Biotech AI Strategy: Why Most Pharma AI Projects Fail & How to Fix It? ( ft.Rose LaRocca-Fisch)

AI is moving incredibly fast across the life sciences sector, but many organizations still struggle to build systems that deliver real operational value. In this episode, tech leader Rose LaRocca-Fisch explains why strong data governance and business alignment must come before chasing software trends. Please visit our website to get more information: https://swangroup.net/ 

Rose shares her practical leadership experience guiding pharmaceutical companies, CDMOs, and global biotech organizations through massive growth. The discussion breaks down why high-profile tech implementations collapse and outlines the exact steps needed to prepare your infrastructure for enterprise-grade tools.

Key themes covered in this conversation:

• Why does advanced software amplify existing operational flaws instead of fixing them
• The OASIS framework for sustainable and scalable IT transformation
• How data readiness directly impacts clinical trial success and manufacturing yields
• Real-world applications using platforms like Databricks to speed up patient enrollment
• The shift toward AI-assisted work and managing data integrity risks

Links from this episode:

• Get to know more about Steven Swan: https://www.linkedin.com/in/swangroup 
• Get to know more about Rose LaRocca-Fisch: https://www.linkedin.com/in/rose-larocca-fisch 

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#biotechai #pharmatech #lifesciences #datagovernance #clinicaltrials #ittransformation

Transcript

Steve Swan [00:00:00]:
Welcome to Biotech Bytes. I'm your host, Steve Swan. And today I've got the pleasure of being joined by Rose LaRocca. Fish. Rose, thanks for joining us.

Rose LaRocca-Fisch [00:00:13]:
Thank you, Steve. I am very excited to be here.

Steve Swan [00:00:15]:
Yeah, we're excited to have you. So Rose has been the head of it for several organizations over the last 15 plus years. I have that. Right? Roughly, give or take.

Rose LaRocca-Fisch [00:00:24]:
Give or take, yeah, give or take.

Steve Swan [00:00:26]:
No, exactly. So, but before we get going, before we get going, you know, give our audience a quick little introduction to you, you know, where you came from, how you got to where you are, those kinds of things, because that gives us a little, little background and context into, into you.

Rose LaRocca-Fisch [00:00:44]:
Okay, sure. Great. So over the course of my career, I've had various IT roles, all focused on transformation. Um, my career has spanned accounting and audit, enterprise systems consulting, and then IT leadership roles in life sciences. And my specialty is coming into an organization or into organizations where it's a key growth moment. Right. And then helping that organization scale, adapt, operate more effectively. So I started out in audit at ey, which doesn't sound like the most obvious starting point for a career in IT transformation.

Rose LaRocca-Fisch [00:01:20]:
Right. But it was, it laid the foundation for me. I was on the emerging growth team and we focused on pretty much governance controls, scaling, finance organizations, and readiness for capital events. Right. Then I moved into enterprise systems consulting at Oracle. And it was right at the tail end of the.com era, right. So if you remember Internet growth, Y2K, ERP adoption, I like all collided at the same time, right? And it was like this huge driver from massive global ERP implementations. The mindset was we modernize everything as fast as we can.

Rose LaRocca-Fisch [00:02:02]:
Right. Or we'll be left behind. So I implemented erps globally, working with various business functions. Finance, commercial, manufacturing, supply chain, clinical quality. Right. That was my first exposure where technology was the driver of scale. Right. So the hardest part is not the software, right? It's never the software.

Rose LaRocca-Fisch [00:02:23]:
It's always aligning the process, the data, the people, so that you get, you know, you get information that you actually can use to run your business. Then I found my way into pharma for my first pharmaceutical on, on Long Island. And we were, that company was at the edge of a big growth phase. In my first three years there, we launched our first commercial product and that growth was exponential, right? You can imagine, like the growth when you go commercial. And my role there was building the backbone for, for that scale, right? So modernizing the systems, the processes, the data so that the business could keep up and my first exposure to all of the GXP and regulatory considerations that come with pharma. So that company was eventually bought by a large Japanese pharmacist and I moved into a leadership role at a CDMO in New Jersey. I joined again during a big transition. We were moving from development focused work to global to commercial manufacturing globally.

Rose LaRocca-Fisch [00:03:28]:
Right. And scaling a CDMO brings a whole new level of complexities, right? It's multiple clients, strict regulatory expectations, quality systems, supply chain, rigorous financial discipline. And uptime at that point becomes mission critical. My role was building the enterprise systems, the foundations that allowed the CDMO to scale globally. Right. So we were in Japan, we were in Germany, and then a few locations in the US and now most recently, my, my last role was at, as a CIO at a global biotech. We had internal manufacturing. So again, I joined right when we were moving from pure R and D to clinical, which meant it included standing up to global manufacturing facilities along with supporting all the enterprise systems that go along with those facilities.

