The NEW Way to Use AI in Life Science Sales (2026)

Before we start the episode, Nick and I are doubling down on our YouTube content and this video can be found on our YouTube channel. So head over there to watch the full video. The link is in the description. If you're not using AI as a life science company to close more deals, you're simply leaving money on the table. Over the last couple of years, we've partnered with more than 85 different life science companies to help power their go to market. And the teams that are pulling ahead and succeeding right now all have one thing in common, and it's that they're leveraging and using AI and putting it into their sales and marketing processes. And so in this video, I'm going to break down the exact AI workflows that we're implementing with these other life science companies so that you can copy them and start booking more meetings and closing more deals. Let's dive in. So before I jump into specifically talking about how to leverage AI, I kind of want to talk about the old way or the traditional way that sales is done. In the life sciences, typically, reps have to manually update their CRM. Meeting notes aren't automatically synced in there. They're constantly having to manually research accounts and contacts one by one, writing emails one by one, by scratch. For every single prospect that they want to reach out to, they have to constantly chase leads that are likely never going to convert, and they're manually following up with every lead that marketing sends over their way. So the old way meant that if you wanted to add more pipeline or you wanted to increase revenue, it meant you had to hire more salespeople. And so the problem with that is that if you hire seven reps, maybe two of three of them are good, some of them are just okay. And maybe there's like one superstar performer within there. But one of the advantages of leveraging AI is that you can actually then clone your top performers, right? So you can figure, figure out what they're doing really well from a research perspective, from a messaging quality perspective. How do they know when to reach out to the right people? Then you're able to basically take that knowledge and scale it across thousands of different prospects or thousands of different people or companies that you may want to get in front of. And so one person running a system like this could do the work of a full team of SDRs. And some of that stuff is what we're going to talk about in here. The key thing I do want to talk about though is it's not about replacing people, it's about augmenting them with human in the loop every step of the way. So it's about using AI to make your team, team better. Right? So it's not replacing or removing those individuals. It's about how can we make our existing team better, more efficient and more effective. And so that's exactly what we're going to talk about in this video. I'm going to share five of the ways that we're implementing AI with our clients today. So number one is list building and data enrichment. The way that most people are doing this today is that they go through, they find individual companies, they go and try and find individual people at those companies. Maybe on LinkedIn, maybe you have access to a single data source where you can find some of this information. If you can't find their email address or you're not able to access it from one of those data providers, you're kind of out of luck. Another thing that people will do is they'll actually just like buy lists from third party websites and then hope that those are all qualified. And the problem with all of these different strategies is one, you just don't know if these emails are actually validated. You have to do additional filtering to figure out if these people are in your ideal customer profile. And you have to pretty much do all of this one by one. And so what we've done instead and what we built is we take a number of different data providers where we can see from things like global data, Apollo, LinkedIn, Sileads, Crunchbase, Gossett, all of these different types of publicly available data sources, or even private commercially available data sources in order to create the most customized hyper focused list possible. And each of these different tools has different strengths. Some are great for academics, some are great for publications, some are great for large pharma. But it's really hard to find a singular tool that can solve all of your list building and data enrichment processes. And so what we're then able to do is we're able to use a tool like clay where we can take all of these highly targeted lists of companies of individuals that you want to target. But then you can also run a number of different, what are called clay enrichments in order to create email addresses, or excuse me, to find email addresses to validate that those email addresses are real. And then you can also do things like being able to scrape somebody's LinkedIn profile, scrape a company website to get insights around their pipeline, therapeutic areas, modalities, and then you can basically create all of these unique data points that you have and you you can do it at scale for every one of the companies in your target list, for every one of the prospects that you want to be going after. And this is all done without having to manually research any of these individuals. This is something that probably used to either not get done because it takes too much time, or you spend all day doing your research and trying to figure out who you want to contact. But now you can do this in a matter of minutes in a completely automated fashion. And this doesn't take the human element out of it, right? It's simply just being able to generate lists faster, find out it's the right people, qualify them, and then making sure that you have like unique data points to help you personalize your outreach based on that research that you're able to generate. So the second way that we're really helping companies leverage AI is related to personalized messaging at scale. The typical, I would say, way that people think about using AI for messaging is they just go to ChatGPT, they say, hey, you know, write me a message to this person at this company. And they