Stewart Gandolf (Healthcare Success)

Hi everyone, welcome to our podcast and today I am interviewing Shalini Chander and she is Director of Product for Invisalign Software and we’ve been talking a lot about AI and our podcast and our blog on a recent webinar and we’re going to talk about it today from a different point of view and because obviously this year I think I saw you’d probably agree to me at least in my career of a year where marketing changed

I can’t think of any year that’s ever done faster. Like it’s changing just so fast. It’s crazy. on that note, we’re going to talk a lot about your career and your perspectives and product management or project management and product management.

But let’s just start off by telling our listeners a little bit about yourself and your background. why are you excited about this crazy world of AI and healthcare?

Shalini Chander

Sounds great. Yeah, so I have been, I’m currently at Invisalign. I’m a Director of Product here. And I work on a lot of the Invisalign software platforms that the dentist or orthodontists will use to be able to access providing those lines for the patients.

My career has been heavily on the product management side. But across general, I would say general health sciences. I did pharmaceutical, did some work in medical device, genomics, genetics before moving over here.

And so each role got a little bit more technically complex. So I’m pretty excited about what’s coming. In terms of technology, I wouldn’t even consider myself a super technical person.

I think it’s just more I enjoy kind of being the user of these things. I enjoy it because I think I can add that value of saying, I’m a really average user of technology.

And that viewpoint, I think, helps to shape how companies and industries should think about how they’re offering it out to their patient or customer population.

Stewart Gandolf (Healthcare Success)

Great. That totally makes sense. So we talked about your background moment ago, and I know you’ve worked in tech, innovation, What do you think has changed most from your point of view in the last two to three years in terms of AI and MedTech Health?

Shalini Chander

It’s interesting because I think AI has been around for a long time, right? so I think a lot of what people just got excited about really recently was ChatGPT came out.

There’s a whole concern of it’s now going to take our jobs and it will do everything. And I think that that concern needs to be, well, in some senses.

I mean, I’m amazed that. the Gen AI can do, right? I’m using it to plan vacations. I’m using it to help create content.

But what I think is really interesting about it is that we, and I heard a friend of mine say this really well, we have to really make a distinction between calling everything AI when some aspects of AI is just automation, right?

Versus what’s happening with some of these truly complex LLM models where they’re really taking what’s out there, public data sets, et cetera, learning from it, and then moving forward on their own.

It’s a true generative AI is actually producing content for you. I think what people need to keep in place though is this difference between automation versus true generative AI and that what it’s generating is based off of content that already exists out there.

So whichever capacity you’re using it for, whether it’s data, whether it’s for marketing collateral, whether it’s for travel planning, it’s based off of what exists.

So as people, we have the ability to decide on what doesn’t exist yet and create that feature for ourselves?

Stewart Gandolf (Healthcare Success)

That’s really, it’s funny because we talk about that a lot in terms of marketing. We’ve done podcasts with people on our team and what’s interesting is a couple of things.

First of all, we’re beginning to say AI feed off itself. In other words, looking at other AI-generated content, which is not ideal.

But two, when people ask us how to use, you know, remain relevant is you have to have original thinking.

Because if all you’re doing is spewing out what everybody else has, then by definition, it’s just, it’s already out there.

So the machines are hungry for new content, new perspectives, new points of view. And without that, it’s really easy to get lost in the fray.

So how does this, you know, you’re a product manager, how is this changing the product manager career approach? Like, how does that, what’s going on now?

Shalini Chander

As a product manager, you can kind of almost boil it very simply into this thing of, we’re really looking for what problem are we solving, right?

That’s what we’re to guide us in terms of, product manager or product owner. So we take a problem that should be solved and we figure out what technology or scope or product or program really applies to it.

In terms of how AI is changing that, the first thing that’s happening is that you’ve been automated / speed up a lot of what you’re doing, right?

Now if we think about we want to all become more data driven, right? That’s still a struggle that I think a lot of companies are trying to get to right now.

I’m not saying that they struggle to acknowledge it. But having those components ready up, can we now pull data instantaneously?

I think AI is going to be huge in this capacity, right? Have it do some of these tasks for you to start helping you pull that which already exists so that you can analyze and identify it better.

Then the next step, have it help you analyze, have it help you identify and look for those trends, pull those in front of you so that you are being able to review the information instead of just hunting for it, right?

so that’s kind of my simpler way of saying this is where we see benefits of it’s going to start helping us.

