Elevate with AI Innovation

Get ready for a game-changing episode of "Elevate with AI Innovation" as we dive deep into Jennifer Bradshaw's Journey with the incredible Jennifer Bradshaw from NLP Logix!

Together, we'll explore the ins and outs of AI-powered SaaS products, uncovering eye-opening insights on customization, implementation, and workforce readiness that you won't find anywhere else.

Prepare to be amazed as we navigate the complexities of data harnessing, customer experience enhancement, and balancing innovation with practicality, discovering how they're revolutionizing businesses across industries as we know it.

With Jennifer's unparalleled expertise in AI solutions, you'll be treated to exclusive stories and experiences from her groundbreaking work at NLP Logix, leaving you inspired and hungry for more.

By the end of this episode, you'll walk away with game-changing takeaways:
1. Strategies for fostering an AI-ready culture
2. Tips for measuring AI's impact and ROI
3. Advice for aspiring AI entrepreneurs

Don't miss out on this transformative journey! Tune in now, subscribe, and join the conversation. Together, let's transform businesses with the power of AI!

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Transcript

Jennifer: 00:00:05
Being willing to embrace failure with a smile on your face. These are the times when you are going to learn the most about yourself, um, things that you like, things that you don't like, maybe in the career that you think you want to pursue. It's okay if you don't like every aspect of the role that you're seeking, find out what motivates you. What you're passionate about. If you're passionate about it, it's not going to seem like a job and it should always keep you curious and wanting to constantly learn,

Jennifer: 00:00:35
but learn from your failures.

Hanh: 00:00:42
Hello, I'm Hanh Brown. Welcome to AI 50, where your data meets innovation. We harness cutting edge AI technology to develop and deploy advanced language model applications. These applications are tailored specifically for the 50 plus demographic. Our goal is to meet the unique needs and preferences of this important group. So now, picture this. You're the CEO of a mid size manufacturing company, and you've been grappling with the inefficiencies in your production process.

Hanh: 00:01:19
Despite your best efforts, you can't seem to pinpoint the root cause of the problems. Well, that's where Jennifer Bradshaw and her team at NLP Logic come in. As the director of product at this leading AI consulting firm, Jennifer has helped countless businesses harness the power of AI to transform their operations. So today, we have the pleasure of speaking with Jennifer about her journey from product development to AI consulting and how her expertise is revolutionizing industries. Thanks.

Hanh: 00:01:56
So get ready to be inspired and discover how AI can take your business to new heights. So Jennifer, welcome to the show. Hi there. Thanks for having me. Yeah, well, welcome. Thank you so much for your time. So to get things started, could you share an interesting fact or a story about yourself? That many people might not know.

Jennifer: 00:02:22
Well, maybe if you've looked at my LinkedIn profile, you might be able to tell this, but I actually didn't start out in technology at all. I went to school and got my bachelor's and master's in teaching. So I am qualified to teach, uh, grade school children and also be a reading teacher. That's my background.

Hanh: 00:02:43
Nice, nice. Okay, well, now you started out developing products at a company and then you transitioned to delivering AI power solutions as a consultant at NLP Logic. So what inspired you to make that change?

Jennifer: 00:02:59
I think the constant need to learn. I love product. I love the product mindset and building things with purpose and watching where the world is going. AI was never going to take a back seat. So I wanted to make sure that I was constantly staying up to date and working with cross functional teams. So that I'm always staying educated on the latest and greatest so that we can truly define the best solutions for our clients.

Hanh: 00:03:26
Mm hmm. That's fascinating. So it's clear that your experience in both areas has shaped your perspective in the industry. How does NLP logic ensure that each client Receive the customized solution, um, that addresses their specific pain points?

Jennifer: 00:03:48
Yeah, that's a great question. And we know that every client believes that their challenges are unique, but the reality is that most business problems share a common thread. So we listen. And we listen without solutioning. That's the very first step, but we are then able to pull from our experience. And our goal is to not reinvent a wheel. So if we have the experience in solving the problem, we are pulling from that tool chest of the past. And we're making sure that we are delivering faster and faster.

Jennifer: 00:04:19
So once you've proven the strategy and you know that these solutions work, it doesn't matter if the industry might be adjacent to the one that you're working in. Business problems happen to be business problems, so it's pretty easy for us to be able to find that common thread and common solutions to implement. Now, I will say there are times where there is the need for a custom build where we're going from the ground up. But most of the time, that's when a customer is trying to build an enterprise, you know, software as a service solution that involves the customer.