Hope that your ChatGPT can output an answer for them. And then no wonder why all of that messaging doesn't look very good. It all sounds the same, it's generic and nobody's ever going to respond to that. And so the key that you have to do with any sort of personalized messaging is you need a data source that talks about your company, your products and services, your unique differentiators, your value props, the Personas that you sell to, what those Personas care about. You almost want this dossier of information about you and your company. And then you also have to figure out all of that information about the prospect. What are the things that are relevant to them, Buying signals, therapeutic areas, modalities, phase of drug discovery, whatever it is. And you have the information about what they're doing individually from like, like their LinkedIn profile, from a job description, whatever it might be. And then you have this like data set about that prospect. But then you also need a way to train the AI on how to actually write that messaging. So you need to create messaging frameworks, rules around what good messaging looks like. And as an example, we have a 27 page document that we use as sort of that messaging guidelines and the things that they have to follow in order to actually write a good message. And so if you have these three very specific sort of sets of context for AI, you're actually then able to write hyper specific targeted messaging using AI agents. And that's where you're able to then take that data that you've generated from your lists and all of the information, the research that you have, and then directly translate that into hyper personalized targeted messaging. That doesn't sound generic, that's scientifically accurate and relevant for the individual that you're reaching out to. So the third method I want to talk about are signals and insights. So it's one thing to say, hey, our target profile is oncology companies, 500 employees working in pancreatic cancer. It's one thing to kind of build a list that way. However, not all of those people are actually going to be in the buying window Only I would say around 3% of your prospects are actually going to be in any given buying window for what it is that you can provide. If you're generating a list today and you send your campaign today, that's going to be different from those people six months from now who are maybe in a buying window then. And so the challenge is you don't want to have to be continuously building these lists over and over, but what you want to do is you want to be monitoring for what's going on in the world, what's going on at the companies that you care most about, what's going on with the prospects that you care most about to figure out when is the right time to actually reach out to them. And so these are things like companies announcements of press releases, different hiring patterns for people that are hiring for specific roles that you can help solve their challenges, that they might have job changes or promotions within companies, event attendance, presentations, publications, website behavior. So if somebody comes to your website, you can capture that as well. And so you have all of these different types of signals that come together. And there's all of these different data sources where this information can come from. What you want to be able to do is monitor all of these different information sources so that when something happens that's relevant to what you can solve for, you have an automated pipeline to then go and reach out to those people, right? So you're pulling in all of the publications, the news, the event attendance, whatever it is, you pull that into say a tool like Clay and then you can automatically say, okay, hey, this news article is relevant for us. What's the company that is referenced in that article? And then let's go and find out who are the people within our ideal customer profile at that company who we should reach out to. Let's go and get their contact information. Then let actually write a targeted messages directly to those people based off the context of that article. And that's again something that can be fully automated in a pipeline to where you have the signals and the insights coming in, and then on the output, you have all of the automated research, the people that you should be reaching out to. And then you can even do a draft and send that messaging right away if you wanted to. You can even have human in the loop where you just have the message get drafted for the salesperson and it gets populated into their CRM or into their sequencing platform and they can go ahead and just hit, hit, send from there or tweak if they want. And so what that's going to allow you to do is stay ahead of any other competition. So while some reps may set up Google alerts or they may log into a platform to go look for recent funding, they're probably not doing it in a completely automated way like this. And so if you have it set up this way, you're going to be the first one that's going to be reaching out to these people with a hyper specific relevant message that will help solve a problem that they might have. So that gives you a boost or an edge above the competition there. The fourth method I want to talk about is workflow automation. So the real power of AI comes in when you pull all of these different things together, which is list building, enrichment, messaging, signals, and you pull them all together to get the biggest value out of all of the different pieces and all of the different parts. There are some tools that you can do this with today. There's some tools like Zapier, make N8N. I mentioned clay. So being able to leverage all of these different automation platforms or workflows in a continuous fashion. So you kind of build up these pipelines of data, pipelines of information, pipelines of messaging, of outreach. As somebody who doesn't know how to code, you can leverage these tools quickly and efficiently and effectively to basically automate all of this stuff. And historically this is something that did require code. You had to have an engineer or somebody that was super technically savvy. But nowadays you could just like click and drag a few boxes here or