Welcome to Executive Edge, a video series featuring expert insights on top technology trends. In this episode, we explore how AI is transforming healthcare and human services—driving innovation, streamlining operations, and strengthening cybersecurity in an era of rapid digital change.
Amy Solomon 0:04
Oh, hey Anne Rodney.
It’s great to see both of you today.
I’m really excited to hear your thoughts about balancing innovation and cybersecurity and embracing AI for both healthcare and human service organizations.
I’m sure you’ll agree this is a hot topic and it’s top of mind, right? For most executives who I talk to on a daily basis.
Rodney Graves 0:27
Hmm.
Amy Solomon 0:35
I’ve been going to a lot of conferences both for healthcare and human service organizations, and there are at least five or six sessions, every single conference, that talk about different aspects of AI. As executives are asking, how can they create efficiencies during a time when staffing is such.
Challenge still had still is a challenge and it’s not getting any better and many of the leaders I talked to are really interested in streamlining operations, streamlining systems and they’re thinking that AI could be a potential solution to giving them better access to information, data, timely reports. So.
Anne, I’d love to, you know, start the conversation.
What are some of the most common efficiencies that?
Or both.
Health and Human services.
Services organizations today.
Anne Balduzzi 1:26
Yeah, I I break it down into a couple of different categories based on what you were recently saying.
I think operational efficiencies is a really big one and that’s kind of the low hanging fruit of implementing AI those. Those are some of the easier implementation efforts, especially if they’re, you know wrapped around you know existing platforms, things like for example, utilizing copilot, they can really help.
Each employee you know get more hours out of their day.
And also things that make you know kind of help that employee do their job as well.
So whether it’s an automated, you know, note taking system or something that is, you know, able to compile all those notes in a logical fashion that kind of gives a recap of whatever issue or you know kind of patient data that they might have been working with, but.
Other areas of AI or lots of innovations and research.
Tremendous, actually, innovations in that space.
Lots of innovations when it comes to personalized and preventative medicine and then improving diagnostics.
We’re going to see more and more medical devices that are going to bring more data to the equation and that greater amount of data is going to set us up for, you know, having allow us to do more AI in the area of predictive analytics, but all of.
That data is also going to open us up to more cyber challenges as well.
Amy Solomon 2:50
What about areas like finance and accounting and payroll? Are are you seeing applications for AI in those areas as well?
Anne Balduzzi 2:59
Absolutely, yeah.
There there is an area of business or actually an even in our personal lives that AI won’t miss.
AI is touching every element of our lives, and so every element of business in the accounting sector, you know, allowing people to do things more automated.
There’s even this year you’re going to hear more and more about agentic AI and AI agents, and those are kind of agents that can autonomously go off and do work.
And then bring that, you know work product back to you know.
Whoever’s guiding that AI that can be done completely autonomously, or it can be done as as I would recommend with a human in the loop so that as this technology evolves, we’re still monitoring it, its progress.
Amy Solomon 3:44
That’s fantastic.
You mentioned security, Rodney.
Where do you see the greatest risks when it comes to AI adoption, particularly around HIPA compliance and other aspects of security?
Rodney Graves 4:01
Great question.
And you know, depending on which day of the week, that answer could change. AI is changing so rapidly as well. As you know, any other aspect of technology. But for just as far as risk, it’s it’s the increased overall threat surface.
What are we trying to protect?
Most AI, and I’m assuming we’re talking mostly generative AI today.
Will will rely upon.
Data sharing, right?
And where are we getting this data from? And with the pillars of cybersecurity, it’s always going to be about confidentiality.
How are we protecting that data and who has access to it? Integrity.
So is this data accurate when I’m pulling in data for a School Report?
And you know, getting some of the what we call what’s termed today fake news and it doesn’t match up with the actual facts or you know the the right perspective that I’m trying to bring to that report.
Not so much damage.