Rose LaRocca-Fisch [00:04:24]:
And that meant building the operational, the financial, the data structures from the ground up, right? So now, today, right. With AI and advanced analytics and data platforms all reshaping biotech and how biotech works, we're at another major inflection point, right? It's another major inflection point. The technology is incredibly powerful, but one lesson from my career that just keeps repeating itself is AI amplifies whatever foundation you already have, right? So if your data, your processes, your controls aren't strong, it just accelerates the problems. Right? So you gotta get that. All right?

Steve Swan [00:05:01]:
You do? Yeah. You know what's amazing? I'm going to go all the way back to the beginning, right. And, and you and I have never really talked about this, but you know, I get the question all the time. Where do CIOs come from? Where's. Where do you see most of it? I either see them in infrastructure or erp, you know, because you're, I'm going to use a sports analogy. You're like the catcher on the field. You get to see the whole field. You get to see everything going on out there, you know, all the moving parts, you know, who's doing what, where and when.

Steve Swan [00:05:27]:
You, you know, and to, to see all that and then to move into what you did, Right. You know, being able to. Okay, if that's not right, if that's not right, if that's not right, none of this matters, Right?

Rose LaRocca-Fisch [00:05:39]:
Exactly. And it's that, it's that foundation in accounting and audit. It kind of. It Gave me that foundation of things need to be in a process, right? There is a way that things is a framework that needs to happen and that drives all of my work. I have frameworks, I develop my own frameworks that I bring.

Steve Swan [00:05:57]:
I was going to ask you that.

Rose LaRocca-Fisch [00:05:58]:
Yeah, yeah, I do. I mean, I have something called. I know it's a, it's a corny name, but I call it oasis. Right? Oasis. It stands for operating alignment, for scalable impact and sustainability. And what that means, it's really fancy, but all it means is you have to, you have to know what work you're trying to get done. What are we actually doing? Right?

Steve Swan [00:06:15]:
Where are we going? Where are we going exactly? You always need to know where you're going exactly.

Rose LaRocca-Fisch [00:06:19]:
Then you need to align business and it, right? Business and IT always have to be aligned. Then you need to assess your skills. What skills do we have? What resources do we have? What do we need? And then the capability, right? Do we have the capability to actually make this transformation successful? Whether it's something as small as a new HR onboarding process to as big as a global quality system implementation in, you know, five countries, then it's the infrastructure and the data that has to be right. And then scale has to be sequenced. You have to sequence scale. No one, no company can, can scale everything at the same time. You can't do. It's like that big bang approach versus like the scaling, right? So, so that's my framework and I, I use it in all transformations that I work on.

Steve Swan [00:07:09]:
Well, yeah, I mean, and, and, and so you need. Or you, you have to go towards, because of who you are and what you do, which is awesome company that wants to, like you just said, align business and it. So I, in, in our world, in biotech world, right. I would say, you know, I, I call it the business value of it, right? Get getting the most out of what we spend on it, the ROI on it and the folks, the companies that have those business partners, right, Aligning business with IT are creating more of an IT organization that's proactive, right?

Rose LaRocca-Fisch [00:07:43]:
Right.

Steve Swan [00:07:43]:
Instead of reactive. The reactive one, right, Is more keeping the lights on. They're more, they're more being able to. They're getting pushed into a box where you're a cost center. So you're not at the table, you're not being heard, if you will. But if you are proactive, right, and you're aligning business with it, or you're working with business and you're at the table, you're a Value partner. You're adding value, you're adding, you're adding money to the bottom line. And if you're doing that, that's awesome.

Steve Swan [00:08:11]:
But, but first the company has to buy into that.

Rose LaRocca-Fisch [00:08:13]:
Right, Right. And, and with AI, you know, so it's always this, do I have a seat at the table? Do I have a seat at the table? With AI I will tell you, every leader has been reaching out to me saying, hey, what are we doing? What's our AI strategy? How are we adapting? We can't be left behind. Right. Sounds all familiar. Right. All familiar from past IT trends. Right. But another very important, the difference with AI, Steve, is how fast it's happening.

Rose LaRocca-Fisch [00:08:38]:
Right? It's, it's happening exponentially.

Steve Swan [00:08:40]:
Like you open the newspaper, it's different. Well, not newspaper, the Internet.

Rose LaRocca-Fisch [00:08:45]:
Exactly, exactly. It's change. It's not. You know, with ERP Transformations, we had multi year projects. That was okay. Nope. AI, things are changing. Whether it's ChatGPT or Copilot or Claude or, you know, I, I had a small project using databricks.

Rose LaRocca-Fisch [00:09:01]:
It's just the, the technology is changing so quickly, so we need to adapt quicker.