Jennifer: 00:04:51
They're unique business as well as process automation.

Hanh: 00:04:56
That's very true. And we talked a little bit before our event is that I can't imagine any aspect of, um, industries or any aspect of your personal and my personal life that is untouched by AI, right? It's infiltrating in all regards. And I actually, we've all experienced AI throughout life over the last 10 plus years, but it's always been in the background. For example, search. We've all searched on Google. Nowadays, maybe it's not so Google. It could be perplexity.

Hanh: 00:05:25
And we've all, um, also have shopped and all those recommendations, right? So it's always been in the background, but nowadays it's right next to you. It's your co pilot. It's your assistant that is truly personalized. Uh, if you know how to set things up and, and, you know, with all the advancement and the speed of change over the last weeks and months with GPT 4. 0, I feel like, wow, you know, multimodal. text, audio, and speech. It's, it's changing. And I know it's slowly, um, deploying

Hanh: 00:05:59
that, but when it's here, especially audible, that's going to help so many folks like for myself, like folks, um, the, the demographic that I'm most close to is folks, let's say with visual impairment, with audible, uh, impairment, or even that may not know how to type or don't type, type well and so forth. So I think that's awesome. So, um, so now. It's, it's clear that understanding the, um, the client's unique challenges is a top priority for the team and that you try to, uh, keep that process in place or standardize as much as possible.

Hanh: 00:06:42
Make sense? Because I think AI allows you to do that. So now, um, in doing so, how do you build strong relationships with your clients? To navigate the complexities of AI implementation because I think people are at different levels of understanding and adaptation, right? Um, not everybody's in the same place. We got people that are still hesitant, fearful and people like you and myself. Who are fully engaged. So how do you address that?

Jennifer: 00:07:16
Well, I mentioned before listening and listening without solutioning. It's really, really important to establish the relationship with the client and to establish the trusting relationship. And my actual teaching background. This is where it's helpful because through every conversation we are educators for our clients. Our job is to demystify AI. We don't want them thinking that it's just this magic wand that you can wave. It will solve any problem. And that comes with being very

Jennifer: 00:07:44
transparent with your communication. So I think with that combination of being an active listener, restating what you hear to make sure that you're taking any assumptions off the table. And then educating it as you go along, don't allow the clients to make their assumptions on what a solution may or may not bring them. You have to have the open and transparent conversations. That means being honest about the limitations that the solutions might bring. So level setting the expectations during

Jennifer: 00:08:12
the education is an absolute must. And I think for us, NLP Logix. Can say we have very strong ties to our customers and we ensure that our open communication goes both ways. We're accepting the feedback from them. If they don't happen to like what we might be telling them, then we truly are working together to get them on the right track and achieve the goals that they really ultimately want to achieve.

Hanh: 00:08:42
Mm hmm. Mm hmm. Cause I think the end of the day, it's about, um, enhancing their businesses, whether it's in terms of. Um, process, uh, workflows or getting more clients for your business, uh, for your clients, for instance, it's, it's about growing and what better time to do that right now. So can you share a success story where your AI solution significantly enhanced the client's operational efficiency?

Jennifer: 00:09:14
I would love to. Thank you for asking. Um, we have a healthcare company that hires highly skilled professionals to review cases and charts. And previously it would take one of these professionals about 45 minutes to review a chart. And now once we deployed our RPA solution, that time went from 45 minutes to just about 25 minutes. So they've been able to scale their business substantially because of the gains in the process. But that we also had another

Jennifer: 00:09:46
medical billing client. They were about they were producing about 25 to 30 different claims a day. And that went up to about 75 after we deployed the solution. So everything that we have done from an operational efficiency standpoint has really allowed our customers to expand their business.

Hanh: 00:10:07
Hmm. Awesome. Congrats. So it's not just speed. It's about accuracy. It's about, uh, growing their business with more clients, like we would discuss. So those are solutions that I tell you nowadays, it's very possible to be exponential. So, um, all right now. So what are, um, the most common challenges, uh, businesses face when integrating AI and how do you help them overcome these obstacles?