A lot of people have already started building it. There’s a lot of companies in the space that are taking the existing data, they’re helping to create that level of gen AI and analysis that can then be spun off for producers by hospitals, by health systems.

And so that’s a whole industry by itself that we see right now. There’s companies in that space. And so that’s going to be amazing.

Then I look at maybe where I work, we still have a journey to go there in terms of making sure that the workflow is set for everyone.

Making sure that the data permissions are set in place. There’s a lot of discussion around what needs to be done there to make it work for everyone.

so I think that there’s still a long way to go in terms of let’s make sure that everyone’s trained on how to use it.

Let’s make sure people are aware of all the opportunities on how to use it. I still have learning that I need to do, but I’m excited to be able to do it and have this make more room for that creation, for the creativity, for the brainstorming of what can we do.

Now that we have the information, we have the analysis and the data, what can we do with it, right?

And what gaps do the uncovering that we can then go plug?

Stewart Gandolf (Healthcare Success)

That’s great. And yeah, we’re all learning really quickly. you know, it’s funny you mentioned before AI has been around quite a while now.

It’s just the large language models are changing it, and we’re just more aware of it as consumers of what the opportunity are because of that variation of it.

So as a product leader, like, what does it take to actually deliver AI-powered value in healthcare? Like, how does that actually work?

Shalini Chander

This is where we need to step back and say the first thing to deliver a value is the product, right?

It doesn’t necessarily have to be shove AI into everything. Let’s first focus on over delivering a value product altogether.

I do think that this needs some level of careful evaluation. AI by itself, it doesn’t have to always be absolute right answer for anything and everything.

I do remember back to previous tech trends. Let’s use.com. As an example when Dot com was a 1st burgeoning industry, everyone started advertising everything they did as a dot com. When Facebook became really big companies started migrating all their sales and marketing from their websites, saying, Come, visit us on our Facebook page. Now it’s come, visit us, interact with our Instagram stories and reels, or interact with us on snap, like tag us in our Snapchat or Instagramor TikToks and this is an evolution of that same. Right? Everyone is. You’re starting to see companies that are dot ai, you’re starting to see them. Say, we use AI for everythingif I’m a patient. And this, I think, is where we need to break this down a little bit.I think the concept of new technology across the board is always really interesting to talk about from an internal development perspective. Great to talk about with your investor community. If I’m a patient.I’m actually maybe still concerned about the robots taking over the world!What is this going to do for me that benefits me as a patient in the long run? If I have something that needs treatment. How does this help me? Because unless it’s a patient, I see it coming at me faster, or I get healthier faster, or it’s cheaper, there’s no real benefit for me. So that messaging has to make sense. I work at Invisalign. So, for example.if we’re going to start advertising to doctors and patients that AI is a component of what we do. I think a relevant question from patients is, well, what does that mean like? Why, why is that better? We have to be able to answer at a patient level. Why, it’s better for us to be able to go in and defend that messaging.

Stewart Gandolf (Healthcare Success)

So, it’s interesting. I just did an interview with my friend Aaron Clifford from Press Danny about this very topic.

And it showed, their research shows about a third of patients are just worried and not comfortable. So, which is actually better than I thought it would be.

So, it’ll be really interesting to see as this becomes more real to people. Like for example, My wife and I both have been a doctor appointment and they’re asking, the doctors are asking us, you know, is it okay if we use an AI transcriber?

And we’re like, of course. And my last doctor goes, oh, thank God. So it’s already becoming part of the patient’s day to day life.

So I’m guessing, we’ll have to see if you agree, but I’m guessing we’re going to see people getting more comfortable as they know.

There’s always in any population, as the innovators, the early majority, late majority, and laggards. So there’ll probably become that, you know will never really fully adopt, but it will be a really interesting marketing challenge to sort of watch that continuum as people get more and more comfortable with marketing.

So, you know, on that note, then, you know, what have you seen in terms of some of the challenges, if you to expand upon either for clinicians or patients with or without AI?

Shalini Chander

So I think it comes back to the same concept, right? So trust and adoption, so the adoption, you want to trust your doctors.

As a clinician, I want to trust the product. Trust is not just an emotional sense, right? It’s also now to fit things like, do I trust that this fits my mentality of how I lean into services to offer to my patients?