Steve Swan [00:09:07]:
Right, but it's changing. What? You said it already a half a dozen times. It's changing, but it's not, it's the same. We're recycling. You know, it's. Is it the Internet? Is it, you know, whatever it is,

Rose LaRocca-Fisch [00:09:19]:
erp, Y2K is it erp? I know, it's the dot com era. Yeah.

Steve Swan [00:09:22]:
It's just, it's the same sort of thing.

Rose LaRocca-Fisch [00:09:25]:
It is. It's the same thing. It's the same. It's not, it's the same transformation cycle. Right. With a new technology, it's just happening a lot quicker than some of these.

Steve Swan [00:09:34]:
Right. But the same process. Right. You know, aligning the business and, you know, the whole thing. What I'm seeing right now, what I've seen with AI, the trend is been. So it was getting, and, and I'm not asking you to confirm or deny this, it was getting beat up. They were getting the, the, the leaders to come in and they were saying, hey listen, I just did some homework with my fifth grader. AI works.

Steve Swan [00:09:56]:
So it's Monday. Can we plug this in and have it working on Thursday? And that's not a thing. Right. So it took a while for, for it to get that message across, I believe, you know, getting your data ready. I mean, it takes a long, long time to do all this stuff. But today, what I'm seeing like as we sit here Today, you know, you know, mid, mid, mid Q2 here in 26 is that companies are starting to sort of, let's retrench a little bit. Let's figure out what we need and what we have and what they're doing. Right now I'm working with several companies that are laying down the Technology Infrastructure foundation, right? Running a network in a cloud environment, cloud hosting, cloud services, right.

Steve Swan [00:10:39]:
A lot of sd, wan, they're all talking, you know, the security, the IAM and things. So they're laying that down to put their data on top of that, then to put their AI on top of that. But to date it, it was, let's just get to AI and that's. You can't. You, you need, you need stuff before that and you also need your data to be ready, right?

Rose LaRocca-Fisch [00:10:55]:
The initial reaction across at least my colleagues in I, in IT and the CIO world was, oh, we're going to turn it off, we're going to let no one can access AI. We need to secure it, we need to secure it, we need to secure it. Yeah, you know, and now, you know, and then it moved to the point, okay, now we have these enterprise grade AI solutions where now our data is secure, right? Because you need to worry about the security of the information that you're putting into these AI systems. And now it's okay, now it's secure. We have governance, we need training, right? So there's the governance aspect, there's training your employees aspect, right. And now what are the business case scenarios, right? So how can we use AI effectively and succeed? Because these, a lot of the business scenarios that you're seeing that companies are employing, because to your point, it was, it was just this influx of, oh my gosh, we need AI right now. It needs to be in my clinical world, it needs to be in manufacturing, it needs to be in quality, right? How can it write my SOPs for me? Can it go look at the data coming out of the manufacturing facility and tell me if my blah, blah, blah, blah, blah, right? So now we're at a point where these business scenarios need to make sense, otherwise they'll fail. And a lot of these AI projects that are happening are failing.

Rose LaRocca-Fisch [00:12:09]:
Whether it's because it never gets to production or user adoption fails. Users aren't using it the way they, you know, to effectively.

Steve Swan [00:12:18]:
Yeah, well, I'm seeing. So what I saw was the numbers I heard were 75% of these projects were failing and a lot of folks were pointing at the data not being ready. There were a million different reasons you know, and I think these, these infrastructure, these newer infrastructure happenings which I just mentioned a minute ago, are part of, you know, trying to mitigate some of that. Right. You know, and then you have, I mean, going back to security and the governance too, right? You've got the security and the governance around your data. But now I'm starting to hear a lot about security and the governance of the outcomes, the outputs, you know, with the data we're talking about the inputs now, we're talking about the outputs. I mean, we've got to govern that, we've got to own that, we've got to say that's ours, that's our employee, effectively. Right.

Rose LaRocca-Fisch [00:13:06]:
Especially in biotech, right.

Steve Swan [00:13:08]:
Where you know, the FDA is not saying you got a mulligan on that, right?

Rose LaRocca-Fisch [00:13:11]:
No, no. And especially with biotech and the regulations and having to ensure that the data that, you know, you, you've got part 11 compliance, you have data integrity concerns, right? These all are factors when you're using AI and biotech. And you know, the FDA and the eu, they've all issued guidance related to how you use AI, right? Yeah. But to your initial point, Steve, especially in smaller biotechs, data is an issue, Data governance is an issue. Data is everywhere in this tool, especially with like shadow its, because you see that a lot, right? So when, when it is not at the table, allows for shadow it to happen, right? So you've got your bioinformatics team doing their own thing, you have your clinical team doing their own thing, right? But data is, data governance is a real concern. Where is your data? Is your data, what's the data integrity look like? Right? And can we get that data together so that we can have meaningful, impactful AI solutions or AI projects? And with biotechs just coming from having just been in a smaller Biotech, we use CROs, right? The CROs have our data, those independent investigators have our data. How are we getting that data back so that we can make impactful decisions? You know, the project that I just recently worked on with AI and databricks was using our clinical data at different sites globally to be able to enroll our patients quicker. Right? Identifying those patients, are we enrolling them as quickly as we can? Because it's all about patient enrollment when you're in phase two.

