First Principles Marketing: Al Moore on AI, Change Management and Building Scalable Teams

ICYMI: Al Moore catches up with 10 Minute Martech on why AI success starts with marketing fundamentals.

“The best technologies in martech have a democratizing effect.”

In this episode of 10 Minute Martech, Al Moore, VP of Marketing at Fluency, joins host Sara Faatz to explore how AI is reshaping not just marketing execution, but the way organizations collaborate, communicate and scale.

From cross-functional AI workflows to the growing importance of governance and shared context, Al argues that the real opportunity with AI isn’t simply automation. It’s using these tools to reconnect teams with the core principles of good marketing.

Al’s Big Idea: AI Works Best When It Reinforces First Principles


Al reframes the AI conversation around a simple but powerful idea: The companies that will benefit most from AI won’t be the ones using the most tools. They’ll be the ones applying AI in ways that strengthen the foundations of good marketing.

For Al, AI is accelerating long-term shifts in how customers research, buy and interact with brands. But despite the pace of change, the fundamentals still matter. Clear communication, authentic storytelling, shared context and cross-functional collaboration remain at the center of successful marketing strategies. AI simply raises the stakes on getting those things right.

He also argues that organizations need to stop thinking about AI purely as an efficiency tool and start treating it as a workforce multiplier. Successful AI adoption requires governance, alignment, communication and leadership in the same way successful teams do.

Al Moore’s 10 Memorable Moments on 10 Minute Martech

1. Great Martech Democratizes Access


The best technologies make it easier for customers to research, discover and engage with brands on their own terms.

2. AI Is Accelerating Existing Behavioral Shifts


Customers already wanted more autonomy and more upfront research. AI is speeding that trend up dramatically.

3. AI Adoption Isn’t the Hard Part


The real challenge is implementing AI in a way that is scalable, useful and aligned with business objectives.

4. First Principles Still Matter


Authentic storytelling, helpfulness and customer understanding remain the core of effective marketing.

5. Organizations Need Shared AI Context


AI works best when teams operate with aligned data, governed systems and shared organizational context.

6. Cross-Functional Collaboration Is Essential


Marketing, sales, client success and technical teams all need to contribute to AI adoption strategies together.

7. Experimentation in Silos Creates Problems


Organizations need to move beyond isolated AI experimentation and toward coordinated, company-wide approaches.

8. Open Dialogue Drives Better Adoption


Psychological safety and transparency around AI experimentation are critical for successful change management.

9. AI Isn’t Reducing Work. It’s Changing It.


Most teams aren’t working less because of AI. The work is simply shifting into new areas and new workflows.

10. AI Should Be Treated Like a Workforce Multiplier


The best AI strategies resemble strong people management practices, with guidance, governance and collaboration built in.

Al’s Martech Hot Take


“You wouldn’t hire 10,000 people with no governance, training or context. AI should be treated the same way.”

Al believes too many organizations approach AI purely through the lens of efficiency and automation, without thinking about the structure required to make it successful. For him, AI should be treated like a workforce multiplier, one that still requires leadership, guidance, communication and shared context to deliver meaningful results at scale.

Al’s Inspiration List


Al draws inspiration from both practitioner communities and leaders focused on practical AI implementation:

• Exit Five Community – A valuable space for B2B marketers to share real-world AI experimentation, operational insights and practical workflows.
• Eric Mayhew – A trusted voice in the advertising ecosystem who helps separate AI hype from proven use cases and scalable paid media strategies.

For Al, communities are especially important because they allow marketers to learn collectively and navigate rapid technological change together.

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Next Up in the 10 Minute Martech ICYMI Series


Paula Mantle, VP of Marketing at Branch, joins us to explore how AI is reshaping discovery, why the flood of AI-generated content has created more noise than value, and what marketers need to focus on now to actually stand out.

From connected customer journeys and rethinking discovery to lessons from Branch’s recent rebrand and the growing importance of curiosity in modern marketing, Paula unpacks what teams need to do to stay relevant as digital experiences continue to evolve.

Want to Keep Reading?


Here’s the full transcript so you can explore every insight from Al’s conversation with Sara.

Sara Faatz: I’m Sara Faatz, and I lead community and awareness at Progress, and this is 10 Minute Martech.

Al Moore: The best technologies in martech have a democratizing effect, right? So it’s natural that marketers are going to be early adopters to AI, but that’s not necessarily what’s keeping us up at night. I think what’s keeping us up at night is how do we do that in a way that’s going to be successful, scalable, in line with our business objectives? And to me, that comes back to first principles of marketing.

Sara Faatz: That’s Al Moore, VP of Marketing at Fluency. Let’s get started. Al, thanks so much for being here. I think let’s start with the fact that people are going to tell you that AI is changing the world, and I think it is, but I think what’schanging more than anything is human behavior. I would love to get your take on what the opportunity is for people in marketing or martech in the face of that.

Al Moore: It’s a great question. If you zoom all the way out, the best technologies in martech have a democratizing effect. They make it easier for us to connect with our audiences. They make it easier for our audiences to find us and do their research. I think it easier us to share information and AI is just sort of the latest and maybe most revolutionary example of all of that. So it is having an accelerating effect on a long-term trend where our markets and our consumers and people want to do more research upfront and they want to engage with brands and companies differently. So it’s natural that marketers are going to be early adopters to AI and it’s natural that we are going to want to leverage these tools, but that’s not necessarily what’s keeping us up at night. I think what’s keeping us up at night is how do we do that in a way that’s going to be successful, scalable, in line with our business objectives?

