Ep. 157 - AI is Reshaping B2B Marketing—Are You Ready?

Guest: Christina Richards, Fractional CMO & Author of Rise of the AI-Powered CMO

Most B2B marketers think they’re using AI effectively. The reality? Many are barely scratching the surface—and failing to leverage AI as a true revenue driver.

Christina Richards, fractional CMO and author of Rise of the AI-Powered CMO, breaks down how AI is transforming go-to-market strategies, reshaping demand generation, and redefining the role of marketing leaders in B2B SaaS.

The biggest shift? AI is moving from a tool for efficiency to an autonomous operator, changing how marketers engage customers, optimize campaigns, and drive pipeline growth. Those who fail to adapt will fall behind competitors who are already leveraging AI-driven personalization, predictive lead scoring, and hyper-targeted ad strategies.

Christina shares actionable insights on how B2B CMOs and CROs can embrace AI—not just for automation, but as a strategic advantage to accelerate growth and revenue.

Key Takeaways:

• AI is Now Critical Infrastructure: It’s no longer just a tool for automation—it’s transforming how companies generate revenue.
• CMOs Must Become Revenue Architects: The role of marketing leaders is shifting from brand builders to full-funnel revenue drivers.
• AI-Driven Search is Changing SEO: If your content isn’t optimized for AI-generated search, your audience may never find you.
• Agentic AI is Here: Autonomous AI agents are moving from experiment to execution—marketers must prepare now.
• First-Party Data is a Competitive Advantage: With hyper-personalization on the rise, companies that don’t own their audience data will struggle to compete.

Get ready to rethink your marketing strategy in the age of AI—or risk being left behind.

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Transcript

Welcome to SaaS Backwards, a podcast that helps SaaS GTM leaders rethink their approach to growth. We dive deep into what's working, what's not, and how to stay ahead in an ever-changing market.

Ken Lempit: Today, we're talking about, well, what everyone's talking about. B2B marketing, the impact and opportunities associated with AI, and there's no better person to discuss this with than Christina Richards. She's a deep thinker on AI in marketing, a fractional CMO who accelerates growth for SaaS firms, and she's just released on Tuesday,

the latest version of her book, 

Rise of the AI-Powered CMO, which explores how AI is reshaping the role of marketing leaders. We'll be diving deep into what AI means for marketing teams, how CMOs can leverage AI for growth, and where human creativity fits into this AI-powered world. If you're trying to figure out how to make AI work for your go-to-market strategy, this episode's for you.

Christina, welcome to the podcast. 

Christina Richards: Great to be here, Ken. Thanks. 

Ken Lempit: Yeah, I'm really excited to record the episode and dig in deep, but before we do, please tell us something about yourself that I didn't cover in the intro. 

Christina Richards: Well, one thing that's kind of unique about me is that I have both a marketing and an engineering background, and so I've always really loved translating complex technologies into relatable customer value, and that, that heavily influences how I incorporate AI into my go-to-market strategies.

It's not just about the shiny new toys, even though I do love new tech. But it's also about how to leverage those applications into real-world business impact. And that's exactly what I also do as a fractional CMO. I help companies build AI-powered marketing strategies that drive revenue. 

Ken Lempit: That's what we're all about here.

It's all about. All about the Benjamins. We want to help our listeners make as big an impact as possible. So why don't we, why don't we just jump right in and let's talk about the new book, the new edition of your book. What's changed since the first edition was published, and, you know, what are important things people should be looking for in your book?

Christina Richards: So many changes. I mean, probably the first thing to point out is that I didn't expect to be writing a second edition this quickly. But AI is evolving at such a breakneck speed that just a few short months after releasing the first edition, I realized parts of it were already outdated. So, the new edition captures how AI is really making this shift from cool experiments to critical business infrastructure.

And it's no longer just about optimizing marketing. It's now transforming how we generate revenue. One of the biggest updates in the book is talking about the section on top-of-funnel demand generation. I really expanded that section especially since. AI-driven search, paid ads, and even branding are really changing radically.

I also dive deeper into how AI is helping us accelerate sales cycles and improve post-sales retention. Plus, I've updated all 16, all 16, and this took a while, of the AI-powered tools tables that are in the book with the best and latest platforms reordering them in terms of which platforms are really jumped ahead in terms of their development.

But I mean, I think the last thing I'd say about the changes in the book is that it's really about looking at leadership, marketing leadership in the age of AI. That shifting role of the CMO, you know, and the marketers who can really embrace AI, as within the persona of being a revenue architect, are the ones who are doing really well.