there, update a couple of prompts and you've got something that's pretty functional. And now where AI fits into this workflow automation is when you actually create AI agents. So it's one thing to say if this, then that which is, is if like a lead comes in, put it into, you know, HubSpot, right? That's an automation. However, where an AI agent can take this further is where you combine that automation flow with specific AI models with LLMs. So as an example I just gave, lead comes in via the website, you could push it straight into HubSpot. But what if there was a step in between that automatically did research on the company, did research on the person drafted a message for you. So then right when it comes into the CRM, you have your follow up message ready to be sent right away, or you can simply just send it in an automated fashion as well. You have these agents that can qualify companies, that can qualify people and then also write messaging. And so you're basically taking a ton of the manual human steps out of the way by providing it through automation and providing it through these AI agents. Some other different ways people are using these as well is for follow up messages. So everybody probably has a call recorder that is able to join calls, it can transcribe and take the notes for you. But if you push those into a AI agent that's trained on how you write your follow up messages, it's going to be able to to take a call transcript and write a really great follow up message for you. Put it in your drafts folder to where you just have to go in edit, make a couple tweaks and then go ahead and hit send. And so by combining the automation component with these AI agents, that's going to be where you have the biggest value add and we're going to get the greatest results of actually leveraging AI. The fifth and final method I want to talk about is around sales training and coaching. Most sales training probably happens like once a year, you might do it, that's your sales kickoff. If you're lucky, you've got a good manager who actually does coach you and actually does provide some of that training for you. In a typical training process within a company, you have that sales kickoff, you go through the training, but 90% of that content is just gonna be forgotten after seven days. And then by day 30, 98% of that content is forgotten. And so what you wanna be doing is thinking about how you can always be coaching your reps at every point in time, so on every single call. And you're reinforcing that training that they learned in the kickoff. And you're reinforcing that all the time through year. And so that way sales training doesn't become this one and done sort of like we would just want to check the box and say, say that we did it. And so a couple of ways that you can leverage AI in your sales training is again, you know, think about call Recordings is being able to analyze a call recording of a call with a client and then give it a framework for what a good call looks like, give it a scorecard for what a good call looks like and then score automatically that call for the rep. Have it provide automated feedback to them. There are also AI role playing tools that you can use. We actually did a podcast with somebody a couple months back where we talked about specifically about how you can custom train AI agents, voice agents and video agents to be trained on your prospects so they can mirror certain Personas. And then being able to actually have your reps practice those conversations with those virtual agents is another great way to where you can train people up, practice these skills before putting them live on a call with a customer and just hoping that they can wing it and figure it out on their own. Other ways that you can use your AI is again listening to those call recordings and figure out common patterns or objections or things that are constantly coming up across your sales team. So not just for individual reps, but also aggregated across your whole sales team, which then can help you determine what are the skills that we need to train our team on, what are the biggest gaps that we're facing, what are maybe a product gaps you even have that you need to go and work on internally to fill those product gaps. And that way you're actually getting it directly from the customer's mouth because you're analyzing those call reports. And so what this enables is being able to then train all of your reps at scale on a regular basis, all of the time. And it's personalized specifically to them because you're able to identify each of those individual skill gaps that each reps has. So instead of a one size fits all training, you can actually target it specifically to the individual and how to uplevel their individual skills. By combining all of these things together. You've got list building, you have personalized messaging, you have signals and insights, workflow automations. And then actually how do you execute on those calls? With sales training and coaching it really frees up your time or your team's time to focus on closing deals. Take all of the admin work off of their plates and give them the ability to actually focus on closing and driving real revenue. Every single one of these AI use cases that I mentioned here will absolutely help improve your sales reps performance, whether it be efficiency or effectiveness. But knowing about these workflows and actually implementing them are two completely different things. Things every company situation is different. Your target market, your sales process, your team's capabilities. What works for one business might not work for yours. And that's exactly why we offer free strategy calls for life science companies. And so if you click the link below in the description, you can book a call with us. We'll assess your current situation, identify the biggest opportunities for growth, and put together a plan that you can actually help execute to hit your revenue targets. And that way, you don't have a dry pipeline and everybody's happy. So, once again, click the link in the description. Book a free call with us. If you want to learn more about some of the best, best marketing strategies for life science companies, go ahead and watch this next video right up here.