MONEY WITHOUT MATH

Embrace AI for Career Growth

• Karen Coyne, CFP®

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What if AI could be your best work ally instead of a job-stealer? 

Let's dive into the exciting world of AI, not as a threat, but as a powerful tool for personal and career growth.

Karen Coyne hosts Susan Youngblood, an AI and Human Capital advisor, as they unravel how AI reshapes our lives, especially in our workspaces. Explore how AI integrates seamlessly into your daily routines, from refining repetitive tasks to sparking creative problem-solving.

Key episode discussion points include:

  • The current role AI plays in our work lives [00:02:51]
  • Preparing for AI-driven changes in the workplace, from those feeling overwhelmed to tech enthusiasts [00:05:17]
  • Enhancing personal education with AI without needing deep technical know-how, discussed [00:05:41]
  • Embracing AI as a career accelerator rather than a threat [00:22:05]
  • And more!

Connect with Karen Coyne: 

Connect with Susan Youngblood:

About Our Guest:

Susan Youngblood is an operating advisor and technology Chief Human Resources Officer and Artificial Intelligence (AI) advisor who has launched, transformed, and acquired companies. Her combination of technical savvy and human capital management expertise positions her to advise boards and leaders on preparing for the AI-enabled workplace.

With a career spanning Fortune 50 companies, private equity-backed ventures, and startups, Susan has been a catalyst for business transformation, guiding organizations through critical inflection points, including digital transformation, M&A, global scaling, and preparing workforces for emerging technologies and AI implementation.

Susan architected the human capital strategy for the launch of the AI software firm Ascendion, where she was the Chief People Officer. Earlier, she worked with Blackstone to prepare for the $27B sale of fintech Refinitiv to LSEG and led integration planning. At IBM, she successfully managed eight global acquisitions and integrations totaling $1B Enterprise Value. Susan's strategic approach to workforce management has consistently delivered multi-million-dollar savings, evidence of her approach to driving high ROI.

Susan serves on the Board of Directors for Cornell University’s ILR School, is an advisor for an agentic AI startup, and is an angel investor. She holds a bachelor’s degree in psychology from Vassar College and a Master of Industrial and Labor Relations (MILR) degree from Cornell University, where she was also the assistant coach of the women’s tennis team.

Karen Coyne: [00:00:00] Do you want to be better with money? But dread the math. I get it. That's why this show is not focused on math. The markets meme, stocks, or even economic predictions. It is focused on how money fits into your daily life from having healthy money conversations to caring for an aging parent. I'm Karen Coyne, Certified Financial Planner, professional, and your host of Money Without Math.

Join us for conversations that are practical, sometimes philosophical, and always fresh. Learn more about me at Raymond james.com/clarity and be sure to subscribe. Artificial intelligence or AI is already changing the way that we live and work with change happening so rapidly. You might be wondering how your own job might be affected or how to prepare.

Our guest today has led global technology teams in implementing AI and driving [00:01:00] digital transformation. In this episode today, we'll discuss where we are today with ai, where we're headed, what will look different, and how you can harness the power of AI for your own career growth. Susan Youngblood is a C-Suite and board advisor on artificial intelligence and human capital.

She's an advisor for Bessemer Venture Partners, the conference board, and several gen AI native companies, leveraging her experience as a technology chief, human resources officer. She's worked with global companies like IBM and BNY Mellon to lead AI implementation, digital transformation, manage global acquisitions, integrations and more.

And if that weren't impressive enough, she has also coached Division one Women's Tennis. Susan, welcome. Hi, Karen. Great to be here. Love it. Love your whole background. Such a unique, uh, combination of experience and, uh, so much to talk about. So I just [00:02:00] wanna get right into it today because on my drive to work, I was thinking, so I was listening to Spotify and it was my, um, the DJ kicked on and said, Karen, we noticed that you like this song.

So here's a couple songs in that same vibe. Then I was. Sending an email and I forgot to attach the email. So of course, sorry, I forgot to include the attachment. So of course I got the alert that said, Karen, do you still wanna send this? You didn't attach a file? And I'm like, oh my gosh. There's so many ways that it's already been impacting our work that we don't even realize.

Uh, so tell us a little bit about, you know, where we are today and let's start with work because I'm sure that in, in a lot of the conversations that you have. People are concerned about, how AI is going to take over work and if it will displace them from having a job. So let's start there.

Susan Youngblood: That's a great, and, and that's a great segue, Karen, because you're right, AI is already been embedded for a long time and we probably [00:03:00] didn't even know it.