Do I trust that this works with my workflow without me constantly having to, as a doctor, change my workflow, change my systems?

For patients that trust and safety needs to come into clarity in that trusted relationship with their healthcare provider, but it’s also safety and it’s security of my information and data.

Now, let’s think about maybe something like a Fitbit or an Apple Watch, right? There’s gotta be behavioral design that encourages use, right?

It’s gotta be easy to use as well. Now, as a patient, if now we’re in a place where I have some sort of a wearable and the data that’s being generated from here is going to my doctor, that’s one level of trust, okay?

My information is flowing to my doctor, to my healthcare system. Now, the question becomes, can it be? technologies, can AI start making recommendations to my doctor for me?

I trust that it’s making the right recommendations, that it’s reading the right information, it’s accounting for my lifestyle, and that the patient, we need to know that that’s either built in place or that my doctor knows that the technology isn’t accurate if there is an AI health destination, etc, that my doctor knows to look out for it.

And so this is where the product that we involve, the technology that we put out there, it needs to reduce effort instead of adding layers of double checks on because nervous that it’s not accurate, right?

so that level of trust in the safety is a challenge that we have to account for.

Stewart Gandolf (Healthcare Success)

So it’s interesting, I to ask a corollary to that because, you know, back earlier in my career, I worked with hundreds of dentists over the years, and I found if I were to break it down, it’s still true, that some dentists are certain percentage, I don’t know, 20, 25%, we’re just always interested in the latest and greatest, like they just love

new stuff. And so they’re their mindset, whether they’re a specialist or orthodontist or a general dentist.

So you have that dynamic. And then you also have, you know, sort of generationally. So usually doctors, as they get older, like a lot of them are like, I’m too old for all that stuff.

I’ll just do the stuff I’ve always done. But are you guys seeing, and where younger doctors like cool, what’s new?

Are you guys seeing that in terms of either any kind of segmentation in terms of the, you know, adaptation or resistance, or is it kind of all over the board, like I just described in terms of AI.

Shalini Chander

I think it’s definitely like you can predict it from what you described, right? There’s going to be some generational trends that relate to that.

Maybe people who are closer to retirement have an established practice, more so than a practice, it’s an established workflow that they’re used to, right?

They have a system that works well for them. People who are maybe freshly graduating from school, as an MC, just starting off in their career, probably more interested in picking up new

technologies, new behaviors, new workflows, and running with it. What we find that’s interesting is we get a lot of adoption from one sector that I would have also thought, wouldn’t have thought as much about as being on the early adopter side, which is the people who are maybe later in their career, not late, but like they have some maturity in their career, let’s say five to eight years, right?

So if five to eight years, you’re a little more of an expert, you’ve built a good base, you’ve established a practice and a system and a workflow that works to you.

But you’re now maybe in a position to buy your own practice and basically go off and say, I’m going to really self-entrepreneur, self-motivate, I’m going to be the decision maker now.

And this is a huge area where people are kind of they’ll change the approach and say, I want to start adopting things that make me more efficient, and that add benefit to my workflow.

This kind of goes back to that trust angle. In order for them to make that decision of, I want to add tools to my workflow that I think are great, that could benefit me.

I got to trust those tools as well, right? And so this is me. an area of I can take some risk, I can add new technology, I can add technology in general, if it wasn’t in my where I started off earlier training zones, but it’s still got to be I got to know it’s not efficacy.

Stewart Gandolf (Healthcare Success)

So just as a side note on that, we for our company as an agency love using Fathom as a recording tool, but there’s risk with that.

So everything’s recorded forever more and we want to make sure that first of all, we talked about this in our internal training, you shouldn’t be saying anything wrong anyway.

But on the other hand, the power of the tool is so strong that we just have to really work to make sure that we’re using the tool wisely.

So obviously, as a device company, you guys have regulatory constraints as well. So you mentioned user trust, but how do you balance these things?

User trust, regulations, with all the promise that these things hold.

Shalini Chander

Yeah, I think realistically, regulation, regulatory constraints, legal constraints, those are design constraints, but they’re not permanent roadblocks, right? It’s really for us internally, and as a product owner, you partner really closely with clinical, with legal, and with regulatory, and you do that early, and you do that consistently and constantly.