Jennifer: 00:10:40
I love that question. Um, I think mostly knowing where to start. It is seemingly Mount Everest that they're trying to climb and they aren't sure necessarily if they should sprint right out of the gate or if they should walk and start to get the landscape in the lay of the land. So it's really important for us when we're establishing relationships with customers to understand what is the North Star. So that we can try to help remove those hurdles and overcome any of the, uh, um, stigma when it comes to adopting a I. So we want to make sure that

Jennifer: 00:11:15
we're having the crawl, walk, run conversation and all in alignment to what their strategic objectives are. So if you take the a I conversation off the table, just have a business objectives conversation to start. It's always disarming for the clients to understand, okay, this is just about enhancing our business. We typically want to make money or save money. Those are the two main buckets, right? And make people happier, have a better onboarding experience and make our humans more effective at their jobs.

Jennifer: 00:11:49
Um, so when we give the clients that North star, which is just their business objectives, then when we start talking about the pain points and we start talking about the opportunities that make sense for AI to solve, then we can start showcasing them. Hey, this is some low hanging fruit. You might be able to automate a particular process within your organization and free up 20 to 25 people from having to do a mundane task. Then we can start to showcase the advantages of achieving their goals. With augmenting humans with Ai.

Jennifer: 00:12:26
So it really helps, I think, reduce those hurdles because you're laying a foundation that they can crawl and then they can walk. And then they eventually, once they're walking, they definitely want to sprint to that finish line and use all the really cool technology to help grow their business. But we put that path that plan in place a road map, if you will. And that's been working quite well, starting from the basic conversation of their business objectives.

Hanh: 00:12:54
That's awesome. You know, it makes sense because you, you have to, the, the, the business owner needs to know what are their goals for the year? What are they wanting to achieve? And then along the way, what is your workflow? How do you plan to achieve that? And then as you uncover in the conversation, Uh, this is how I do it, and here, potentially, here's a roadblock that I would love to remove. And then you explore what AI, uh, opportunities to integrate, uh, because

Hanh: 00:13:24
AI is not for everything, right? Um, it's not, but it's a lot. And when you hone it in properly, I'll tell you, it exponentially can save you, like you say, a You know, from hours maybe to, you know, like one or two as opposed to 10, let's say, um, so yeah, I think it's great. I think it's great to, um, walk on that journey with the business owner and encourage them along the way. And my, my recommendation is I start small, like once you identify your pain points, prioritize what's important for you, top one or two or three, start with

Hanh: 00:14:01
something that that's doable and it's small so that you can gain confidence.

Jennifer: 00:14:05
Exactly.

Hanh: 00:14:06
Yeah.

Jennifer: 00:14:07
It helps build and establish trust within solutions as well. When you see success with that smaller solution.

Hanh: 00:14:16
Right, right. I agree. So now, how do you ensure that your AI solutions are developed and implemented in an ethical and responsible manner?

Jennifer: 00:14:32
Everything has to be explainable and transparent. So we have extremely open communication with our clients and we are consistently monitoring all of the models that we're deploying before we put it in to production. When we're testing, when we're training, we're constantly reporting out what our findings are where we may have made adjustments, um, but we also have to educate. As well, because there are things that we might not be able to do. There are limitations.

Jennifer: 00:15:00
And so in order to ensure that we are being responsible, we have to educate the customer directly on what the limitations might be. And just that constant monitoring and making sure that it's, there's really a dip in performance and it's not just an outlier. So the model health. After the fact, after a solution is deployed to production is conversation that we constantly have with clients, even in the upfront build process. A lot of organizations believe, okay, we're doing things

Jennifer: 00:15:34
in a transparent manner. We're able to see the decisions that the model is making. We're able to explain it. And then they believe it stops there. Once we're in production. It's working. It's fine. We don't need to check in on it. But the model can degrade over time. Things might need to happen. We might need to retrain, or maybe we just got a batch of data that doesn't belong. So when we're educating our clients during the build, we're trying to help

Jennifer: 00:16:02
them understand that things can change. Today doesn't look like yesterday and it may not look like tomorrow. And so if data changes over time, the solution might need to change. And I think that takes a bit of education. Um, but for us, I think it is the cherry on top of how we are consistently remaining ethical and responsible with the use of AI.

Hanh: 00:16:24
That is the only way, right? Um, no, that's great. No, um, the model, like you were describing it, it evolves. It's never static because we're continuously fine tuning. And adding to the knowledge base, right? So I see that is, um, like you said, it never ends and it should not, right? And it's a, it's a, it's a process to include your client as part of their domain, um, expertise, right?

Jennifer: 00:16:50
Right.