When you think about Siri or Alexa or any of the things that you're, you know, just mentioned, we use it automatically and I think that's a great way to think about AI. Instead of AI taking our jobs, AI really helps or augments human skills. Um, and it's actually unlikely that AI has the ability to take over an entire job.

There are exceptions, but today, AI completes certain tasks that comprise a job, but in general, not entire jobs. Mm-hmm. So. As background, Karen, a AI is very good at things like completing repetitive tasks, performing research and data analysis, and in actually in the manufacturing and logistics space, moving physical things.

Ai, uh, enabled robots are really helping, um, in many ways. But as I mentioned earlier, jobs are made up of tasks that have to be completed to get the work done. Most people's jobs. [00:04:00] Even at very, very senior levels have some tasks that they do that can benefit from AI help. Mm-hmm. Or what they're calling augmentation.

As a result, AI will likely change how much time you spend on each task. That's required to complete your job, but it will not completely, um, fulfill an entire role, especially in more senior roles because there are many human things that AI definitely cannot do today. And I'll get to those a little bit later.

Karen Coyne: Okay. Uh. Where, where do you see people might be more insulated as opposed to less insulated? Where it could take over an entire job?

Susan Youngblood: I mean, if you are, if, if an, if a job is in a very repetitive space. Then that may be something that AI's really good at also, although there's not that many jobs today that do this, but that are specifically only [00:05:00] synthesizing and researching data.

I mean, there are elements of jobs that, that, where people do that, but that's where AI is really great. You can go out and, and, and look at lots of data and bring it together and synthesize it, right? Mm-hmm. But it's mostly, those are components of a job versus an entire job.

Karen Coyne: Mm-hmm. Right. What, so for people like me that are not super tech savvy and just feel so overwhelmed by all of this change and, and how much it's happening, even though, like you said, I mean, it's, it's been really steeped in our day-to-day lives for some time now in ways that we just haven't even recognized. But what do you recommend that people can do to prepare? Where's a good place to start? 

Susan Youngblood: And I love what you said actually, that as a consultant, most people I've spoken to feel like they're not technical and that they are fearful that they can't understand AI. But the reality is, and the good news is, is the majority of people do not need to understand the deeply technical aspects of Generative AI in [00:06:00] order to use it. Just like you pick up your phone, you don't really understand what's going on beneath the cover. Mm-hmm. But you know how to use it. You know how to make, send a text message, you know how to make a phone call. You probably can check your calendar and do a bunch of other stuff. Same thing with generative AI.

You don't need to be a deep techie to really understand what, how it can help you. What you do need to understand is what it's capable of, and that's where you need to start with your education. It's you're, and, and if you're in a company where they're providing training vets. Great. But there are many, many articles and podcasts, YouTube videos, classes that can help you understand how to use generative AI to be more productive or in your work.

Again, it's not going into what an LLM is or what an API or all these things that, you know, you hear about in the news. You're just like, I don't wanna hear this. Right? You don't need to really go there. You really just need to understand. It's just like when you got a new phone, you take it outta the box and [00:07:00] there's, you know, the tutorial on how do you use this? That's what you're doing with, with, with generative AI and ai, right? It is really around how do I use this and how do I help utilize it to make me more productive in my work?

Karen Coyne: Mm-hmm. Um,

Susan Youngblood: So when you take that perspective, I think it's a little less scary. I will suggest, the one thing I always talk to people about is the fact that AI.

Is changing so rapidly that if you're going to go look for podcasts or YouTube training or course, whatever it might be, not Coursera because that's a paid service, but if you're going to look out for something, make sure that it's less than six months old. Wow. Because since I speak regularly on AI, I'm constantly on a, you know, daily basis listening because things that I talked about three months ago are kind of outta date in many.

Circumstances wild. Yeah. Again, not to be scary, but just be conscious of where, what data you're reading and make sure that you're looking at the dates of what you're reading and what you're [00:08:00] ingesting.

Karen Coyne: Yeah. And you know, but that kind of supports my, I'm not gonna say lackadaisical attitude, but somewhat not so urgent attitude towards it 'cause I'm like, I can't possibly know everything that there is to know. And it doesn't matter because it's like a VHS, like it's gone from beta to VHS. To, you know, streaming and I, I'm trying to still learn how to use the VHS machine. Like that's,

Susan Youngblood: but you don't, that's the great part, Karen, is you don't need to know everything. Right. You really, really don't. Okay. When you have a microwave, you kind of, I mean, there's a million buttons on that microwave, but you probably press the 30-second button and maybe the aro button the most, you probably don't use a lot of it, so you all the

Karen Coyne: functionality.