You invest in that level of relationship transparency, and with your opinion leaders as well, right? You want to balance this excitement of what are these cool things that we could do, and what products that you get, versus how can we both explain it and defend it, right?

From a clinical perspective, a legal perspective, a regulatory perspective, so you want to make sure that you have this love, trust, internally, that you have good documentation around it, and that you’ve got controlled rollouts, right?

So anything that we want to roll out from a software update perspective, whether it’s around how do you submit a prescription to how do you monitor what’s happening with your patients in the long term or the short term, it’s got to be done with a controlled rollout that we’ve tested, we can prove that we’ve tested it, and it’s safe and efficacious for

with doctor and for their patients.

Stewart Gandolf (Healthcare Success)

That totally makes sense. So I want to go back to a topic we touched on a moment ago, which is the confusion between automation, machine learning, LLMs, true generative AI.

Give us a sort of 30-second tutorial on what these things mean.

Shalini Chander

Sure, and this is going to be maybe my also my non-technical opinion. So I’ll try to put it in the way that I understand the best.

Automation handles repetitive tasks with rules. And so this is as thought as easy as writing formulas in itself as far as I’m concerned.

And we’ve done a lot of this. We keep having a lot of this throughout. Machine learning is finding patterns in structured data to help you learn from that.

LLMs are trained on the unstructured data and language and information. And from that, they can synthesize or generate things like human-like tasks.

So Gen AI is much broader now. It’s really opening up what we can do in conjunction with this. structured or unstructured data, and it can make recommendations, it can help you look for design and new drugs, simulating disease pathways, generate synthetic data so that you can run test cases against them, but each of these has different types of use cases, so they also come with their own level of risk, and that inside of the healthcare, dental, pharma, med device industry, it’s got different validation needs as well, right, and so each of these needs a lot of study and validation before they can be used and immediately used.

Stewart Gandolf (Healthcare Success)

So that’s great, well give us some examples of how this actually works and when it goes on.

Shalini Chander

How it works and when it doesn’t, so I think that some good on-the-market examples, I think that maybe like some of the two best ones, would say like something like Phillips, they’re using AI for coronary imaging, and so with that they’re improving that elastic accuracy.

You’ve got companies in the diabetes space, Dexcom’s a really great one, right, so I think we’re all familiar with continuous glucose monitors.

So DEXCOM uses AI and some of their CGM systems, and they have real-time alerts for people, right? Now, I think what would be amazing is the alert itself makes sense when, let’s say, your sugar level spikes too high, so as a patient, you start getting alert, hey, this is too high, do something about it, right?

And I think what these companies have done to is to build an alert and say, we’re starting to, you’re starting to trend too high.

Let’s maybe address your glucose levels before it spikes too high. What I think is gonna be interesting in the future is going to be, can it predict when you’re going to go too high?

So it stops your behavioral patterns altogether, or it gives you an alert for you to change your behavior altogether.

And that, I think, is gonna be that true future of what do we think AI is gonna be the benefit that patient population?

How do we get to the point where better and more technology is actually going to now cycle back and impact our behavior in a way where we can really get into preventative, right?

We’ve got, you know, examples of wearables. think a lot of the, what we saw come out with early Fitbit, Apple Watch, people were really into, oh, let me just monitor my steps.

And it was gamified a little bit where people could compete with each other. And people got really interested in monitoring their usage, right?

But the component of what is generative AI going to tell us is really going to come back into, but what is that going to cause me to do?

And how is that feedback was going to incentivize me to change my behavior? You see a lot of that with the early adopter population.

They see a basic metric like, I’m only doing 5,000 steps a day. I want to be motivated to do 10,000.

Now it’s going to be, what else is that going to incentivize me to do? Like beyond just doing more exercise.

How does this change my behavior and then put me back on a feedback loop? And I think those are still areas where there needs, there’s a lot of potential.

for what’s going to happen there, right? You’re going to be able to say, let’s not just incentivize my behavior on changing, but let’s now work with my healthcare provider on how they can monitor better, monitor in advance, be preventive, preventative monitoring as well.

React and respond to my needs and maybe start working earlier on that as well.

Stewart Gandolf (Healthcare Success)

Yeah, it’s funny with, I use my Apple Watch and do lot of things that most people don’t do in terms of a trail running on the weekends and the when I talk to my provider, it’s like sometimes I wonder like if they could only catch up with what I’m already doing, you know, it’s like there’s all this technology we have available, but it’s just not part of their workflows, not something they will consider.