Ken Lempit: Thanks. Sounds like there's every reason to get the new one, even if you have the first edition. I want to kind of dig into what the impacts are really on CMOs. It seems to me that AI is moved from almost bolt-on or experiment to a lot of AI native applications and kind of even some DIY projects. So I think we need to talk about. For those that haven't really gotten their hands dirty, you know, what's changed over the last 12 months or so, and what are the things that CMOs really need to be aware of? Like, if they're just getting busy, what should they be aware of? 

Christina Richards: Sure, that's fair.

Well, I'd say at the beginning of last year, like at the beginning of 2024, AI was still A lot about efficiency. You know, people really focused on automating content and improving targeting and streamlining workflows, but late last year, agentic AI really began to catch full traction. And with that, we've moved from AI just being a productivity booster to AI really kind of being the operator.

I mean, instead of just assisting marketers. AI agents are now capable of planning, executing, optimizing with minimal human input if you are ready for that. But this is the fundamental challenge that we're dealing with. These capabilities exist, and there's so many guardrails that need to go around it if they want to be used effectively.

And I think the natural progression of something like that is that the AI is really changing how we work overall. One of the things that's not talked about enough, I want to say, is that it feels like AI is shifting the balance of power. I mean, for the last two decades, it's been all about performance marketing.

If you could measure it, you could justify it. And now, as AI automates that execution, it's shifting a little bit, the differentiators moving back to strategy, moving back to brand and human connection. And I find this particularly exciting. I mean, I think that the marketers winning in the new landscape are the ones who know not only how to leverage as efficiency, but in such a way that they're spending more of their time focused on human-based creativity and storytelling.

Ken Lempit: Well, I want to hold the thought about thought leadership, storytelling, some of the things like near and dear to my heart because I want to unpack a little bit of some of the things you brought up in that last segment. I don't know if everyone's gonna know what agentic means as an example.

So we're going from the era of sort of the enhanced user interface to something different, right? So maybe you could sort of just go back over that and explain what it really means. 

Christina Richards: Sure, so you literally have an AI that you can engage with that acts as your agent as an autonomous agent. They're capable of managing all the factors in a campaign on their own, obviously based on the things that you put into place, but it can make decisions without the human oversight at every step.

Now, depending on who you are, this can either sound fantastic, or it can sound terrifying. And as a personal control freak. I understand the concern there, and there are a lot of things we have to put into place around, you know, ethics and guardrails. But I think we should think about using agentic AI and this ability to allow AI to be more autonomous.

In kind of the Pareto 80 20 rule, right? There's 80 percent of things where you can really leverage this in a powerful way. There's 20 percent of things that you should probably never take out of the human loop. But if you look for what those 80 percent are and what the agentic AI can be very powerfully used for, then you have a real advantage.

Ken Lempit: Are there a couple of use cases for agentic, maybe tools that you would bring up or just at least the use cases where you see big strides and big productivity gains? 

Christina Richards: Yeah, I mean, for every positive case, there's usually going to be some kind of, you know, a gotcha story that has happened. But one of the places where I see this starting to really work well.

When it's implemented effectively is in customer engagement, you know, either within a product-led product or, or in you know, post-sale customer success, but, you know, the marketing aspects of that go across the whole funnel. There's multiple opportunities where you can engage the customer using agentic AI in such a way that you can pull out valuable information and really support the customer in a way where.

They feel like they're getting true, you know, support from the product, from the company in a way that feels satisfying. 

Ken Lempit: Yeah, I've definitely experienced the customer support AI in a great way where it's, it's not just, Oh, I can't help you. Let me connect you to somebody but it actually goes and resolves the query.

It's really fabulous when it works well; I agree with you. That's a great application. Everybody's looking at return on investment. And even though these are our shiny objects, some of these projects will get approved without a business case. But how do we go about building business cases for AI-powered marketing tools?

Do we have enough data and case studies to be able to prove out these values? And, you know, like, where is the bleeding edge of that? 

Christina Richards: Yeah, it's a great question. And really important for your listeners who are trying to get this going in their organizations. First, let's just be honest.

For most people, if you walk into most boardrooms and say, Hey, we need AI because it's the future. Your CFO will probably, you know, choke on something. So you really want to go in armed with we really want to go in speaking the language of revenue. So, so speak in numbers, AI-powered marketing it can reduce customer acquisition costs.