Susan Youngblood: Exactly. So you, and you and your car probably has a lot of stuff in it that you have. It's there, but you, you don't need to understand all of it to drive to the store. Right.

Karen Coyne: But it's wild to me because I see, you know, people like me that I've, I've touched it, but, you know, just very gingerly to kind of see what's happening there. Then you have people that are like, what, what is this [00:09:00] thing?

How does it work? And then you have people that are using it. For everything. I mean, they are not even responding to a single email without plugging it in to a chat GPT or something. They're running their, I'm in groups where women are preparing meal plans for the week by plugging in. I don't even know what they're plugging in. I'm like, oh my goodness. They're getting workout plans, meal plans, truth, like, you know, they're using it for everything.

Susan Youngblood: So, and that's the beauty of it. So that, that you can use it for everything and, and anything. I wanna go back and just go back 'cause you said you, you talked about it being daunting and, and that's what, especially what I hear from people who are employed, they're like, how do I do this?

I have a full-time job. I may have other responsibilities at home. Like, when are you expecting me to learn this? And then, oh my goodness, I have to keep current. So it's not just a one-time deal. I have to continually stay current. Yeah. And that where people can get paralyzed. Mm-hmm. I assure you I've, you know that you don't need to spend a [00:10:00] lot of time doing this if you are commuting.

You can listen to a podcast if you are cleaning up after dinner, just, you know, you can play a YouTube. You don't have to watch it and listen to what's being covered. There are, there is so much material out there now, and you can be selective. You don't need to go into the deeply technical things about it.

Yeah, just finding a podcast or YouTube or whatever it might be that you can listen to where you start to learn the language and understand. W There's people that tell you, they're so excited to tell you on YouTube what they use it for, that it gives you all kinds of neat ideas as to where you can be using generative AI.

And yes, you can ask it. To create a recipe, you ca I was actually traveling with my family, uh, in Europe and we walked into this restaurant where we thought we had a reservation that had three floors. And I said, I am in X restaurant in, uh, Munich. I have no idea. [00:11:00] Like, do we, do we just sit down or whatever?

And it told me exactly what to do. I was floored. I didn't know it could do this, right? Mm-hmm. And it was just a little. App on my phone and I just said exactly where we were and how confused I was and it said, oh, go to the second floor. You don't need to talk to the waiter. You know, the, just sit down anywhere.

And I thought, this is pretty cool. That's wild. So I mean, again, that's a tiny little example, but you'd be surprised when you ask it in plain English. I mean, you don't, you don't need to be a prompt engineer or something special. You just ask it in plain English what, where you are, tell it as much of information as you can and it.

Gives you an answer.

Karen Coyne: Yeah. And it seems like part of it is you just have to do it. You just have to get in there and get started. And once you start doing it, then you get better at learning how to massage the requests and the the prompts. Absolutely. Yeah. It,

Susan Youngblood: it, it, I like to think about is if I were speaking to, um, somebody who's in another country or, and maybe, you know, unfamiliar with where, where I am, just think about that they're in [00:12:00] Japan or something and I have to tell them.

And tell the prompt, okay, I'm, it, it probably knows by my address, you know, uh, where I am that I'm in the United States, but I have to tell them I'm in. You know, this state, I'm, I, you know, and I give it as much context as I can, and here's who I'm speaking to, or whatever it is to tell it, give it the background. And the more background you give it, the better it can answer your question.

Karen Coyne: Mm-hmm. 

Susan Youngblood: And then if you ask it a question, it, well, you can refine it, it knows, it remembers what you asked it, and then you continually refine the question so that it gives you closer to the. You know what you're asking it.

Karen Coyne: Yes. So someone shared a screenshot recently of a conversation they were having with chat when they said, Hey, chat, you know, how are you doing?

And chat responded with something along the lines of, I'm great. And by the way, how did that, uh, anniversary surprise go that you planned for your wife and, uh, how was X, Y, Z? And I'm like, okay, that sounds like a human interaction. Mm-hmm. That doesn't [00:13:00] sound like a tech AI, that's, that's, that's more even than I thought it was capable of doing right now.