So, you know, like let’s talk about, can you think of any sort of game-changing example where AI really made a big difference for the work you guys are doing or some other, you know, case study?

Shalini Chander

Yeah, I would think so there’s two areas that we’re hearing about lot and we’re working both of these. One is in virtual monitoring or virtual care AI monitoring.

One is in X-ray analytics. And across multiple industries, not just what we’re doing out of line, it’s actually really fascinating. So the concept of virtual care, you can think of it as telehealth, right? Telehealth is when I getting on a screen, you’re my doctor, and I don’t have to come to you to meet. That’s awesome by itself. I don’t have to leave the house and struggle with scheduling at a point, et cetera.

Now with virtual care, we don’t even have to be on the call at the same time, right? This is a concept with a line with anywhere where I can just, you know, use my app, right, using my app to take a picture, take some records, send it to you.

But I’m not sending it to you. The system is going to analyze it and give you an interpretation of my results.

Now, pros and cons, the system itself is not always going to be 100% accurate. So it’s going to say, maybe like we can think about it as results

And you can think of it like, let’s say, a traffic light, green, we’re pretty confident in these results. Red, we’re pretty confident that these results, that green is confident results that the patient is doing really well.

on track with their, this line, on track with their health. Red, patient seems off track, really confident in the results of their off tracks.

The doctor now needs to call the patient and maybe schedule a real life of the patient. Yellow, somewhere in the middle, we think these are the results, you’re going to need or a checkup, right?

So the pros and cons of this is that this makes sense to, I think, the health care provider of, let’s do some double checking.

If the patient is on track and we’re confident in the results, that’s great. Yellow or red, we should double check on them anyways, right?

Maybe make that appointment, come on in, and for our purposes, let’s adjust, you know, where you are from an Invisalign compliance perspective, any other provider who’s using a virtual care could take that same pattern of, let’s do a double check here.

I would say, this makes a lot of sense if the doctor can integrate this into their workflow. It sounds great, but it does have to be integrated and work well in their workflow.

I would say the challenge for the patient is how do you message back to the patient in a way that the patient understands confidence levels, sensitivity, specificity, what it means for them.

What is the action that the patient should take? The green part makes sense. You get an alert as a patient. Good job. You’re on track. Everything looks good, and so we can skip our appointment. If it’s falling into a yellow red zone, right?

And again, yellow is, we may need to double track these results, and red could be, hey, we’re pretty sure that you just need to follow up.

And whether or not this is dental or any other health aspect, right? That messaging for the patient really just has to then be broken down, not into three areas, but two, which is you’re doing great, keep doing what you’re doing, or hey, you may need a change.

We need to talk more closely about that. And that’s where you’ve got to really specific now though at the patient level and you can’t have the system giving them these alerts and you can’t have AI just giving them instructions.

I think it has to be monitored more closely to look at what is that patient specific use case?

Stewart Gandolf (Healthcare Success)

Yeah for sure I’m glad you said that because I was thinking you’re not sending red to the patient are you?

Shalini Chander

was kind of explaining like the kind of…

Stewart Gandolf (Healthcare Success)

Yeah, I get it I get it I just think that’s great because yeah the positioning is to the it’s binary to the patient you needed like I was playing with this it’s like you know either like oh congratulations you don’t need a checkup or yep you need to come in like that’s it they don’t need to know all the rest of it so that’s exciting that’s I can see knowing as an orthodontist as I do I can see where the workflow is so important right that’s a whole different thing and they need to come in do they not need to come in like how do we do that and you know systematizing that’s really key so so when you think about you know product managers or other health innovators you know like what are they, we mentioned this before, like, you know, adoption, trust, design, what are any advice on some of these things? how do we pull this all together for them?

Shalini Chander

How do we pull this together for them? So, as a product manager of the product owner, I think the best thing for us to do as a PM community is to be open to learning, right?

There’s going to be a lot of change, there’s going to be new components, we need to learn how to use it. Once we learn how to use it, this is now how to incorporate it into our workflows internally and in industry, and then it’s going to be how do we incorporate it into product.

In product, it needs to feel like this is helping you, this is a superpower and not a constant, you must always be learning how to use it.