It can shorten sales cycles and increase your conversion rates. And all of those things are things that you can pretty easily turn directly into projected revenue numbers or shifts in revenue. If you, you know, look at your historical data, you can make some projections and then track to those and then add on top of that, the fact that you've got research like McKinsey's latest report that can back you up.

They've got data that shows that AI drone marketing can boost revenue 20 to 30%. And then once you've laid that revenue groundwork, I'd say next highlight the competitive risk. For me, this argument is a real clincher because if your competitors are automating and add targeting, and they're running these hyper-personalized content engagements at scale, and you're still doing things manually, you will very quickly fall behind.

And so I think, you know, start with the numbers and the potential for revenue growth. The mid-tier is going to, hey, we need to get there before our competitors do. And then the last thing I'd say is start small but strategic. Like, don't pitch an entire AI transformation right out of the gate.

Pick one or two high-impact areas like AI-driven lead scoring or automated personalization. Prove your ROI out with those and then expand. And that way, your leadership can see the quick wins and see the value without feeling like they have to bet the farm right out of the gate. 

Ken Lempit: Sounds like good advice.

 Are there other resources besides McKinsey that people might be looking for where ROI or loss aversion might be highlighted? 

Christina Richards: Well, actually in Rise of the AI Powered CMO, there's quite a few case studies in there. And the way the book is set up is at first I start out talking about the whole go to market strategy from front to end, but then I go through each stage, you know, top of funnel, middle of funnel, bottom of funnel. And depending on what you're trying to implement, you can go and look at the case studies that are in there and see the kind of results that real life companies have gotten from their AI implementations.

Ken Lempit: So is, is this new wave of tools and go to market changing the structure of marketing teams? Are there new roles, changing roles here? And what about leadership? What's happening up top? 

Christina Richards: Yeah, I mean, I think it's absolutely changing you know, what teams look like in general. And I think that you know, you've got. New roles coming out. Things like you know, strategists that are both marketing strategists as well as AI. You've got need for AI literate people who can do content and advertising and all of these pieces. But I think the thing for me, and this might be my perspective, but I think the thing that really is the big shift out of everything that AI is changing is this whole concept of

what should the CMO be focused on? Are they a brand leader or are they a revenue architect? And I would say that they're a revenue architect and that the biggest thing that is really, you know, moving the ground underneath CMOs is thinking about how they need to change their approach overall to the go to market strategy and leverage AI to help them do that and be that leader within organization for the overall go to market strategy. 

Ken Lempit: Is that maybe a path to CRO for CMOs. You know, I think we have a real acceleration in the adoption of the sort of overarching CRO role. Do you see some relationship there between, you know, being a revenue architect, being the AI leader and getting more responsibility. 

Christina Richards: Yeah, I certainly do. I mean, I think this is a very debatable topic. And not everybody on the podcast is going to hear this and agree. But, you know, this, this need for revenue architecture absolutely exists especially in B2B SaaS. You need one person kind of looking over the whole end to end strategy.

And in some cases we've created CROs and that they are the ones that do this revenue architecture. But I think that when you have it be the CRO, it comes from a very specific point of view. Very, very end of the funnel focused. I think there's some value in having that revenue architecture persona be with someone who is a little bit earlier in the funnel, but then stays with the customer all the way through post sale.

And that is the CMO. Now, granted, I might be a little biased but in a lot of ways, they're more qualified to actually drive this vision from beginning to end. And I think that. That really is where CMOs need to step up. It's not just about marketing campaigns. It's about aligning with all the way from identifying the ICP all the way until post sale.

And yet in B2B tech, we're not always structured that way. So I think that, that there is an opportunity for marketers, marketing leaders to really own this revenue, architect role while they leverage the AI tools that can help them own that space. And so, yeah, I think they're, they're probably really well fit for that role.

Ken Lempit: Yeah. I mean, uh, listen, cheerleading the CMOs to rise up, to, to take the CRO mantle. So I think we're on the same page on this. Yeah. So I want to go back. I promised you we would talk a little bit about the need for creativity and the power of thought leadership. So I think there are folks that worry that AI is gonna impact the need or perceived value of creativity.

And I guess my question is, you know, how How do you see AI augmenting rather than replacing human ingenuity in marketing and and how do we make the case for creativity in an evermore automated world? 

Christina Richards: Yeah, it's a great question, and it's a real. It's a legitimate concern, but I love this question because it gets to the heart of what makes marketing marketing.