Getting incorrect information for healthcare when we’re trying to speed up like a prognosis or diagnosis of a condition. And if that data is not accurate, if the integrity of the source data is not there, that’s a big risk.
And then third pillars availability.
You know, once we become dependent on something like AI or.
A.
A solution that depends on.
AI.
What happens when that goes down?
You know what happens when we are waiting or depending on speedy analysis for a cancer treatment and suddenly it’s not available anymore.
So CIA is that the acronym for that so?
Amy Solomon 5:46
So.
So thank you for that perspective.
So from a security perspective, what should executives be thinking about?
What should they do to if they’re implementing AI, you know, should they have policies and procedures?
Like what should they do to really elevate their concerns around protecting their business when they’re implementing AI solutions?
Rodney Graves 6:12
It’s getting ahead of the game, you know when when, anytime there’s a new solution or a new.
Category genre of solutions we want to be ahead of the game as far as which ones we want to use, right?
There’s a bunch of different options out there for just generative AI, so whether it’s the the chat gpt’s or the Microsoft Copilots Google Gemini, we want to make a decision on which ones we want to use.
Based on that same the pillars I spoke up earlier.
Like what are the protections in place that are available for each?
How does it match up with our organization?
Amy Solomon 6:52
Hmm.
Rodney Graves 6:52
Once we gather that information, make a decision on which systems we want to use. OK, what protections do we have available in our system to keep and protect our our organization from unauthorized sharing of data, whether it’s patient data in healthcare or proprietary data?
Or sensitive information of any type.
What protections are in place to, you know, prevent us from adding or or integrating with systems that aren’t sanctioned or allowed?
So it’s more of that first step of what do we want to do and how can we protect ourselves.
From the the unauthorized use of AI, if you will. And then I know talking and working with you previously and a lot of it comes down to just education.
Education of our our users so.
Anne Balduzzi 7:45
Yeah, TRA training is a big cornerstone to really protect organizations as we move into this fast-paced kind of world of AI, because things are always changing.
The threats are always changing.
Right now it only takes a few seconds of capturing somebody’s voice.
So that’s you’re on the telephone and you’re going. Hello. Who’s there?
How are you?
That’s enough of your voice for them to actually copy that voice and have it call one of your employees and maybe change the routing number.
On a, you know, on a vendor payment or whatever.
Might be.
So there’s a lot of new scenarios that are opening up and your average hacker, thanks to AI, is now an above average hacker.
So they keep getting more and more sophisticated and and it’s really important to to help balance the innovation with the risks. And one way in which organizations and you know companies can do that is to develop AI governance models.
Amy Solomon 8:24
Weekly.
Anne Balduzzi 8:41
And and your governance model is really kind of multifaceted.
It’s on one hand.
And it’s kind of an oversight committee, and I know the word committee is sort of, you know, kind of not another committee, but that’s actually could be a really critical committee to the future of your organization because it’s the people on that committee that will be making the.
Decisions about which AI initiatives move forward and tracking whether they’re, you know, whether they have all the right pieces of the puzzle in place to be implemented, or to be effective after they’re implemented.
And then there’s the employee policies.
That kind of rest into that, that tell the employee, you know whether they, you know, the training is mandatory which you know large language models are allowed to interact with.
Are they allowed to use synthetic data?
Maybe in certain scenarios you know, so a lots of different use cases around that, but overall you want to make sure that you’re, you know, working in a really transparent environment and you’re keeping your ethics.
As high as possible, because at the end of the day it’s all about the patient.
And giving that patient the the best care that’s possible.
Amy Solomon 9:49
Welling on the Human Services side, you’ve got clients, behavioral health organizations, disability support.
And then senior living. You’ve got the residents, aging residents. You know, it scares me to hear, you know, all the shenanigans that are going on now. And older folks tend to be more vulnerable.
To believe that the caller is real, so you know you made some really good points there, both of you.
I’m saying how can mid market healthcare or human service organizations get started using AI today?