Susan Youngblood: Um, it is, I mean, it's trained on all of the interactions and the data that it reads, right? And so that it doesn't have emotion, but it's learned that that's the proper thing to do in a human interaction. So it can be, it can freak you out and think, well, how does it know all this about me? And is that, you know, but it's it when you go back.

Karen Coyne: But it was regurgitating data. I mean, it was regurgitating and input precisely. Right, right. Okay. I wanna go back to, we were talking about work, um, and the skills requirements. Uh, so, and I'm thinking about this too. You know, I have two sons. I think you have, do you have kids in college? Mm-hmm. Mm-hmm. Um, so I have one who just graduated college and is actually interested in cybersecurit,y and I have one who's going to be entering high school. Um, and when I think about the way that education has changed, the way that we work has changed. Tell me a little [00:14:00] bit about your thoughts on, you know, skills requirements in education and how that's changing.

Susan Youngblood: Wow. That's a great topic. Uh, and it's a big topic. 

Karen Coyne:  probably a whole separate podcast episode

Susan Youngblood: It's, it's, and I'll try to synthesize it when I look at, and I, and I do spend a lot of time in higher education. I'm speaking at classes, et cetera, and it's, it's really interesting to think about how education is evolving.

Both, uh, you know, at the kindergarten level all the way through higher education utilizing generative ai. It can actually create, if you give it the proper information, it can create content in ways that are specific to a particular learner. For example, if I learn better audibly and somebody else is better visually, that it can adapt.

If you tell it to how it creates content for your consumption, where it. Fails is generally in the human interaction standpoint, which is why you still absolutely need teachers to help when somebody gets [00:15:00] stuck, but if it really does, it is able to create. Personalized content, which would have been a little difficult in the past.

Sure. So when you think about that, it really is. I, again, I tend to see AI as an enabler. So if I can use a tool to learn faster or make myself more productive, I think that's a really positive thing. I, I do think that in, from an educational perspective, people involved in that area will pivot and use those tools.

To be more effective.

Karen Coyne: Mm-hmm. Okay. So it's changing the way that we learn. Yeah. 

Susan Youngblood:Uh, well it's, I think it's changing the delivery method. It may not be changing the way we learn. 'cause I know after years, you know, that I learn best by listening and then writing stuff down. But somebody else may absent out.

They have to learn by experiencing it. Right? Right. So, I'm not sure it's changing the way we learn, but it's changing the way we deliver the content that's needed to be learned.

Karen Coyne: Got [00:16:00] it. And what about the types of skills, uh, expertise that will be more or less

Susan Youngblood: valuable? So, so another great question. Um, I think that, and again, working with the, with a number of academics in this arena, we've been looking at, I've been a part of this group called the AI Alliance, and we're looking at how do we help.

Um, help employees and everybody upskill in this changing world. There's two parts. It's one is the very tactical part of how do I learn how to work alongside AI and, and if I'm in a manufacturing environment or some other environments, how do I work alongside robots? Right? That's one thing, and we can go back to that, but what's also incredibly.

Important is honing in on your uniquely human skills that, that machines cannot replicate today. AI can't do, can't make ethical [00:17:00] decisions. It just can't, it, it, it doesn't have emotional intelligence. It doesn't have empathy. It can't hold your hand, it can't read your body language so that it knows if you're in pain, it it, it's incapable of leading a team or inspiring people to follow it, right?

It's a machine, right? And people are not motivated to follow a machine, and we will always need these skills no matter what. I don't care how advanced if we have. A GI, which everybody keeps talking about. The research shows that these are gonna be the essential skills of the future because they are uniquely human and cannot be replicated by machines at this time.

Karen Coyne: Oh my gosh. There's so much that you just said. I wanna go back and like rewind and in real time and just unpack all of what you said there was so, so much. Um, but what I'm hearing is a lot of the EQ leadership

Karen Coyne: Vision.

Susan Youngblood: Yep. Ethics is a [00:18:00] big one. Ethics there are, because of the, the introduction of AI and generative AI into companies, there are lots of new jobs being created as a result of AI every day.

I mean, we talk about the, the press love to talk about the things that are negative, which is people, you know, jobs being replaced, but there are, are so many jobs being created as a result of ai. And this, the whole idea of having an AI ethicist or people who are sending AI policy in or, and, and overlooking the, the things that AI is spitting out.

It makes a lot of mistakes still. So it's not. It doesn't have the context, it doesn't have the context in a meeting to be able to, you know, understand the values and what's happening or the, maybe the values of the company or other things. So having ethical AI decision making is not, is really not possible right now.