You know, AI is incredible at generating content. But it's still not great at creating truly unique ideas. It can remix what already exists, but it can't come up with a new brand story or a viral campaign hook or, or an emotional connection that makes people care. I mean, not yet. Now maybe that's where we're headed.

But it's not where we are right now and, I tend to think that that will be something that, that will kind of be on that, that edge of never quite getting there with AI as we move forward, hopefully. But it's, it's better to think of AI like a, like extremely eager intern, right? They can draft and optimize and personalize content at scale, but they still need human oversight to ensure the work truly resonates.

It's a great brainstorming and idea generation machine. But it's up to human marketers to really curate and refine and build on those ideas into something that's truly innovative. So I'd say that the future of marketing, it's not about humans versus machines or machines replacing humans, but it's about embracing AI as a creative partner.

Ken Lempit: Yeah, I mean, I, I'm with you there and I think that you know, distillation is never going to be something new, right? So it's, it's always looking in the rear view, but it makes me think that I should start like an AI company called heart strings and see if we can, see if we can get an AI that can tug on a heart string or two.

Cause, cause I agree. It's, it's hard to get the output to be that spark, you know, it's great, but it's not quite that emotionally intelligent output. At least not that I've seen yet. Let's kind of go toward the how to part of the conversation. So what do you think are like for demand generation?

Like, do we have a fair amount of folks interested in demand gen? What do you think are the most effective AI based strategies for demand gen? You know, how can we, how can we apply these tools to the kind of stuff we get paid for. 

Christina Richards: Yeah, absolutely. So, I mean, obviously, depending on where you are right now in your AI journey, different strategies will make sense at different times.

But there are 3 areas that seem to always be smart places to start with AI, and those are in content optimization, which can bleed over into hyper personalization. Predictive scoring and dynamic ad targeting. Those are the three that I usually like to look at first. So if we think about content optimization you know, we, we all know that I can generate content, but more than that, it can predict what will rank and what will engage and will convert.

It's got those heuristics to understand, you know, what's worked in the past and what your audience really cares about and it, it can make good predictions about what will work in the current trends. And really use that analysis to fine tune messaging on a dynamic basis in a way that we can't right now when it's just human managed.

So that's one piece, you know, I would say hyper personalization, except that there is a little bit of a barrier to hyper personalization. You do have to be of a certain size and have a certain amount of resources to really make that work. So I usually start with content optimization. And then the next one I would say is lead scoring.

I can instantly rank leads based on real time signals like past interactions, engagement patterns, behavior on websites, things like that. And then that can allow you as a marketer to make sure that your sales teams are really focused on the highest intent prospects instead of wasting time on people who may not be in a buying cycle, for example.

That was something that used to really bother me in my campaigns is you could get interest, but you didn't really know where they were until you had a few more steps in the process. And I think that that kind of lead scoring based on intense signals can be really powerful there. 

Ken Lempit: Yeah, I like I like that application a lot.

In fact, we just finished an episode with the Co founder of SyftAI which is a, it's actually a sales side tool. But they're going well beyond intent and saying we're going to go out into the world and identify the most likely prospects based on all these things that they put out, like their news releases, their job postings, the structure of the organization. So that the ability to create opportunity by understanding what has worked before, in fact, they go through your case studies to train their AI and so they're looking for case studies that kind of resemble what you've sold before. And if you are large enough. You have enough customers. You can actually do a great job of training the AI on what you know what has worked for you as an organization in the past. So I think that's, that's a very cool one.

Christina Richards: Yeah, well, and that's where the training part becomes so important because as we all know, you know, businesses are constantly shifting form and you. So what your customer looked like two years ago may be different for specific reasons right now. And so if, if you're doing it really well, you're training the, the model up with that set of information so that it can understand those nuances and really give you good intense signals.

Ken Lempit: Yeah, and I love the advertising case. I mean, to me, that's one of the things that our clients seem to worry about the most because it's often their biggest line item. So they're spending a lot of money there and they are trusting in this most cases, either Google or meta or a programmatic kind of a black box.

So to sort of rest control a little bit of where they're spending their money and, and why I think is also a really powerful app. 

Christina Richards: Absolutely. I mean, you know, if I think back pre AI, my most fastidious advertising team, you know, they were never a set and forget kind of group, but they would still probably only check the ad spend and allocation a couple times a day, right? And being able to do that every hour, even every minute. That's a whole other level of performance. So, yeah, that's definitely one of the top three in terms of the smart foundations with AI and marketing. 