Anne Balduzzi 10:21
I think it’s it’s kind of a good idea as a first step to do an AI assessment and that’s, you know, we all think our security or our data might be or our security and our data might be kind of, you know, really well polished and and it.
Ready to go, but unless you have an outside observer come in and it truly assess that scenario, it’s hard to really look at your baby and say, oh, it’s not ugly when somebody on the outside can give you more of an honest opinion.
And then also conducting an opportunity analysis and that kind of helps you create the matrix of AI use cases that are going to work best for your type of organization.
And every organization is different and every culture is different.
So you know, with the kinds of AI use cases that might work for one, you know organization may not work best for another, but it’s all designed to make everyone work more efficiently and kind of, you know, raise up the standards in which you’re providing care.
But also make it, you know, allow your employees to work in a more, you know, environments more pleasant for them because these tools are working for them so that they can take more time to spend with on patient care and less time on paperwork. And then it’s doing.
A vendor analysis as well, you know, kind of looking at the vendors that you’re currently interacting with, understanding what their AI, you know Rd. maps look like and at the end of the day, this is all designed to give you your own AI road map.
Rodney Graves 11:48
Yeah, I’ll chime in there. I think that what you said at the very beginning was was was great, I think and overall the readiness assessment, if you will, that would be that first step a lot of times because you know AI coming from the security side and I.
Anne Balduzzi 11:57
OK.
Rodney Graves 12:05
Talk about it as almost a bad thing.
All the time and and and being risky. But I’m also, you know, Terminator years old so.
Amy Solomon 12:08
Mm hmm.
Rodney Graves 12:15
AI to me is, you know that sentient being.
Takes over. You know the world and and and ends it for for humans anyway.
Anne Balduzzi 12:24
I’m thinking more Star Trek future.
Rodney Graves 12:24
But it.
See and and at the same time, like I embrace a lot of the aspects of what we’re calling AI now on the security side.
And maybe it’s just marketing and and terminology, but behavior analytics is a big thing where we are not looking for signatures or evidence of previous attack styles. We’re more looking for anomalous behavior across the organization.
Something that’s not allowed.
Something like me logging in from Sri Lanka to log in and evaluate systems and then an hour later logging in from Dallas, TX and AI in in certain systems with detect and call that something like impossible travel and block my access based on that not being a normal.
Human activity so.
You may already in you being an organization looking to adapt AI, but.
You know, considering the risk you may already have protections in place, maybe they’re not turned on or configured properly. You may already have a lot of the new next Gen.
Or smart solutions that are looking to detect and evaluate your baseline and and detect anomalies based on that evaluation.
So the first thing is to have that assessment and say, hey, what do we have in place to protect our data from being transferred out of the outside of the organization?
Without permission, what do we have in place to protect from an AI generated bot sending notifications outside of our organization that these vulnerabilities are available? So that assessment I think is the first step on both sides to see what is it that we want to do and what.
Do we have in place to protect us?
Amy Solomon 14:19
Those are excellent thoughts.
And I guess you know sort of bringing everything together here. I think the goal of a lot of organizations is to create efficiencies and to provide a better experience for patients, for clients, for, you know, residents and senior living communities.
So you know you’ve got on one hand, you’ve got staff efficiencies and you’ve got on the other hand creating a better customer experience. So as you really think about all of that.
Can AI really be a part of that solution for an organization to achieve those goals?
While staying safe and secure.
Anne Balduzzi 14:59
Yeah, I mean I, I I one thing that’s very popular these days for a lot of different organizations are using chat bots and chat bots have gotten increasingly sophisticated.
So it can train. You can train the chatbot you know on a lot of the, you know, specific information about your organization or what’s available. You can even use the chatbots to help with, you know training your employees.
And also providing information you know down to somebody might ask the chatbot if they’re.
You know, kind of a a member of your staff say, oh, you know how much time off do I get this year?