Rose LaRocca-Fisch [00:14:52]:
Sure it is, right. But it's the first, the very first step is we need that data and it needs to be good, it needs to be good data that we're able to use. And that's where I see a lot of the Struggle now is getting that data at a point where it could be used with an AI.

Steve Swan [00:15:09]:
Yeah. I mean, it's the gasoline that drives the engine, right? Absolutely. And, and you know, you see some of it taking place. AI, I mean, Right. And using that structured data coming out of your ERPs, coming out of some of your clinical data, coming out of some of your CRM systems.

Rose LaRocca-Fisch [00:15:25]:
Yeah.

Steve Swan [00:15:25]:
Customer service systems developers, engineers. But away from that, you know, I mean, it's a lot of IT discovery in the labs, it's all. It could be in notebooks, it could be all over the place.

Rose LaRocca-Fisch [00:15:35]:
It isn't elns, it's in elns, it's in homegrown systems. Right. Because that's another thing that happens when you're in these. In biotechs, you'll see a lot of homegrown systems. Right. And you know, how, how quickly were we able to modernize our systems? Right. And that's, that's key because with biotech, it's. Change is constant.

Rose LaRocca-Fisch [00:15:55]:
Right? Biotech and change are synonymous. Like, change is constant in biotech. It's just the way of the world, right? It's like, what's that saying, that just give it a second, it'll change. That's.

Steve Swan [00:16:05]:
Yeah, right? Yeah, yeah, yeah.

Rose LaRocca-Fisch [00:16:06]:
It's totally the way it is. But with that kind of change, you want that entrepreneurial spirit, but you need the data, you need the governance, you need the structure. And that's what, you know, someone like me does, right, Is we put in that structure so we can have our data governance, so that we can build and scale on that. But if you don't have that foundation, right, AI is not doing anything for you.

Steve Swan [00:16:27]:
I also think we haven't played up on your point enough where you need to know where you're going, right? You need to know your destination. I've gotten calls from folks to find their AI person, and I say, why, what are we doing?

Rose LaRocca-Fisch [00:16:39]:
Chief AI officer.

Steve Swan [00:16:41]:
Yeah, we just don't, we, we don't, we don't want to miss out. Like, what's it look like in the marketplace? Well, where are we going? You know, because I had one company a couple years back call me two years ago this past January and say, we need chief AI officer. I said, okay, cool. What, what, what's, you know, what do you need? They said, well, we just feel like we don't want to miss out. And I said, oh, boy, that's not for me, you know, And I know, I know the person they hired. I know the new head of IT there. And on the side, they both have come to me telling me it's not really working out, you know, that's why. Because there was no.

Steve Swan [00:17:15]:
There was no.

Rose LaRocca-Fisch [00:17:18]:
Yeah, what's the business?

Steve Swan [00:17:19]:
No, no destination. What's the business case? What are we doing?

Rose LaRocca-Fisch [00:17:21]:
You know, what are we solving for?

Steve Swan [00:17:23]:
Yeah, what are we solving for exactly? What's our. I mean, I always tell folks, it's just like when you're in an interview or when you're anywhere. You need to know what, what, what the destination is. You need to know the address you're heading to before you put it in gps. You can't. GPS is really smart, but you need to know where you're heading, right? And same thing with AI. It's really smart. I had a guy that I placed less than a year ago, he does a lot of the MES systems and he said to me, he said, steve, you know, everybody keeps telling me AI is coming from my job.

Steve Swan [00:17:51]:
I said, what do you think about that? He said, it's never taken my job. I said, why? He said, Maybe I spend 20% of my time hands on keyboard doing the technology. The other 80% is sitting with business figuring out, helping them figure out what they're asking me for.

Rose LaRocca-Fisch [00:18:05]:
Right, right.

Steve Swan [00:18:05]:
And then getting the ask massage so everybody's happy with it. And then I go and solve that problem. He goes, AI is not doing any of that. There's not a chance. He said, you need to know exactly what you're asking.

Rose LaRocca-Fisch [00:18:17]:
AI is not changing the work in the middle. It just doesn't.

