In this episode, I am kicking off a new series with a simple warning: mind the gap. Specifically, I am addressing the AI Pipeline Growth Gap, which is the massive disconnect between using AI for tactical content creation and using it to actually generate revenue.
While recent surveys show that over 93% of healthtech marketers are using AI, less than 10% have a strategic roadmap for how it will impact their pipeline. In this episode, I introduce a four-pillar framework designed to help you bridge that gap.
We move past the tactical efficiency use cases to explore how Signal Intelligence, Orchestration, Execution, and Governance can transform your marketing from a cost center into a revenue engine. If you are feeling pressure from leadership to show real ROI from your AI tools, this series will give you the actionable roadmap you need.
Key Topics:
- “(00:00:00)” Introduction
- “(00:01:30)” AI adoption for content versus pipeline impact
- “(00:02:52)” Key statistics
- “(00:04:20)” What the C-Suite actually expects
- “(00:08:00)” The Four Pillars Framework for AI pipeline growth
- “(00:12:30)” Pillar 1: Signal Intelligence and detecting intent decay
- “(00:15:28)” Pillar 2: Orchestration and dynamic routing
- “(00:17:30)” Pillar 3: Execution and Acceleration
- “(00:19:54)” Pillar 4: Governance and Learning to scale
- “(00:22:00)” Overview of the upcoming seven-part series roadmap
If you are interested in discussing this or any other topic, let’s have a chat. Reach out to me directly to schedule a no-obligation discussion. This isn’t a sales call, but rather an opportunity to talk through your questions and challenges.
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Full Episode Transcript
Adam Turinas: [00:00:00] Hello and welcome to the Healthtech Marketing Show. I’m your host. Adam Turinas and, I’m the CEO of one of our presenting sponsors. That’s, health Launchpad. We are the pipeline growth company for B2B Healthcare. I also wanna give a big thank you to our other presenting sponsor, healthcare Now Radio.
We are part of their podcast syndication network and being part of that has been extraordinary. It is five Xed. Our exposures and we’re reaching a much, much bigger audience thanks to the work that Roberta and Carol do at Healthcare Now Radio. So wonderful to be part of that network.
And, maybe if you’re listening to this for the first time. you can subscribe to it. You can subscribe on any of your favorite podcast applications. And we’re also on YouTube. You just search for the health tech marketing show and you can find all of [00:01:00] our past episodes and they’re well over a hundred of them.
So today I’m starting a new AI thing. So, and what I’m focusing on is. What I see as one of the biggest disappointments and frustrations that I see across our community and like me, you may be feeling this pain and lemme tell you what it is.
We’ve all been excited and delighted by how we can use AI for content creation.
And you know, there’s some other thing, other use cases that are where it’s incredibly valuable things like doing research, but the big disappointment is in how we can use it to generate pipeline.
I wanna share a couple of stats with you. So we’ve done a couple of surveys with the Health Tech Marketing Network.
This is a community of health tech. Marketing leaders. [00:02:00] There are about 250 of them. And in the first wave of research, which we did last summer we had 110 responses where we’re in the process of doing an updated benchmark on that now. And there’s a consistent story. So 93 plus percent of.
Health tech marketing organizations are using AI in marketing. No big surprises there. But here’s the disappointing thing, is that the vast majority, so well over 70%. Are just using it in a tactical way. And this is not a criticism, by the way, if this is you don’t say, well, don’t, you know, I’m not criticizing you for being in that situation.
You’re gonna understand as we get into it why you are not alone in maybe feeling frustrated about that. Only about [00:03:00] 20%. When we did the survey back in the summer, we are using AI in a marketing workflow. So again, maybe in some cases actually integrating that in that seems to have increased, so haven’t got the final numbers yet, but it may be close to a third, have actually made progress on that.
So that’s great. But less than 10% have a strategic roadmap in how to use ai. in a bigger way, and particularly in a way to grow revenue as opposed to using it tactically. And this is a problem, it’s a big problem because when you ask the community, what do your bosses expect, what does the C-suite expect of you?
the majority say sort of, they’re kind of two primary things. Efficiency improvements, that’s number one. So it’s the old do more with less thing. But the second thing is we want to see it making a contribution to revenue growth. And actually one of the changes that we’ve seen [00:04:00] between the two surveys is that’s gone from being equally important to efficiency and growth to actually being more important.
So here’s the big disconnect. The majority of our community is using AI tactically, primarily as an efficiency tool. But the expectation is that as marketing professionals, we are gonna figure out. Use AI to grow the top line, and that pressure is growing in 2026.
So what I’ve, done in creating this, what’s gonna be a series, is to go back deep into what I’ve been learning over the last year. I’ve analyzed. Marketing conferences that I’ve attended. I particularly, I, learned a lot last October when I attended Macon, which is the marketing AI conference run by the Marketing AI [00:05:00] Institute.