You know, or you know what are the rules and Reg safety regulations for using this piece of equipment. You know, those are the kinds of things that we’re using.
Amy Solomon 15:42
Thanks.
Anne Balduzzi 15:43
We’re moving from a kind of a the typical user interface that we’re used to like on our computers to actually having vocal user interfaces. And so these voice user interfaces are more, you know, they’re easier to talk to.
They’re very human sounding, by the way.
And you can, you know, in some environments it might be easier to, you know, kind of text that chatbot or, you know talk to the chatbot directly and you could even add an avatar to the chatbot.
So it can look like anybody you want it to look like.
Amy Solomon 16:12
Well, that’s fantastic.
Anne Balduzzi 16:14
Yep, and the chatbot speaks in almost every language on the planet. So that’s an added benefit to people working in, you know, different communities.
Amy Solomon 16:22
Oh, that is fantastic.
Any final thoughts for you Rodney?
Rodney Graves 16:26
I’m just chiming in on on Anne’s last thought.
Because you know, prior to the last time I heard her speak about it, I was always against chat bots.
Because you know, it’s one of those repositories that could suffer from what we call data poisoning, where the information that is injected into the chatbot repository is malicious and you know incorrect. So.
Something like a chatbot for finding the right.
Part for refrigerated replacement. Again, if it’s incorrect, it can cause some inconvenience.
Something like the wrong prognosis for someone with a certain stage of of cancer or or some type of medical situation is going to hit a lot harder.
So it’s one of those places where I was, you know, apprehensive just based on the risk.
Like I said, I heard Anne’s last presentation.
On some of the benefits there and improvements. So she’s she’s bringing me over to what I still call the dark side, but it’s probably the light side in reality.
But yeah, just this again.
With everything that we do as far as technology and moving forward, there’s always going to be a certain amount of risk introduced. I’d just like to say the last thought that it’s the same as my first thought, always prepare in advance.
Limit your scope as far as adoption in the beginning and you know, do a lot of test runs prior to.
Make sure that when it fits the organization but two it it. It protects the organization as well so.
Amy Solomon 18:10
Well, this has been such an insightful conversation.
I know I’ve learned a lot today. Where you, Anne?
Anne Balduzzi 18:18
I.
I think you know, go out. Go ahead.
You know, don’t be fearful of this technology, you know, go ahead and experiment with it.
It’s happening regardless of whether you know you want it to or not.
It’s the. It’s a moving freight train.
Right now it’s it’s actually growing at an exponential pace.
So things are be prepared for a lot of change, a lot of fast change.
And just, you know, if things aren’t working, if you pilot these, you know, early solutions.
Give them a try.
Start to get your team.
Kind of, you know, more educated in the area of AI and that’s gonna protect your organization as well. When you get that training in place, whether it’s a cyber training and by the way, those cyber attacks might be not come to your organization, they might come to a.
Vendor organization and that could still impact you.
So you’ve got to train a lot of training and then if if you’re, you know, beyond the training when you’re piloting these, you know, kind of new projects and new opportunities, if it’s not working, fail fast, you know.
Rodney Graves 19:04
Exactly.
Anne Balduzzi 19:16
Go ahead and put it on the back burner and try something new because eventually you want to get to the solutions that are really gonna work for your organization.
Amy Solomon 19:26
Again, this has been so insightful.
I really appreciate your both providing the information about today because I know that this is something that so many executives are looking into, but they’re just not sure how to get started.
So you both have provided great suggestions and advice and just wanted to say thanks for tuning in to the Executive Edge episode today about balancing innovation and cybersecurity for both healthcare and human service organizations.
And thanks again Ann and Rodney for spending some time with me today.
Rodney Graves 20:01
Thank you.
Good seeing you both.
Anne Balduzzi 20:03
Yeah. Thank you.
Amy Solomon 20:03
Yeah, you too.
Anne Balduzzi 20:05
Take care.