So, that user experience of incorporating it has to be positive, right? Again, that relationship of the product manager back to the development teams, back to your key opinion leaders, your customers, health care provider community, and then back essentially to the patient.

It needs to be again, and done with trust, which is through consistency and clarity, you want to code design this with your user base.

Workflow integration is critical. It’s not optional. It’s foundational. So again, if this has got to be technology and tools that we can build in, give trust with that information, and commit to handling as partnership.

Stewart Gandolf (Healthcare Success)

Got it. And then one of things that we had talked about was, you know, what happens when AI just makes everything more complex than it is clear if they’re gone to a product and how do you handle that?

Shalini Chander

So, not even a health care example. I’ll give you an example of, I was just goofing off. I asked, I think I was asking, I said ChatGPT, make me an example of what an ancient civilization looked like, but it kept putting people in glasses.

I don’t know that people didn’t have glasses in 2000 years ago. Oh I know that. And I know that this is where, you know, it’s not perfect yet, right?

I’m sure that it will be very soon, and it’s going to account for these factors that are unsaid. I think this is where, you know, and kind of using that going back to that traffic light model, right?The green yellow red is a concept that I think is easy to explain of we’ve got really clear on this hand, really clear on this hand, maybe a middle zone that isn’t.

And I think it’s where it’s what do you do with that middle zone of information, right? How do you communicate the messaging around that?

Because that is where, you know, one thing I’ve really learned as a product manager is your product, if it gives any sort of a result, like let’s say we’re giving an Invisalign plan result, or we’re giving or you’re giving out diagnostic information around, let’s say x-ray insights.

It can’t just be here’s info and it’s very complicated. It’s got to be actionable. Your guidance has to be actionable because it’s really just got to answer the question of, but what do I do next?

what do I do with this information? so in terms of general AI models, right? It could be technically sound, but what if the recommendations it gives out are unclear? It’s really got to be a what do you do next? You’ve got to have your explainability in your features or some level of education or a system walkthrough, so you can just define this well with people, right?

If it’s related more to what data that is pulling from, it’s going define thresholds and say this is the explanation of how and why the data comes.

You can’t assume that a data model speaks for itself, you’ve got to be able to analyze it and explain it.

Stewart Gandolf (Healthcare Success)

So it’s interesting with AI, too, I think, and what you’re going to talk about the future in just a moment here, but as this evolves, when it first came out with ChatGPT, all you would hear about, because it’s the news, right? we talk about the hallucinations and the things that were crazy? And so that was the focus. And now it’s getting pretty good, but it’s not perfect.

And so what it’s interesting is over time as it gets better and better, will people, it’s likely in my opinion, that people will give up the sort of cognitive processing, and just rely on it too much which is like without this sort of skeptical overview. And it’s funny, like, last week my wife and I love eating outside. We just do. It’s like in pretty patios. We live in Southern California we asked for, like the best patios in Orange County, with a good view, and we know all the restaurants that suggest, like all wrong, doesn’t know anything, but it will get better and better. And I think it’s like the. And the idea of using AI for road thinking, and as the 1st place to go is really important, but it’ll be really interesting to see how that evolves as people get more and more reliant upon it. For example, how many people get out a map to drive someplace? People put in the nav just to go home? It’s like, so the critical thinking is going away. So, in a positive way, and maybe negative. What do you think AI powered healthcare is going to look like in 10 years as things become more standard?

Shalini Chander
So I think something that could be really interesting is well. And one comment I want to make on the product manager side, too, right like one of the tools and the things that we need to get to, and that we’ll probably all get to soon is we should just be out there building our own agents right? This is gonna help all of us to do our work, right? And it’s going to be out there to help us find that information and answer the questions around, what are these new problems that we’re facing? And how do we look for the information to support this in that same sense, translating over, I think no, in 10 years doctors are going to be using AI copilots. It’s going to support them during diagnosis during intake during general care planning. I think, where the doctor needs to rely on their expertise is going to be the doctor is the one who’s in charge. They’re going to have to sign off on stuff. The co-pilot can pull information and maybe make some guided recommendation for them. But personalized treatments have to be dynamically adjusted. And this is by real-time information and data from the system, from the patient, but also the real-time life factors of the patient. So, I think AI can get more proactive on kind of empowering health management, maybe predicting issues before they escalate like we talked about. But I think ultimately that doctor is going to have to be the owner of how can I support my patient and their outcome along with making sure that system efficiency is there in place? Right? So, it’s going to be super supportive and helpful kind of your earlier point, though, right like where people are relying on technology a lot. I think we’re going to face the same thing that we face now within the health community, which is Dr. Google, right? Everyone now Googles their symptoms, and everyone thinks that they’re dying when they go to their doctor. They’ve self-diagnosed. I think AI is just going to escalate this, because now they’re not going to go in and say I Googled my symptoms. They’re going to go in and say, I have already self-analyzed all of my trends, and AI has recommended I follow a certain course of treatment, and they’re going to come in with evidence. And how are we going to be able to tell that this is or isn’t the correct way you want to kind of like your example of a paper map.