Steve Swan [00:18:19]:
No, the work in the middle, that's what I always call it. Yeah, the work in the middle. It's not, you know, for what I do, for what you do, for what mes, for anything. It's. It's helping, you know, on the ends, but it's not doing the work in the middle. And that comes from experience and that comes from knowing, you know, how to read the room and how to read the tea leaves and what, what really needs to happen.

Rose LaRocca-Fisch [00:18:38]:
So.

Steve Swan [00:18:39]:
Oh, yeah, you know, there's a lot of moving parts there.

Rose LaRocca-Fisch [00:18:41]:
And something else that I've seen change. You know, we walk in with my. I have my three year roadmap, right? This is my three year roadmap. I'll update it annually. I'll meet with the business annually. Right. I would say my last two years as CIO of the seven years was my, my roadmap was changing quarterly, Steve, quarterly. I was updating orderly on new.

Rose LaRocca-Fisch [00:19:03]:
I mean, granted, biotech changes, but still, you know, two year, three Year roadmap is usually feasible. Not with AI. At AI, I was at a quarterly

Steve Swan [00:19:10]:
update, so that I was going to ask you, is that what was changing? AI? Was changing it.

Rose LaRocca-Fisch [00:19:13]:
Yeah, I was changing it. AI was changing it. How can we use AI more effectively to solve this business problem? And those business problems change, right?

Steve Swan [00:19:22]:
Yeah.

Rose LaRocca-Fisch [00:19:23]:
And they're, and they're, it's quick to do. As I said, I see a lot of AI now from the biotech world in manufacturing. Right. Looking at your manufacturing results in clinical with enrollments and that type of thing. And so that's really where I see the, the biggest impact AI can have right now.

Steve Swan [00:19:42]:
Right. Well, so I was. Some of my other CIOs have, I've done some, you know, podcasts with they, they two things, right? They talk about AI is creating the bionic employee. You know, it's really, it's, it's allowing folks in, in, in that guy in MES that I was just telling you about or somebody in accounting or whatever to, or, or, or somebody like my kid, right. To, to let AI take care of some of its more mundane tasks. Right. And then that individual can focus on sort of higher level stuff. Right.

Steve Swan [00:20:13]:
And some of the CIOs have told me that they feel that those bionic employees that AI is creating tend to predominantly, at least for now, the ROI is paying off in the customer service area. Right. We've all seen that. Marketing, communications and then the, the, the developers, the hands on keyboard developers. It's, it's, it's, you know, AI is writing their actual code, they can work with business AI is writing their code, then they understand the architecture and can put it all together. So it's saving them a few hours so they can focus on.

Rose LaRocca-Fisch [00:20:42]:
So that bionicle is replacing the initial work. Right. So, so our roles are changing from the initial developer to let me review and let me make sure that this makes sense and let me optimize. That's where the rules are changing. So roles are changing, not being replaced. They're changing, it's changing. So I've used countless tools, whether it's Copilot or we were a Microsoft shop. So whether it's Copilot.

Rose LaRocca-Fisch [00:21:08]:
Let me write the structure of my SOP. So it got me 80% there and then the extra 20% you needed an expert to. This is my process. Right.

Steve Swan [00:21:18]:
So not replacing, just enhancing.

Rose LaRocca-Fisch [00:21:20]:
Optimizing.

Steve Swan [00:21:21]:
Optimizing, yeah. And that's where there's no need to be scared of it. It's going to help us all and it's going to be awesome. It is awesome.

Rose LaRocca-Fisch [00:21:28]:
It is awesome.

Steve Swan [00:21:28]:
And it's going to continue to be awesome.

Rose LaRocca-Fisch [00:21:30]:
It is awesome.

Steve Swan [00:21:31]:
Harnessing it and figuring out how we interact with it, you know. So now when you look at your traditional it, what you've done, right, whether it's your erp, whether it's your other things, how do you see, not only from a data perspective, right, you're putting a lot of data out of those systems, but how do you see, you know, in the recent past, we heard a lot about these software companies, their stocks getting dinged because of AI, right? Is it going to, is it going to be hurt by AI like the CRM and the ERPs and all that stuff? So how do you see, or maybe you haven't yet, these, these large software platforms interacting with AI and how do you see AI helping or hurting?

Rose LaRocca-Fisch [00:22:10]:
Oh my gosh, I've seen it. They are absolutely incorporating AI, right? So what I've, what I've seen is a lot of system upgrades happening very quickly, building the, changing the foundation of these systems so that they're AI ready, right? And then, then you see the quarterly updates or the system updates that are happening with more AI features like in an HCM system. I mean, everyone knows this in the ATS systems, right? AI is crazy in ATS right now. Not necessarily in a good way. So we could have a whole other podcast on ATS systems and AI and HR. But you know, systems like Oracle or SAP or even NetSuite, they're building in the, the AI, into the, back into the infrastructure so that you have the capability to use AI. I see it in financial systems where AI is being used, incorporated into these bigger systems, being used to help your financial close your financial analysis. So things that we'd be doing on spreadsheets are now being done by AI, totally making the, the accounting manager's job completely different, right? Change the role.

