Decoding AI’s Marketing Impact with Scott Brinker

AI is revolutionizing the marketing landscape. We’ve come a long way from its foundational applications in chatbots, predictive analysis and recommendation engines. Today, businesses can use AI coding assistants and next-generation no-code platforms to create custom applications perfectly aligned with specific operational and experiential needs. Leaders can use AI to enhance their marketing strategies, streamline operations and deliver personalized experiences. Marketers can use AI to create content and self-serve analytical insights.

But despite the dramatic evolution, AI adoption in marketing is still in the experimental and early production stages. This provides immense opportunity — and challenges — for marketing leaders. Marketing professionals should understand AI’s implications for strategy, leadership and operations in order to leverage AI effectively, and martech leaders must integrate these capabilities into their existing stacks to stay competitive. 

Florian Delval, Snowflake’s Product Marketing Lead, talked to Scott Brinker, Editor at chiefmartec.com, about how marketing leaders can capture this value and stay competitive while also navigating the challenges that come with the rapid evolution of AI and industry adoption. In our recent webinar “Decoding AI’s Org-Wide Marketing Impact,” Scott covers several uses and impacts of AI, from data strategy to technology stacks and creative productivity. 

Autonomous marketing workflows with AI

AI assistants such as ChatGPT, Gemini and Claude are significantly impacting marketing workflows and leading to more autonomous operations including content creation, data analysis and customer interaction. “It is amazing how much adoption those things have actually achieved in such a short period of time,” Scott says. “It is the vast majority of marketers saying ‘Yep, we use these assistants in our regular marketing.’”  

This automation speeds up the marketing process and allows teams to focus on strategic initiatives. For example, AI assistants generate initial drafts of marketing copy, summarize reports or segment customer data, freeing up marketers' time. 

However, a chart from the March 2025 “State of Martech” report distributing the approximate spread of marketers’ adoption of AI technology — ranging from the earliest innovators to laggards asking “What AI?” — shows a chasm between the large majority who are using AI assistants and the more advanced adopters and innovators using agentic workflows and AI agents. This points to a gap and opportunity for marketing leaders to move into more competitive positions by going beyond AI assistants and deploying agents and autonomous workflows. 

Unstructured data opportunities in marketing 

“To be honest, so much of the data that we were working with in marketing for years and years was a relatively narrow set of things that were well structured,” Scott says. 

Unstructured data in the marketing context, on the other hand, includes things such as email threads, chatbot transcripts and any text documents or even visual data that are not easily organized in a traditional database. “So much of that data just never really was in a form that marketers were able to harness or mine or leverage,” Scott says. With AI, this data presents significant opportunities for marketers to gain deeper insights, such as into customer sentiment, preferences and pain points. AI can also use this data to improve personalization, such as by tailoring messages, offers and experiences to individual customers for better engagement and satisfaction. And analyzing this data with AI can enhance customer service by identifying common problems or questions and leading to better support resources and more efficient issue resolution. “I think this is one of the vectors that marketers have to be much more creative,” Scott says. “It’s one of the things I’m most excited about.”

But capitalizing on these opportunities requires effective data strategies and integration with cloud data warehouses to ensure data quality, accessibility and AI-driven analysis.

Harnessing AI requires a robust data strategy

“We’ve been in the mode here now for easily the past five or eight years in marketing where we knew that developing stronger and stronger data capabilities was the key to so many unlocks,” Scott says. “And AI has multiplied that by an order of magnitude.”

Successful AI integration requires a robust data strategy, helping ensure data quality and compliance to maximize AI's potential. AI's effectiveness depends on the accuracy and reliability of the data it processes. A strong data architecture and proper data management also help ensure accessibility, enabling AI-driven analysis. This process needs rigorous auditing and upholding of data quality and compliance, which have always been challenges in martech. With AI raising the stakes, prioritizing the data layer is essential for martech leaders.

For more, watch the webinar to hear Scott describe the benefits of not just having a data warehouse but having it integrated with the martech stack and to see him discuss where insights can come from. Plus, find out how many respondents say they already have this integration and with what cloud service. 

All of this translates into many AI-optimized martech improvements, including in data strategy, cost models, team dynamics and practitioner empowerment. For marketing leaders, it means streamlined operations, personalized consumer experiences and enhanced marketing strategies overall, ultimately driving growth and competitive advantage.

AI is transforming marketing roles

AI is transforming roles within marketing organizations at all levels, from the CMO to team managers and the marketing practitioner. 

At the CMO level, leaders are seeing the shift in consumer behaviors and channels. One of the biggest examples is in Google Search and the impact on SEO — one place where the path is leading to AI agents talking to AI agents. “This is incredibly exciting. This is a new generation of commerce and digital marketing, and the main thing CMOs need to pay attention to,” Scott says.

On the flip side, brand safety is an area to watch out for with AI — for example, with “AI slop.” “That is the exact thing you do not want to be doing. That is destroying your brand,” Scott says. The conversation continues with more detail about the opportunities that come with using these tools well, the areas that AI can have the most impact and the biggest recommendation for CMOs of where to reinvest.

Heads of marketing technology are probably very busy these days. They have existing classic martech stacks but now have to layer in all sorts of AI assistants and AI agents, expanding the stacks they have to manage. In the past, commercial solutions were the most important and efficient ways to make that happen. Scott talks more about how that’s evolving into custom technology with AI, the biggest opportunities and risks from apps and agents and the empowerment it gives martech leaders. “I think this is just starting now, and we’re going to see a lot more of it in the coming years.”

Marketing team managers and directors must have empathy and understanding of how much these changes — the speed and scale of work that can be done — affect those who work under them. It’s great to have efficiency gains, but even if you’re pouring that into creative production, the volume is increasing. The conversation explores the balance of efficiency, creativity, collaboration and “the opportunity to develop more muscle for experimentation” — things that are “net new” for these teams. Directors must encourage their teams to “stretch beyond.”

Marketing practitioners such as growth marketers must lean into AI tools and harness them for creative output and more self-service analytics. 

As Florian summarizes: “A lot of what everyone in the org has to do will remain. But what will change is how they achieve it. We are moving from SEO to the notion of generative engine optimization. We’re moving from structured data to adding unstructured data. The opportunity has become larger in a sense, even if your core functions and responsibilities remain the same.”

“I think this is going to be a real golden age for marketing,” Scott says.

How Snowflake can help

An effective AI strategy requires a robust data strategy, and Snowflake provides the secure and governed foundation marketing organizations need to capitalize on artificial intelligence.

With Snowflake ML, teams can access predictions such as customer lifetime value or churn and obtain recommendations on next best action, campaign prioritization, optimized send time and more. Snowflake Cortex AI provides a wide range of functionality to take advantage of both structured and unstructured data via natural language. This means that marketers can access and use not only text stored in tables but also voice recordings, PDFs, images and more. Conversational AI assistants are within reach, all while keeping data governance and security. Finally, by combining these technologies, teams can build toward Agentic AI, creating autonomous agents that handle complex, multistep tasks such as outcome-based campaign planning or audience segmentation, moving from insight to execution.

Learn more about how agentic AI can transform customer experience and marketing. Download the ebook “A Practical Guide to Agentic AI for Customer Experience.”

And hear more great insights in the full webinar, “Decoding AI's Org-Wide Marketing Impact: An Exclusive Session with Scott Brinker.”