I really can’t say enough good things about that organization and their commitment to AI literacy for all marketers, particularly for B2B marketers. Like us. I also, I had, several podcast interviewees who, people who’d been on the show, like Nick Panai from Innovalon, who shared, many different ways that they’re using AI to grow the top, top line.
And then there were a bunch of podcasts that I listened to and then a ton of other conversations. That we had in the Health Tech Marketing Network when we meet monthly. And so in total, I think it was well over 30 hours worth of carefully selected conversations, across about 80 people. And I used AI to analyze all of those conversations.
And I’ll get into a little bit about what I learned, but you know, a ton of different use cases. Came outta this so ton of different [00:06:00] applications of AI to grow the pipeline. Honestly, it’s sort of o an overwhelming list and I think that’s the root of the problem. making that big step is overwhelming.
But I was able, thanks to the help of, my friend chat, GPT, I was able to organize those, use cases into four key pillars. And those pillars are signal detection. the second one is orchestration. The third one is, execution acceleration. And then the fourth one is governance and learning.
And what I’m gonna do is in this episode, I’m gonna explain those in a bit more detail. in the following episodes,
My aim with this series is that at the end of it, you’ll feel better informed, hopefully inspired, and hopefully ready to take. A big step forward in shifting from [00:07:00] more tactical use of AI to strategic use of AI to grow your pipeline.
And I want you to, at the end of this, to have some very specific things that you think you can take action on. I’m really hoping that as an industry, that this helps us collectively. To move forward with using AI to its full potential as a result of this, that you actually see top line growth that you can correlate directly back to what you’ve done with ai.
they’re gonna be seven episodes, so today’s episode is about. The pipeline gap, the AI gap in pipeline growth and to introduce the framework to you in a couple of weeks. So I’m alternating these. we do an episode every week. You know, one week’s an AI episode, the next week’s, a non-AI episode.
in two [00:08:00] weeks, We’ll do a deep dive into the first theme, which is Signal Intelligence. Episode three will be about how you can master the use of AI in orchestration. The fourth episode will focus on execution, and acceleration. Things like building virtual teams, automating workflows.
And then episode five will be about governance and learning. So, you know, the healthcare specific considerations that can make or break your implementation. it’s kind of, this is an area which I think a lot of people. I haven’t really been thinking about that hard, and I just think without a really good foundation, you just can’t scale your use of ai.
And then episode six, we’ll be kind of putting it back together, which is how do you build a roadmap, and how do you select what you are gonna do and putting all the pieces together. And then with episode [00:09:00] seven. I’m gonna try and dive into some case studies, some specific examples from across the community.
So let’s move on to talk about. the individual themes. I’m gonna start off with the four pillars as I call them. and so again, let’s start off with the first one, which is signal intelligence. And that’s about seeing what matters, seeing it sooner, and seeing it in a way where you have more actionable intelligence.
and so it’s something which is moving from. You know, being able to sort of see a signal to knowing actually more information about the signal and what you can do with it. So lemme give you, a specific example of that. So. you might be able to use AI for what’s called intent decay.
So, you know, you are, maybe you are, doing a BM, you’re tracking, couple of dozen accounts you are noticing that one of the accounts [00:10:00] that’s been very actively engaged with you suddenly goes cold. So what does that signal mean? Does it mean that they’ve made a decision, and you’re not in the running?
Or does it mean that something’s changed in their organization? So, you know, again, you can use AI here to help analyze that, maybe analyze some of the previous signals to develop some hypotheses about that. And then take a next best, best action. Maybe it’s to send them a Hail Mary. Maybe it’s to send them some sort of how to type content that will help them as they move into their next phase of their decision.
But that’s the notion of it. the other one might be, you know, you are enga, you’ve been engaging with the champion at an organization that seem, that’s been actively engaged and they suddenly stopped. Responding, they suddenly stop you. They stop opening your emails and [00:11:00] you think they’ve gone cold.
But, you might be then pick up some additional signals from other people in the organization, which may mean that the, they’ve actually moved on to the next stage, which is they seem to be much more actively. Ready to decide that you are their vendor because they’ve got people in purchasing, checking out information about pricing or implementation or you know, something like that, that HA shows that they’ve moved on to the next stage.
And so what we’ll get into in this episode is how you can use ai to. Detect those signals and then figure out what to do next. Second pillar is orchestration, which is about choosing the right response at scale. So signals without action are interesting data, but orchestration means you are using AI not just to identify the opportunity, but [00:12:00] to decide how to respond.
So it goes really closely with signal identification, and think of it as the conductor of an orchestra coordinating all the different instruments and you’re using the sheet music to guide what you’re gonna do. so I’ll give you an example. So instead of, this lead scored 70 fives center sales, it’s this account showing enterprise buying patterns.
And so we need to route this to the enterprise team and trigger and outreach executive outreach sequence, and then we know we’re gonna need to prioritize this for developing a custom ROI model that that would be an example of how you are shortening the cycle between, knowing an accounts in market to taking a much more precise action, which is tailored.