Rose LaRocca-Fisch [00:23:21]:
It's now about, okay, now let me spend most of my time analyzing what the system has already put together for me instead of spending most of my time putting it together. It's in FP and A systems, right? With budgeting and forecasting, being able to do modeling of different scenarios. It's all being built in, in manufacturing, it's in being able to anticipate yields, right? So in biotech and cell manufacturing, so I was in cell and gene manufacturing specifically, most recently, it's being able to gauge what the yields are going to be. So on day 12, you know what resources you're going to need. So I see AI being embedded throughout these systems for at least the past year.

Steve Swan [00:24:02]:
Right. And the human error gets reduced.

Rose LaRocca-Fisch [00:24:04]:
It does. But the key is AI is not foolproof. Right. So you need that. Data integrity is important. You need to be focused on data integrity.

Steve Swan [00:24:13]:
Yeah. Well, you have to, right? And, and like I said, when you, when you, when I talk to and when I see and when I interact with the less experienced CIOs, right. They, they don't know how to handle that conversation. Because if they say no to their leader, if they say no to the CEO, cfo, CEO that comes and says, let's plug in AI and have IT running by Friday, they say no. They feel that they're going to lose their job. If they say yes, they know they got the job for six more months. So they figure out how to get AI running, which, you know, for the most part they probably can't because it's just not quite there. But they can do some of it, you know, they can.

Rose LaRocca-Fisch [00:24:46]:
So usually, I mean, it happened to me. I had my, my chief HR officer running into my office. What are we doing with AI? My daughter's using AI, right. I'm like, well, here's the AI strategy, right? So it kind of goes. It, it goes back to the foundation of it, Steve. Right. You have an it. I have, I've lived with it governance boards.

Rose LaRocca-Fisch [00:25:05]:
I've run it governance boards. each organization that I, that I'm at, I establish an IT governance board. That's where the CIO leads the IT governance board. But you have your key business leaders that participate in. It's typically a quarterly meeting. You're aligning on IT objectives and strategy. Exactly. So that's where this belongs.

Rose LaRocca-Fisch [00:25:25]:
AI strategy needs to be there at the governance board level so all of the leaders know what strategy we're moving forward with. We've all aligned on the strategy. Right. And then you're updating on the strategy. Now, again, quarterly. Because AI is changing so, so much. That's what I mean by how fast things are changing with AI.

Steve Swan [00:25:41]:
You could probably even have more meetings than that. Right? But quarterly, you're not going to get them together more than quarterly. Yeah, so.

Rose LaRocca-Fisch [00:25:47]:
Exactly. So that's where IT belongs. It belongs on the IT governance board, where we're all aligning the business and the IT are aligned on what we're moving forward with. Right. Whether it's an system, a quality system, an AI strategy, a data classification strategy, by the way, which a lot of companies do not, a lot of smaller biotechs do not have IS data Classification, but that goes to data governance. Right.

Steve Swan [00:26:08]:
So it was data Classic. I mean, are we talking about. So data classification, knowing where it belongs or when it leaves our organization or both of the above?

Rose LaRocca-Fisch [00:26:16]:
All of the above.

Steve Swan [00:26:17]:
Okay.

Rose LaRocca-Fisch [00:26:18]:
It's the data that's being developed, where it's being stored, the controls that you have around that data. Right. How that data leaves the organization, if it does leave the organization. Right. Into data governance. Yeah, but a lot of organizations do not have those data classification programs.

Steve Swan [00:26:35]:
I mean, yeah, I know that. I placed a guy that did. Does a lot of Azure security and such. Right. Then he got involved with DLP. Big time. DLP, I'd say roughly a 3 to 4 billion dollars organization. He couldn't get anybody to claim responsibility over the data.

Steve Swan [00:26:53]:
He went all the way up to the cfo, he said, if something happens, do you own it? And they were like, nope, not me. You know, so no.

Rose LaRocca-Fisch [00:27:00]:
Accountability is. Is a tough one. Accountability is a tough one. It's. It's joint, right? It's joint. It's with any. With all data. It's the business owns the data, but it is accountable as well as the business.

Rose LaRocca-Fisch [00:27:12]:
Right. So I. It enables. The business owns, it enables. And it's accountability by both. That's the way it needs to run. Otherwise.

Steve Swan [00:27:22]:
Yeah, you're not getting anywhere now. So away from, you know, obviously, like we talked about, big, big into transformation. Right? That's you.

Rose LaRocca-Fisch [00:27:31]:
Yep.