Hanh: 00:16:50
Yeah. No, that's great. So how do you help clients prepare their workforce for the adoption of AI technologies? Those are tough questions.

Jennifer: 00:17:00
It is, it is. And we hear it quite a bit. Um, there's a lot of fear around it, and you always hear that word replace. Replace, we're going to be replaced. Um, and this is where the education comes in. So typically when we engage with a client, at first, we are offering up an AI education session. This is the demystification of ai. What are the appropriate uses for ai? What are the not so appropriate uses and also what are some of the out of the box things that already exist within

Jennifer: 00:17:30
their current technology stack, you know, microsoft copack copilot, how might that integrate into your life and make you a more effective human. So we're trying to have conversations with our clients right off the bat to show them that. You don't necessarily need to go this full blown custom build. Your employees aren't going to be replaced. Our goal is to make them more effective and help them achieve the strategic goals, elevate them, upskill them, reskill them so that they can go and

Jennifer: 00:18:04
do bigger, cooler things, and hopefully be more happier in the long run. So I think ensuring that our clients really understand AI is not meant to necessarily replace the human, but to make them more effective, get them excited, get their leadership bought in. And I think we have a much easier path forward in helping to take away that fear and anxiety around the unknown with AI.

Hanh: 00:18:31
So true. It helps you get back to the soul of your work as opposed to being tied up with it. Like I find myself get caught up in whether it's email or whether it's sorting through things and organizing. And that was the first thing I try to tackle on is how do I organize, whether it's my day or my task to give me back, you know, a couple hours, right? And I found out that these couple of hours I can actually do things that I enjoy. Yes. So that's how it has affected, you know, me personally.

Hanh: 00:19:03
So that's great. So now what excites you most about the potential of AI in transforming businesses across industries?

Jennifer: 00:19:15
The thing that I keep coming back to is the potential that it's going to unlock in humans where it's already unlocking the creativity. Time and space create a world in which people can be curious and they can consistently learn and they have that passion to do bigger and better things when we get bogged down with the mundane tasks. How excited are we to go and upskill ourselves? How excited are we to go and try to find the time to learn something new? So I believe that we're going

Jennifer: 00:19:51
to become much better humans. We're going to become smarter, and we will absolutely know what efficiency means. Not only in our body. business life, but in our personal life as well. So I'm really, really excited to see how we evolve as humans because we have become more effective. Thanks to AI solutions.

Hanh: 00:20:13
Mm hmm. I agree. Like personally, I feel like I have to become a better prompter for instance, and that's like fine tuning your output on going. And I feel like after thousands of trying, I'm actually pretty good. But what it does, it helps you become more, um, well, a better prompter and it, uh, increases your, uh, critical thinking, right? I mean, they go hand in hand. You can't be a good prompter without utilizing, uh, your critical thinking.

Hanh: 00:20:42
So all in all, at least personally, I really think it's enhanced me as a, an individual, a professional creativity and productivity in all regards. So I highly recommend learning, adapting, uh, but just like anything, you know, adapt it with enthusiasm, but with caution because I also see folks, um, misuse. I mean, it's, um, it's real and, um, so that's, that's kind of my attitude when I try to share it with folks is, um, Proceed with enthusiasm, but with caution and then look at it from your own personal life ways that you can improve your, I think the key is upskill, right?

Hanh: 00:21:24
That's a very common key right now. A common word. Definitely. That's, that's important. So let's talk about data, right? The feel of AI. That's what data is. Now, how do you help clients? Harness the power of their data to drive effective AI solutions.

Jennifer: 00:21:47
Great question. So we love talking to clients and geeking out on their data and many clients really have a great understanding of their data, but we really like to tell that untold story. So this is during that give us access. We want to check signal. We want to see what your data can tell us. They're going to always come to the table with what they believe the data is saying, but it's always awesome when we get to tell them the things that they didn't know about it because this is what's unlocking the different

Jennifer: 00:22:19
needs and potential for AI solutions. So we like to, again, go back to what are you trying to achieve and then map their data to see, can we actually achieve it in the current landscape? Okay. So there are plenty of times where we've actually needed to collect different pieces of data to make a solution more effective or more efficient for a client. And we wouldn't have known until we dug in and started analyzing the data and potentially running some assumptions through. Our experimentation and then we go back

Jennifer: 00:22:50
to the customer and we share with them exactly what we've done, why we did it. And again, trying to get that alignment to their core objectives and then telling them we might need something different, or this is a good crawl. Let's start here. And then let's start capturing this particular data element so that. We know what the walk is going to be. This is your kind of AI roadmap, if you will, by getting this new entry, new data introduced. So everything is a matter of what that data tells us the right

Jennifer: 00:23:24
solutions that we're going to pick because of what that data tells us. And it goes back to that road mapping so that we know what the data is going to get us to the ultimate objectives on their roadmap.