To the behavior that you are seeing from the organization. so another example might be personalizing the journey. So for [00:13:00] example, the, CFO gets ROI content tied to pricing. The IT director gets integration guides, the end user. So maybe a chief nursing officer gets training videos and these are all automatically coordinated.
And so this is one which I think you’re gonna say, well, yeah, But the problem is it’s really hard to do. And, I think many of the big. Marketing platforms like Demandbase are really good at that, so we’ll, get into that. And then the other area we’ll get into is about continuous experimenting.
So how do you use AI to improve the way that you do AB or multivariate testing? The third area is execution, acceleration. It’s about reducing time to value. And this is where the rubber meets the road, right? So, all the, or intelligence and orchestration in the world doesn’t mash if you can’t execute fast enough.
And in health tech, you know, speed is meaningful. And it’s weird, [00:14:00] right? Because we have very, very long sales cycles. And you can go for long periods without any real signals going on, but then suddenly you’ve got to got to scramble and you know, being able to respond quickly with the right information can make a really big impact on your likelihood of success with a particular deal.
So there are all kinds of different things I’m gonna get into in this particular episode. I’m gonna explore one of the quite controversial areas, which is AI SDRs. So these are virtual agents in some industries, some parts of technology, particularly SaaS where maybe it’s a, is there a shorter sales cycles?
The deal is more transactional. Ai SDRs that can basically call 24 7. They don’t get tired, they don’t quit. They learn really, they, you know, they learn and improve really well, where they make a lot of sense. I think there’s a lot of debate [00:15:00] in our industry as to the impact that they can have, particularly with the sales cycles are so long.
But, I want to dive into that because I do think there is a potential for them in our industry. another area is about creating Ag Agentic workflow. So I’ll share, something I heard from the guys at In Lon about how they’ve created an AG agentic workflow. For page search, which just blew my mind that they built this in-house.
And then I’ll share some other tools and, and tricks as well. The last area is governance and learning, and that is how you can build a foundation that’ll enable you to scale what you’re doing without breaking trust. and the core concept here is that. you know, as you start to use a lot of these tactics at scale, you are creating risk because you’ve got, more people using it and they might be using [00:16:00] it without training and, and without the sort of care and diligence that you might use yourself.
I heard actually about a, a healthcare company, that, hired a new chief growth officer and they had been using, their CRM in a really structured and disciplined way for how all outreach was done. And, um. A lot of the salespeople were saying it was just holding them back. And so the first thing he did, and this is with good intention, was to basically say, you don’t have to use that system for sending out all of your emails and your, you know, LinkedIn outreach.
Or your phone calls, you just, just go ahead and, you know, go in and, and, do it without doing that. But just go back and log the transactions, the calls and the emails back in the CRM. And so, you know, that frees up the salespeople. That’s great. But if you also say to them, and you can use AI to do it, and here’s some prompts and here’s some things that you can do that work.
You have no idea how they’re gonna be [00:17:00] using it. That puts your company at a great deal of risk, basically reputational risk. ’cause a lot of what you generate, you know, a lot of what untrained people would generate, which at GPT is crap. And then it also creates potential, legal risk liability, particularly in areas like biotech where you might be saying some things that actually are not compliant with where you are from an F-D-A-F-D-A standpoint.
And so we’ll get into how you can build a foundation that will ensure that you do no harm. And in fact, what’s happening is, that your whole organization is doing things at scale, which actually are positive and not, potentially create risk and a negative impact. so that’s it.
So that’s what we’re gonna be doing. That’s what I’m gonna be doing, over the next, couple of months. actually, I think this might even take us at least through March to get through this. But what I want you to [00:18:00] take away from this, and I hope you’ll subscribe and come back to this, is that in this series,
I want to help you.
overcome the frustration that AI is just not living up to its full potential for you and that you can be using it. As an organization in a much more strategic way,
and I want you to help you overcome what seems like a pretty overwhelming barrier. And trust me, I get it. we use AI very actively in what we do, what we do and, how we use it for pipeline growth.
And I’ve been surprised that the barriers that, we are hitting and we’re still working through. By the way, if anybody out there tells you they’ve got it cracked, and you know, there’s an easy way to AI enable your pipeline, they’re full of it. nobody has got this fully figured out.
there’s a lot of options out there to help you do it, but at the end of the day, you are the one that’s gonna be on the hook for developing the right strategy and the [00:19:00] right plan to do this. And my hope with this series. it’ll help you, take the right steps in the right direction.
So this is helpful to you, please subscribe, tell your friends, email, anybody you think might find this useful. Post about it on LinkedIn, if you like, I’d love it if you would. Really would appreciate it. and by the way, if you wanna have a chat about this, you know, we’re still working out a lot of this stuff.
I don’t pretend that we’ve got it cracked, but we do have some things that we’ve figured out and that we can share. so, you know, you can book a call with me down below and love to have a chat with you. It’s nothing really for sale here. I’m always looking to get other perspectives. So, please do reach out Anyway, hope you listen to more of these episodes.
Hope they’re helpful. Would love to get your feedback and I will see you on the next one.