It's the people need to be making the ethical decisions. Yeah, that [00:19:00] makes, makes sense. Yeah. And doing all of the things that are uniquely human. And those are the skills that researchers are saying are going to be the essential skills of the future. I'm not saying that you don't need to understand how to use AI or to leverage it to make yourself more productive and solve problems and use it as the amazing tool that it is. But these skills are absolutely essential.

Karen Coyne: Yeah. Yeah. We can, we can actually use AI to teach us how to use ai. That's, that's funny too.

Susan Youngblood: That is true.

Karen Coyne: Right?

Susan Youngblood: That is

Karen Coyne: true. Uh, so I'm so, so you as a mom of, you know, kids that are in college mm-hmm. And you probably have friends whose kids are in the same boat.

You know, are they asking you, Hey Susan, you know, are there. Particular classes my kids should take or what? What should they focus on while they're in this stage of their education to prepare for what the future might bring them?

Susan Youngblood: Is that something that comes up? I think a couple people have asked me that [00:20:00] question, but it's actually usually the young people that are asking that question and, and I think it really depends on what field they wanna go into.

I mean, I'm not, you know, I'm not suggesting that every single. College student take a deep, you know, uh, technically deep course on LLMs or data science. It might be helpful, but it might be overkill for depending on where you're going to go. So I'm not, I, I would say that in whatever school that you're in.

Uh, looking at, looking at the course catalog and understanding and taking advantage of whatever classes that are associated with your career paths that are available would make sense. I mean, I'm thinking many universities have, they may have an engineering school, they may have a business school. They may, you know, it depends on what you're going into as to what classes you would take, but what I tell everyone regardless of age is just start using it.

See what it can do. Why, and again, go, you can just go and do a search and if you're interested, can AI help me with this? There's generally somebody [00:21:00] who's already out there on YouTube saying, Hey, I did it. I used it to do X. Right? And it's, it's, it's exciting and inspiring and it doesn't take that long to, to get inspired with what other people have done.

Um, and to be able to see, as you start to use it in your own work and for your own tasks, seeing how it can help you, we're, we're essentially. Inherently creative people. We come up with new ideas, we have inspiration. When you see what this tool is capable of, you will find ways to apply it to your work, probably, right?

Karen Coyne: Yep. Mm-hmm.

Susan Youngblood: Chance. I mean, you don't, again, you don't have to be technical. You're the expert at what you do, and when you see what the AI can help you with, you will naturally use it as a tool to help you get to where you're going.

Karen Coyne: So that reminds me of, of kind of going back to, uh, the work, you know, conversation.

Uh, you're a big advocate of using AI as [00:22:00] a career accelerator. Mm-hmm. Right? So don't be afraid that it's gonna take your job. Use it to amplify. Absolutely. Talk to us about that. Okay.

Susan Youngblood: So. Broad sweeping statement. Anything you learn about AI has the ability to help you with your career, improving your proficiency with ai, any tool, there's so many tools, a AI-enabled tools, they will.

It will help you automate tasks, help you solve problems, creative creatively, and it saves you time. And in it enables you and I really see this as the truth. If you use AI to do what it's great at, which is right now repetitive tasks, you know, synthesizing data that frees you up to spend your time doing things where you.

It's a higher level of thinking. Right? And that's where the real breakthrough value comes from, is when you're using your creativity and your inspiration to [00:23:00] solve problems or to think of a new idea for a new product. I don't know, depending on what job you're in, right? Got it. Or better way to do something.

So taking, using AI to get rid of the stuff that you probably didn't love to do 'cause it was repetitive or time-consuming, frees you up to do higher value stuff. Yes. Yes. Right. Well,

Karen Coyne: and a lot of times, people just get so stuck in the weeds that they don't have time. Like they don't have time to be creative.

They don't have time to be bored. Absolutely. Which is often when a lot of these ideas come to the surface.

Susan Youngblood: Right. Name one person who actually loves making PowerPoints. Right? Seriously. I mean, seriously. Now there's. If there's software that does that for you, just tell it kind of the bullets and it creates beautiful charts and no longer are you spending hours agonizing over beautiful PowerPoints.

Karen Coyne: Oh my gosh. Right. That's so funny. I was just having a conversation the other day with someone about, uh, a talk I'm giving and I was like, I don't really know if I wanna use PowerPoints. And I had referenced a part of my talk is about sitting on the sofa, researching. Meal plans and workout plans, but you can do it at home on your sofa, eating gummy bears and drinking wine.