Ken Lempit: Yeah. Makes sense to me. So what's coming, what are the trends that we should be looking at?

Like where should we be aiming our, you know, our research for the future? And I realized this is crystal ball is a tough thing, but if you were going to say, Hey, this is the next. you know, six to 18 months. Here's what's really on the horizon. What would those few things be? 

Christina Richards: Yeah, well, this is one of the questions where I could talk way too long on it. So I'll try to keep it to just three or four things. But, I mean, we already started to talk about agentic AI. And I think that that's rather new and not not a lot of your listeners will probably have already dabbled into that. It's just a few very specific portions of industries that have really done that.

But Sam Altman of OpenAI said that this would be the year that agentic AI agents would enter the workforce, is what he said. And I think he's right. I think that's exactly what we'll see happen. Another important trend is how AI generated search has been changing SEO. Now, this has been going on for a couple of years already, but I mean, you guys are all familiar with the AI generated search output that you see in Google now, and it's really turning traditional SEO strategies on their head. So if your content is not optimized for AI search, it's going to get increasingly harder for your audiences to find you. So I think that's really important very closely tied to that is this concept of branding optimization within the LLMs themselves.

And this one I find particularly interesting because when I wrote the first edition of the book most people hadn't even thought of this or didn't know what the term meant. Hadn't heard about it, but now we already have tools like RF Dot, AIO by Ruder Finn, and that helps brands manage how they show up in large language models.

And I think it's going to be a critical piece of future AI driven brand strategy. I mean, I'm sure most of your listeners will log into LLMs pretty much on a daily basis to do various things, right, personally and business. And if you think about that, you really need to understand and manage how your brand shows up there.

I mean, what does the LLM say when your brand comes up? Does it say what you want it to say? And how can you make sure that it does? I think that's going to become increasingly more important. And then probably the other one to mention, because this is really important for people to think about if it's not already top of mind, and that is how critical first party data is going to become you know, we were all reminded in January when TikTok went offline, like, if you don't own your customer data, you're renting your audiences, right?

And now TikTok isn't going to apply to most of your B2B SaaS folks, some maybe, but 

Ken Lempit: we have them out there.

Christina Richards: But it was, it was an event that everybody. Was aware of and it really kind of draws into sharp focus that you really need to own that information. And AI amplifies that situation because hyper personalization that we talked about before.

It really depends entirely on first party data. And if you don't control it, you lose your ability to market effectively., 

Ken Lempit: You know, I think that hyper personalization, I'm not sure everybody can conjure that. And I want to bring up another example of a company that I just got exposed to recently called Unusual.

They're a Y Combinator. Start up and every site visitor gets their own web experience, not just a little bit of content changed, but they get an entire web experience based on what we know about them. And obviously, there's a baseline. If we know zero about you. Well, there's a baseline. But as soon as we start to know stuff about you, you get an entirely new web experience and unique just to you.

And I just I'm not sure people Could picture that level of personalization. Same thing with email. You know, we're used to pumping out marketing emails that are all the same. But if we know stuff about you, we might send out, you know, thousands of unique emails based on what we know. So, it's time to really, you know, expand your imagination as to what might be possible because it wasn't possible before.

Christina Richards: Yeah, 

Ken Lempit: absolutely. So people want to get your book. How are they going to do that, Christina? 

Christina Richards: Yeah, it's on Amazon. We can put the link in the show notes. 

Ken Lempit: Awesome. And you also have fractional CMO services aimed at SaaS companies. How can people find you if they want to learn more about what you could do for them?

Christina Richards: Yeah. So the best place to connect is on LinkedIn. I also have a website, thecmoplus.com, but on LinkedIn, I share every day, every week strategies on AI driven growth. And I really help companies figure out how to navigate this whole process of incorporating AI into their marketing infrastructure.

And so if you need help with that, that's definitely what I do. 

Ken Lempit: That's awesome. Thanks so much for being here today on SaaS Backwards. If folks want to get in touch with Austin Lawrence, our demand generation agency for SaaS, we're at austinlawrence.com. I'm on LinkedIn/in/kenlempit, and I'm there pretty frequently as well.

And if you haven't subscribed to the podcast, maybe Christina's episode has convinced you you ought to do so wherever podcasts are distributed. Christina Richards, thanks so much for being on the podcast. 

Christina Richards: Thank you, Ken. Appreciate it.