Hanh: 00:23:34
Mm hmm. That is so true. Do you find it that clients are amazed what data signifies or what it comes with, whether it's unstructured or structured? Um, that's, that's in my mind, that's still hard for them to grasp what all that data entail. What's your experience in that?

Jennifer: 00:23:51
Yeah, I agree. I think they believe, every client believes they have great data and they haven't. access to great data. Um, I don't think they realize sometimes the limitations that their data brings to the table and maybe it isn't as accessible and it isn't as understandable as they believed it to be just because they're able to get reports from it doesn't necessarily mean the data's giving the right information for the solutions that we're going to have to put in place. So I think there's always a little

Jennifer: 00:24:23
bit of that tension when we're trying to Re explained to the client, just what their data says and the limitations that it does have. And then I think it opens up their minds to the potential for other solutions as well. Cause it starts to, it's like Pandora's box. Once you start digging in, you are going to uncover so much. And then I think the clients start to realize, Oh, okay. You're not just in it to use cool technology and say, you've built

Jennifer: 00:24:56
these flashy solutions for us. You're actually coming to the table with a problem and you're telling us we have some limitations, and you might not be able to solve that problem. How do we move past this? What do we need to do? And that's where that, that teamwork and that collaboration and that trust that we established in the initial part of that relationship is really important to us at this point in time. Because if they trust us, they're going to believe us as we're leading down the journey of how

Jennifer: 00:25:22
their data might need to change. We have implemented data lakes for customers because their data was spread across the board and so many different systems and they did need a place where it could live structured and unstructured. And so we've had to say, we understand, we know what you want to achieve right now. But we'll go after the low hanging fruit. We might be able to do a couple of POCs, but now let's really focus on getting your data to a workable standpoint where you are set up for that big roadmap and being able to achieve your strategic goals.

Hanh: 00:25:56
I love that you mentioned data like there's no better tool than consolidating, cleansing and organizing and having all of it in one location in the cloud.

Jennifer: 00:26:07
Right.

Hanh: 00:26:07
And then the potential is great. You know, it is. Uh, we, we talk about how we have inoperable data, but it's, it's segregated. And it doesn't communicate, right? And I think that's one of the key benefits of AI is that you got to have an ecosystem, an ecosystem that speaks to each other and data like is a good start.

Jennifer: 00:26:29
It is.

Hanh: 00:26:29
Per view and fabric and so forth. So that's awesome. Now, measuring AI's impact. So what metrics, um, do you use to assess the success and ROI of your AI implementations?

Jennifer: 00:26:48
It is so important to understand current state. So we spend a lot of time understanding what does the current workflow look like? How long does it take the humans to perform the current task within the workflow today? What are the obstacles? This is really where the success criteria starts to be captured because we're understanding how they're measuring today. And then we dive into what does success look like in the future? How do you intend to measure this? And obviously we're going to be highly

Jennifer: 00:27:18
opinionated because we've, we've watched this happen time and time again. So we start throwing out the different measurements. If they're not measuring today, What we see and really it's if there's a cycle time, if there's a start in a finish to a process, we should be calculating how long it takes in the current state so that we can understand if we're deploying an AI or ML solution, we then know we can measure. A decrease in time. That should be the ultimate goal is to see that decrease in time. And it could also come down to accuracy.

Jennifer: 00:27:50
Maybe the time doesn't matter. So if we ask a customer, what do you do today? How are you measuring it? They could say by the accuracy. We can't make a mistake in the documents that we're processing. So we, it's a very important metric to track the KPIs on how frequently there might be an error within document processing. Okay, so we know current state, what can the error rate be for future state? What are you trying to get to? You're trying to get to that 100 percent

Jennifer: 00:28:18
perfection is 99.8 percent acceptable. So it really depends on how they're measuring things today and how they want to measure things tomorrow. So it could come in a variety of different measurements, but that's always one of the initial conversations that we're having, especially when we're going through that current state review.