And they were like, oh, [00:24:00] that's a perfect example. Just plug that into the AI tool. It'll generate slides and you can have like a gummy bear on a sofa drinking wine. Totally

Susan Youngblood: true. It's, it's absolutely true. And again, the more you experiment with it, the less scary it is and the more you wanna en engage with it because it really is an augmentation to our abilities.

Karen Coyne: Mm-hmm. 

Susan Youngblood: And so, so going back to your, your, your question though about how do you help it accelerate your career is that, you know, I think, you know at, if you're in the workplace, if you're using AI to, to solve, like, or work on practical projects or improve the quality of your work or solve a real problem in your workplace, it not only helps you, but it helps others.

And that's very valuable to a company. If you're coming up with creative new ideas, because again, you've freed yourself up to have that creative thinking time or you know, then that is very valuable. In fact, you know, I think that employees who [00:25:00] proactively learn about AI embrace its capabilities and come up with ways to use it, will be seen as more forward-thinking and valuable.

Mm-hmm. Than employees who wait for their company to tell them what to do.

Karen Coyne: Yep, you're right. You're absolutely right. And I, I love the point that it's not just about, you know, being more efficient, it's actually about opening up, tapping that creative potential that we so often don't get to use because we're stuck in the weeds or doing these repetitive tasks that, you know, AI could do so much more quickly and efficiently for us, that's.

That's, that is one of the human skills that you talked about that, you know, maybe AI can't quite do for us yet. Um, it's creatively solve some of these problems, right?

Susan Youngblood: It can give you ideas. It's a great brainstorming partner, but it's only regurgitating what happened in the past. Yeah. And that's the reality of it.

It may help you think through some things. It may help spark an idea, but it's not, you know, [00:26:00] um, it's not replacing human creativity at this point.

Karen Coyne: Mm-hmm. Well, I know some of these things we could have whole separate podcast episodes on, uh, like on on any of these questions. We could have an entire, just 30 minutes dedicated to that.

But you've definitely given us a lot of food for thought today on, you know, how it can affect us at, at school, at work right now in the future. Uh, before we wrap, Susan, any last closing thoughts, anything you wanted to make sure you share with us before we close it up today? Yeah.

Susan Youngblood:  I think just to summarize, the future of work is not about AI replacing us, but about AI augmenting our capabilities.

It's using these powerful new tools that are coming out every day to unlock new opportunities, enhance our creativity, and solve complex problems that we thought were in the past. You know, unimaginable. While, you know, while change can be scary, I really believe and encourage everyone to see the, that the future of work is filled with possibility.[00:27:00]

Karen Coyne: So a very positive outlook, and we just, we need to dig in and roll up our sleeves, start getting comfortable. It's definitely not going anywhere, right? It's not going anywhere. It's, I mean, who would take a great tool and throw it

Susan Youngblood: out the window? Right? Right. We'll have to harness it. There will be, you know, lots of things that we need to, to, you know, to look after, you know, as it's, as it's moving forward. But absolutely, it's not going anywhere.

Karen Coyne: Yeah. All right. Well, you've done a convincing job. You've convinced me that I don't need to be afraid. I mean, I have just very lightly dabbled, uh, but not gotten, you know, even knee deep yet. So, um, thank you for the words of encouragement. Thank you for the insights, and this has been a really enjoyable conversation today.

Likewise. Thanks for having me. Thanks again for listening. Please follow us on Spotify if you're not already, so you don't miss any future episodes. We'd also love for you to rate the show while you're there. Connect with us on social search, Karen Coyne CCFP on Facebook, LinkedIn, Twitter, and [00:28:00] YouTube. If you have feedback or if we can be of service in any way, please let us know.

And now for the standard disclosures, opinions expressed are those of Karen Coyne and not those of Raymond James Financial Services or Raymond James Securities offered through Raymond James Financial Services Incorporated. Member finra. Investment advisory services offered through Raymond James Financial Services Advisors, incorporated.

Clarity Planning is not a registered broker dealer and is independent of Raymond James Financial Services. Karen Coyne Financial Advisors located at 12920 Kamar Drive, suite 2 0 2, Hagerstown, Maryland two one seven four two. Phone (301) 739-7002. Any opinions expressed by Susan Youngblood are not necessarily those of Raymond James.

Raymond James is not affiliated with nor endorses Susan Youngblood. This podcast is for [00:29:00] informational purposes only.