And to your point, in line with how our consumers want to reach us. And to me, that comes back to first principles of marketing. And that is one of the biggest opportunities that we have is to use this opportunity to think about, okay, how can I tell an authentic story to my market? How can I empower my team to be successful? How can I be helpful? These are things to keep marketers up at night for time immemorial. And AI has really just sort of accelerated that. And that is the opportunities to think more systematically around how can we leverage these tools versus just experimenting with them in our silos and within our own works.

Sara Faatz: Have you found new ways to do that? Or are you still in experimenting phases or what is working?

Al Moore: Yeah, I think two things. One is we work as an organization. We’re very focused on building an operating system that’s going to allow advertisers to reach their markets at scale, expand new channels, stay current with how their audiences are looking to shop and use AI powered automation to be able to deploy campaigns at scale.

Sara Faatz: And

Al Moore: We take a similar approach internally within our own teams. How can we actually, not just in siloed ways, look at and experiment with different LLMs and different AI use cases? How can we actually take the marketing use cases, the client success use cases, the sales use cases, the technical and engineering use cases and applications, ladder those up to broader business goals, right? Cross-functional working groups, cross-functional pools of data that are governed and that are organized and structured in a way that AI can safely operate and shared context. And so that’s what I’m most excited about in terms of moving from individual workflow-based experimentation into more of a real organizational way of working that uses these tools and eliminates duped efforts and ensures that everything is, we’re all working to our greatest effect.

Sara Faatz: Right. Well, and I would think that that would take some change management because it’s probably different than the way you’ve worked before. Does it also mean that you have or need different skillsets within the organization?

Al Moore: The change management piece, I think it begins, again, drawing back to first principles, are we open and transparent with how we’re communicating? Is there that psychological safety with your teams around, "Here’s how I’m using AI. I want to bounce an idea off of you, " so that we have open dialogue around how we are using these tools, and then we can take that and apply this towards cool, here are the rules of the road, here are the governance, here’s how we can be most successful with this. So that’s been one major area of focus and also kind of a learning here is thinking about how do we just communicateopenly about how we’re using these tools as a first step. And in terms of the change management pieces and kind of skills that you’re looking for, yes, there’s change management involved and anytime you’re on a journey of a new technology or a new way of working, there’s going to be a lot of change management that happens.

But I think again, having cross-functional leaders, cross-functional workflows and open dialogue across the different functions of the business is a way to kind of unlock and create that environment where people can move forward together

Sara Faatz: And

Al Moore: Share their wins, share their experiments, share their failures, and make progress collectively. And that’s been a big point of emphasis internally within our team and our organization.

Sara Faatz: Well, let me ask you this, who are you following right now for inspiration or information?

Al Moore: There are a lot of great thought leaders out there right now and a lot of leading voices in this space. I think that there’s a lot of value in the communities as well. And I follow and I’m a part of the Exit five community. And that’sa great way for B2B marketers in particular to engage with peer sets and to kind of get the tribal knowledge of, “Hey, what’s working for you? What’s not working for you? How are you moving forward with this in your technology in your team and both from a technical perspective, a strategic perspective and kind of an ops and HR perspective?” So I love the Exit5 community for that. Then within the space that I operate in, the advertising ecosystem, there’s a lot of noise around AI and there’s a lot of jargon. So it’s really valuable to have voices that can separate the jargon from real proven use cases of real practical subject matter.

So Eric Mayhew is a great voice in helping to break down the fact from the fiction when it comes to advertising and AI’s impact on advertising. I appreciate Eric so much. I went to work for him, but I definitely recommend him as a leader for anybody that’s looking to drive paid media at scale. But yeah, again, I would also look to communities because we need to be working together and hearing from each other around how to put this technology to work successfully.

Sara Faatz: One last question for you. You have a martech hot take.

Al Moore: I know it’s a great question. I don’t know if this is so much of a hot take as just maybe something that’s under discussed in the space is the importance of thinking about AI from an HR lens and not just a time savings and efficiency lens. I don’t know anybody that is working less hard right now because of AI or working fewer hours. The best use cases and the best examples of AI being used successfully involve aligned data, business context, and 10x or more impact multipliication. So we need to think about AI as a workforce multiplier and we need to think about how we work with it in a way that we would work with our human teams. You’re not going to hire teams, 10,000 people, and turn them loose with no governance, no training, no context, no data, right? And your best managers are going to be able to collaborate with an AI in a similar way and direct it in a similar way that they might be working with a peer.

Sara Faatz: And so

Al Moore: I think that when we are building our teams and leveraging these tools, we need to think about that with that HR type of mindset. Am I setting my team up for success? Am I providing the right level of guidance? Am I providing the right level of data information so that everybody can be successful? And I think that is an area that’s going to separate people that are just experimenting and running amuck with a bunch of different tools from a really orchestrated and scalable AI strategy and growth strategy across your team and your business.

Sara Faatz: Yeah. Yeah. That’s great. Well, Al, thank you so much. I’ve really enjoyed our conversation today.

Al Moore: I very much appreciate it. Thanks so much, Sara.

Sara Faatz: Listeners, thanks for tuning in. Make sure you like and subscribe wherever you get your podcasts. Until next time, I’m Sara Faatz, and this is 10 Minute Martech.

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