Steve Swan [00:27:32]:
Away from AI, or do you think that that's really where the transformation's happening now and it's going to continue to happen in our, in our biotech world for a long, long time to come?

Rose LaRocca-Fisch [00:27:42]:
I think AI is. Is it. Is it for the next few years?

Steve Swan [00:27:46]:
You think so?

Rose LaRocca-Fisch [00:27:46]:
Yeah, it's changing. So just because, look, in the past, Steve, a year and a half ago, I was not having this discussion.

Steve Swan [00:27:53]:
Absolutely not. Nope, nope. Year and a half ago it was

Rose LaRocca-Fisch [00:27:56]:
like, for technology, it's really.

Steve Swan [00:27:58]:
A year and a half ago you were doing. It was. What are we doing about it? You know?

Rose LaRocca-Fisch [00:28:02]:
Yeah, it's. And, and the organizations that have found a way to hone in on the specific AI objectives will succeed. They will. How? How does it fix my problem? What is my problem? Right. What is my problem and how is it going to help my problem Again, back to my example of our problem at that point in time was how do we enroll our patients as quick as possible so we can get through our phase two trials? That's where we should be focusing AI. You can't even begin that project until you know where the data is.

Steve Swan [00:28:34]:
Right, right. And like you said, knowing what the problem is, you got to identify our destination and where we're going. Right. Because if you start the other way around, say we need to use AI to do great stuff. What great stuff we looking to do?

Rose LaRocca-Fisch [00:28:46]:
Well, I mean, you have. Each department has its own thoughts, right? Yeah. Oh, we need to make the onboarding experience better. Oh, we need to do training better. Then you have your quality team, like, oh, I need to be able to see what manufacturing is doing or what it is doing. Right. Or then you have your internal audit team that. Forget internal audit.

Rose LaRocca-Fisch [00:29:05]:
Right. I ran internal audit for.

Steve Swan [00:29:09]:
I know you did. That's why I'm laughing at you.

Rose LaRocca-Fisch [00:29:11]:
Through a rotation. So I can laugh about internal audit, but it, it's.

Steve Swan [00:29:14]:
That's why I'm laughing. I'm laughing with you, not at you.

Rose LaRocca-Fisch [00:29:17]:
I know, I know. Talk about auditors that are not liked. But anyway.

Steve Swan [00:29:21]:
Right, right. You walk in the room, everybody. Everybody gives you one of these. It does.

Rose LaRocca-Fisch [00:29:25]:
One of these.

Steve Swan [00:29:25]:
Yes, yes. Yeah, yeah. Um.

Rose LaRocca-Fisch [00:29:27]:
Uh.

Steve Swan [00:29:28]:
Oh, she's back.

Rose LaRocca-Fisch [00:29:29]:
It's true. It's true. I much prefer transformation roles, that's for sure.

Steve Swan [00:29:33]:
Yeah.

Rose LaRocca-Fisch [00:29:33]:
Well.

Steve Swan [00:29:33]:
And like you just said, you know, I mean, I think those big transformation roles and opportunities and, and in our industry is going to come and the center of it's going to be AI. Right?

Rose LaRocca-Fisch [00:29:42]:
Yeah. And you have to move quickly. And that's the thing, especially in biotech. Like growing up in biotech has taught me one thing. If you don't move quickly, you're. You're left behind very quickly. Right. So.

Rose LaRocca-Fisch [00:29:53]:
And AI is just another component of you need to move quickly, but you need the strategy first. You need the strategy, you need the foundation. You got to get that foundation right first and then you build the strategy and you move forward.

Steve Swan [00:30:06]:
I always have one last question as I think you know that I like to hit people with, you know, I'm a music person. I like music. I think I've told you that. Love going to see live shows. My wife and I travel around, we see music and just to sort of add a personal flavor to it. Right. I always like to ask folks, you know, their favorite live band or favorite live act or favorite live concert that they've ever been to. And every once in a while, someone will tell me they, you know, I'll get something sort of off the wall, but for the most part, I've gotten a lot of the same sorts of answers.

Steve Swan [00:30:37]:
You know, bigger bands, whether it's X, Y or Z, I won't put any even names into your head, but if you had to pick one, and if you. If you're not a live music person, I respect that as well. But is there anything that you would say was your favorite over the years and forever? We could talk about. We could talk all the way back to when you were in high school, whatever, you know.

Rose LaRocca-Fisch [00:30:56]:
Well, actually it was pretty close, but. So I live on Long island in New York and I don't know who. If I say Long island to you, what singer do you think of? Do you think of anyone?

Steve Swan [00:31:08]:
Billy Joel artist?

Rose LaRocca-Fisch [00:31:09]:
Yeah, exactly. Billy Joel. You got it. So I was very fortunate in the mid-90s. So it was a while ago. I was at a Billy Joel. I was at a charity function and Billy Joel was the performer. There were maybe 200 people.