How did you ever figure out how to get home. To begin with, you had to learn it, maybe on paper, maybe through experience, right? And I think that this is where we’re going to see that just same, you can make that same comparative distinction. How are you ever going to learn it? If some AI system’s always in charge of it. Right? I think we need to balance between learning through doing an expertise versus passing all this off to the systems right? We don’t have to drive in a horse and buggy to learn how to drive a car, but we do still have to learn how to drive with safety aspects before we pass everything off to the robotic cars of the future. Right? There’s got to be some balance of like. Where do we end, or where do we continue to have ownership versus? Where does the system support us?

Stewart Gandolf (Healthcare Success)

I agree. The judgment is the part, and judgment and sort of curation of this stuff and figuring out what matters and what doesn’t, and not everybody’s great at that, so that’ll be really interesting to see how that evolves over time. So, what role will product managers play in shaping that this future we’re talking about? And how does the product manager skillset evolve in an AI-first environment?

Shalini Chander

I think it was just yesterday the day before right and there’s we’ve seen these constant articles a has kind of replaced our jobs I think Bill Gates the of this past week.

I think him said that it’s definitely gonna replace lawyers soon, right? And this is really interesting. There’s one aspect.

think that’s in common. What roles will PMs play? What roles will I need people play? I think a huge aspect of being a product manager is when you own the product you own those relationships internally with your teams, externally as well.

You are evangelizing your product internally to other teams, right? With your development team with clinical, legal, regulatory. It’s really team partnership. You are always being told that the role of product management is to represent the voice of the customer also back internally I think it’s just as important to represent the voice of internal teams back to your customer base or to external teams, right?

What this summarizes for me is that your product manager is a storyteller And I think that storytelling is a concept that remains with us, right?

Yes, AI can tell the story, but I don’t think AI is going to, again, think of those brand new concepts to create that story, at least not today, right?

And maybe we’ll see where we all are in 10 years, but today I think this is their strength, right?

And this is where I look at even the legal profession. Yes, there’s so much information there. And, you know, tools can help you comb through the information.

But will the tools make an impassioned plea for your client or an impassioned argument? And I think this is where that aspect comes in.

As a product owner, evangelizing is my job, right? Evangelizing building relationships, convincing people, selling my ideas, socializing my ideas, of which take years to do.

And I think that that remains with us, right? I truly think of tech as support to us. It will actually change the way that we work.

It’ll change the role of what types of tasks that we have to do, though, and hopefully for the better.

Stewart Gandolf (Healthcare Success)

That makes a lot of sense. And I like the distillation about what the product manager is ultimately meant to do right to evangelize. In your case, I’m assuming it’s not just the consumer, but also the dentist, to think about things from their point of view, because it’s really easy for things to become process-driven and operational-driven, as opposed to market-driven.

So, as somebody else, or you’ve been around for a while, you’ve definitely have some excellent insight, so what would be your advice to someone else leading a healthcare product team and the wants to make an impact on patient care?

Shalini Chander

So, my biggest view of advice, I don’t think has anything to do with current or future technology. I think it’s just really saying, start with the problem, right? What is the problem to solve, which is a standard thing you hear across, product management, but in this aspect, I really think it’s start with the human problem. Like, what is it that your customer needs, and what does their customer need, right? In this case, it’s us to a healthcare provider, healthcare provider to a patient, right? Understanding both sets of challenges is the beginning of how you start thinking about, what can I do to help solve this problem for you and I think the key word there is help solve the problem for you.

