is a plug-and-play solution.

C-suite leaders often expect immediate ROI after onboarding AI tools-but AI isn’t magic, it’s capability. It requires a clear strategy, operational readiness, and strong cross-functional buy-in. Otherwise, you end up with automation that no one uses or trusts. Or even worse, automation that operates with flaws and mistakes.

Another misconception is underestimating the human side of AI integration. Successful AI transformation isn’t just about choosing the right model—it’s about preparing your teams, rethinking roles, and creating a culture of experimentation without fear. When leaders overlook that, AI initiatives stall.

With GenAI dominating boardroom discussions, what advice would you give to business leaders looking to cut through the hype and create real ROI?

Start small, but start right. Choose one high-impact, repeatable use case where GenAI can save time or improve output. That could be generating content briefs, summarizing performance reports, or automating parts of campaign setup.

Then measure everything. Don’t fall for vanity metrics, look at how much time you saved, how much closer you got to conversion, or how the AI-generated insight improved your strategic planning. Run tests.

And finally: Don’t chase GenAI just because your competitors are. Chase it because you’ve identified a clear opportunity where human + machine collaboration can make your team faster, smarter, and more effective.

Is there anything that you’re currently reading, or any favorite books, that you would recommend?

Yes! I love reading and I hope that’s something that is never “automated” pr anyhow taken away from us. I always recommend “The 15 Commitments of Conscious Leadership” to fellow leaders, especially relevant for anyone scaling a company in high-stakes, fast-evolving environments. Another common recommendation of mine is “The Hard Thing About Hard Things” by Horowitz. It is an essential reading for any leader navigating ambiguity.

As for the AI-related books, I am currently reading the “Empire of AI” by journalist Karen Hoe. Very interesting and highly recommended if you’d like to understand the AI industry better.

Thanks Mary!