Rose LaRocca-Fisch [00:31:29]:
It was crazy. Totally unforgettable. So we didn't start the fire. I know. You know, the song was amazing. Steve, when I tell you it was the most phenomenal experience I've. I've ever had, ever. I mean, Billy Joel, upper up close and personal and not my favorite artist, but trust me, that performance was incredible.

Rose LaRocca-Fisch [00:31:53]:
Sang his. I think his set was maybe eight songs at most. It was. We didn't Start the Fire. Uptown Girl, you know, some of his more famous songs. And I think at that point, he and Christie Brinkley were divorced at that point.

Steve Swan [00:32:08]:
But makes sense because when I saw them Once in late 80s, I believe it was his birthday. It was the beginning of May. I think his birthday was beginning of May. And we were. I was at Brendan Burner at the time, which I don't know what it's called now. And before he came on stage, she came out, all the house lights went on. She said, today's Billy's birthday. It's the last show of the tour.

Steve Swan [00:32:31]:
And she said, he's going to come out and he's going to. Maybe we start something that started with a guitar like the first. And so he. He was going to come out and he was going to be down in the crouch hitting his guitar and. But it was going to be turned off. She said. And as soon as he does that, before we put the spotlights on him, we're turning on all the house lights and we need all. Whatever, 30,000.

Steve Swan [00:32:50]:
You just sing him Happy Birthday. So they were married at the time and he was.

Rose LaRocca-Fisch [00:32:54]:
What a wonderful person. Very good, very friendly, very. It was just. It was amazing. Amazing. So I would say that's my favorite concert.

Steve Swan [00:33:04]:
That's good stuff. And again, like you said, not. You weren't a huge inspiration.

Rose LaRocca-Fisch [00:33:10]:
He's not my favorite artist. No. By any stretch, but phenomenal performance. Phenomenal performance. I mean, who doesn't love Billy Joel, right?

Steve Swan [00:33:17]:
But you know every song, right? You know you do.

Rose LaRocca-Fisch [00:33:20]:
And I could repeat everything. Isn't that funny how you remember words of every song?

Steve Swan [00:33:23]:
Yeah, there was. I even forget the name of the song now. There was. Oh, the one where he does that. They whistle.

Rose LaRocca-Fisch [00:33:31]:
Yeah.

Steve Swan [00:33:32]:
For the longest time. For the longest time.

Rose LaRocca-Fisch [00:33:33]:
Yes, yes, yes, yes, yes, yes.

Steve Swan [00:33:35]:
I remember that in my. When I was in 10th grade, driving, doing my driver's head classes, that was on constant.

Rose LaRocca-Fisch [00:33:42]:
He lived up in Lloyd harbor, which is, like, on the north shore of Long Island. And it was right at. He was right at the. His house was right at the end of a causeway, right? So Lloyd harbor leads into Lloyd Neck or Covenant. And his house was right at the corner at that of the causeway. And that was, I think, Christie Brinkley. He lived there with Christie Brinkley for a short amount of time, but it was like, before her. But we would always drive by, right? And always want to try to catch a glimpse of Billy Joel and try to catch a glimpse.

Rose LaRocca-Fisch [00:34:08]:
So. And the person that I went to this benefit with did not tell me that Billy Joel was performing. So I was completely in awe. It was just.

Steve Swan [00:34:16]:
That's awesome.

Rose LaRocca-Fisch [00:34:17]:
Phenomenal. Phenomenal.

Steve Swan [00:34:18]:
We saw him also at MSG a couple years back, and my daughters, who are now 25 and 23, they were with us, and they couldn't believe their mother singing every single word of. Every single.

Rose LaRocca-Fisch [00:34:30]:
Knowing the word of. How do you. How do you not. Yeah.

Steve Swan [00:34:32]:
And in the beginning, in the middle of. Just told side note, in the middle of the concert, Piano Man's playing, right? Two guys in front of us get into a fist fight.

Rose LaRocca-Fisch [00:34:42]:
No.

Steve Swan [00:34:43]:
Swear to God. Swear to God.

Rose LaRocca-Fisch [00:34:46]:
Oh, my God.

Steve Swan [00:34:46]:
One guy. One guy told the other guy to sit down. He's like, I'm stand, dude. This is like, what, a concert?

Rose LaRocca-Fisch [00:34:51]:
Yeah. Hello.

Steve Swan [00:34:52]:
And he punches the guy, and security guard shows up. The girlfriend start going at it. My wife only in New York. We're ruining Piano Man. Like, come on. Anyway, well, awesome. Thank you very much.

Rose LaRocca-Fisch [00:35:03]:
Thank you, Steve. It was a pleasure to be here. Thank you.