I am co creating with my users and I need to have that mentality that I’m not making something to throw at them or say I’m getting to you figure out how to use it. It’s really being relentless about, I want to partner with you to make sure this is usable and that this is helps you solve some of your challenges and adds value for you not on adding five more steps to your workflow. And then ultimately your metrics or your outcomes and your successes is or isn’t the same right. We want to make sure they’re successful and make sure they have better outcomes. Whether it’s time savings, et cetera, or better patient health outcomes, but it’s really about improving and it’s improving with someone and not at them.

Stewart Gandolf (Healthcare Success)

Totally makes sense. Okay, final question. Given everything we’re talking about, how do you say grounded and focused, you know, when you’re working at this sort of cutting edge of technology and, you know, the very, very important, you know, patient’s health.

Shalini Chander

This is a great question, right, and I want to give you something that says, it’s really all about the data point being people, right, and I think that’s like really true, right.

I want to acknowledge that in under the general umbrella of healthcare, I think this is so critical as a patient of anything. I want to always be looking at features, technology tools, like I’m so excited about brand new information that comes out as a positive for the healthcare. field

And if you’ve got to take that attitude with you, when you work inside of the healthcare health tech industry, right. Every, every feature that we ship needs to be improving workflow, education outcomes. But I think looking at that, staying really close and connected to your clinician base or patient. It’s really all about keeping that mission of like, I’m delivering value and that this is meaningful outcomes that come out to you, right?

And I want to, and I say that because I acknowledge too that working from this line is fascinating, right?

so much about the oral health space. I think oral health is systemic health, right? And you need to get your patient population or doctor population to just echo that as well.

We really need to think about in this line by itself, not just for making you look pretty beautiful smiles, nice teeth.

It’s really all about saying how do we connect this back to a message of health and that health benefit to you.

So, think remembering that and remembering that we’re not here to just say, oh, really cool features, cool 3D printing, something interesting that we’re doing.

It’s more than that, right? more about saying, oh, really impacted someone’s life. We made someone happy. We made the doctor’s life easier so that they could deliver more value.

I think keeping that mission in place is what really brings it back that we’re not just inventing for the sake of inventing. We’re inventing to make people’s lives better.

Stewart Gandolf (Healthcare Success)

And I think that’s the core of your job, right, as a product manager is to be able to think about it from their point of view, which by the way is the marketing concept back I  learned in marketing one-on-one is like, you know, don’t think about how to sell something, create the product that people need, solve a need, it’s kind of at the end of the day the most important thing. So Shalini, this was great, enjoyed speaking with you. I think that AI is such an intriguing topic. You know, it’s like, when regard, it’s like everybody’s like, oh my gosh, more AI, but it’s evolving so fast, it’s just, it’s rare when something happens so fast. I think, I remember when the internet first came out and dial up modems and, you know, I remember one of my colleagues saying like, frankly, I’m not impressed, it’s like, but it’s like, it didn’t, so it took a long time for it to get really, really good. This is already, the LLMs out of the box are already really good and they’re getting better. And I think the applications and uses are a little overwhelming. Like in our own company, we have, we call it AI and innovation club monthly. And like every month, you would think this would be a dumb meeting, every month we’ll bring in new ideas on how to apply these things. So, I appreciate your time today. That was excellent. Any final thoughts for us as we wrap up here?

Shalini Chander

Well, it’s interesting that you mentioned that you’re doing this within your own company and we are actually starting to do this. So, a lot of this discussion around, we have product internally that have had components of AI in them for years now. We have products that have really cool, new components of gen AI in them. And then as a PM team, we’re actually working to educate and re-dance and parcel more on what are all the possible tools.

So even though it’s funny because even though we’re talking about this and I’m excited about it, I don’t think of the expert by any means, right? It’s really just about, I’m excited about what this can do for us. And so, I’m really eager to go out and both learn more but also help drive anything that we can do as a group to bring it back in and say, let’s all learn from each other as well.

Stewart Gandolf (Healthcare Success)

Well, I totally agree. mean, my whole, you know, I always joke. I’m like horrible at lot of things. But one couple of things I’m pretty good at and innovation has something I’ve always just been passionate about. So, for me, this is like a candy store. Like I love innovating and finding new ideas and how do you apply it.

So, which is why I invite people like you to join our podcast. So, thank you so much. I’ve enjoyed it. And we’ll see you around.

Shalini Chander

Sounds great. Thanks Stewart.

Stewart Gandolf (Healthcare Success)

Bye. Bye.