Hanh: 00:28:40
Very true.. Measuring the impact of the ROI of AI, um, it's so important that allows you to justify the investments, right? Right. Um, because it's um, it's one of these things if you can't measure how do you know you're improving and if you're not improving, why are you paying for it? Right. Exactly. Yeah. No, it's so true. So let's talk about AI and customer experience.

Hanh: 00:29:11
So how can businesses leverage AI to enhance their customer engagement and satisfaction?

Jennifer: 00:29:18
I think a lot of it comes down to personalization. I think as humans, we like things to be tailored to us, our unique humans. So when you're shopping online, it's really nice when you get those handy dandy recommendations on products or services that you should be purchasing based off your prior purchase history. So I see things moving more in that direction as well. But think about where you could get recommendations and when you can get recommendations. It feels like AI is so

Jennifer: 00:29:44
accessible right now. And then if we talk about edge AI, having AI on your own personal device, think of the world that that's going to bring in the personalization of the contents that you can receive from different venues. And I also think of bringing information. To people when it's most necessary. So if you go to a call center, they're typically open Monday through Friday during normal working hours. When the majority of us are also at work, but think about being able to call on a Saturday on your day off, and you're still getting a very similar

Jennifer: 00:30:21
experience and getting the information that you need for your current situation. And you don't have to call during normal business hours. So on top of personalization, I think, you know, Accessing information more readily and I do see because I use chat GPT almost like a personal assistant or a virtual assistant at times. So I see AI being able to improve the customer experience. If you're moving towards more virtual assistants, you know, we see a lot of organizations who want to have that white glove service for their customers.

Jennifer: 00:30:57
And I think AI makes that. More tangible and takes what they believe to be great customer service. And it just brings it up a level because you're now going to bring that personalized virtual assistant to the table.

Hanh: 00:31:10
Mm hmm. Everything that you mentioned, those are key, uh, characteristics of enhancements from AI. So I think it's, it's awesome. You mentioned about accessibility, my gosh, 24 seven. You know? And, and not only, um, it helps you make decisions, but I, I think another component, uh, in terms of folks who are, let's say, 50 plus, 60s and 70s, it's empowerment. Oh, for sure. I always think of it as empowerment.

Hanh: 00:31:35
It's like you make better decisions when you are empowered.

Jennifer: 00:31:39
Agreed.

Hanh: 00:31:39
And, um, yeah. That's exciting. Yeah, that's great. Now, balancing innovation and practicality. So how do you strike a balance between pushing the boundaries of AI innovation? And then ensuring practical implementation solutions for your clients?

Jennifer: 00:32:02
Right. And I think that really comes down to, we have to listen. We have to listen to our clients and truly understand their needs. There are many times that clients will come to us and they will ask for a specific solution. And one of the first questions out of our mouths typically is why? And then what are you actually trying to achieve? And so trying to get to the root of the problem. Is really going to help you understand

Jennifer: 00:32:28
what the client is trying to achieve and again, taking it back to what is your organization trying to achieve strategically so that we can try to piece the story together. It's not that we don't want to take our clients word for it. We want to trust, but verify. And so while they might want to come to the table and say, we need to implement a gen AI solution, and we have to do it within 2024. Okay. Help us understand why, what are the benefits you're trying to get out of it?

Jennifer: 00:33:00
What are your company's objectives? And if we were to bring to the table a different solution that might get you there eventually, but we just see a much bigger need and we might be able to. Put a solution in place that doesn't take much time at all and then starts to build that trust within your workforce or your end users. Would we be able to propose such a solution? Nine times out of a 10, the customer is always going to come back to us and say, please tell us, tell us the path to walk down.

Jennifer: 00:33:30
We don't want to just use the shiny cool new toys because they are available. Sometimes it's pulling out the traditional tools that have worked for decades and that really helps get them on the path forward. So again, it goes back to listening and really understanding your client's needs.

Hanh: 00:33:46
And you certainly don't start with a solution or a product, right? You start with the goals, objectives, what the clients are trying to achieve for that window of time. How do they plan to achieve it? What workflows are they doing right now? What is not meeting their timeline or their goals for the year? And then you kind of carve out what's going to work best. Right. We discussed this, you know, it's not a solution. AI is not a solution to everything.

Hanh: 00:34:14
Right. And, um, but no, those conversations that you have, it's so important. It's patient. It's, uh, it's, uh, understanding their mindset coming in and understand their workflow and their goals. So, well, that's great. That's great. All right. Um, now fostering an AI ready culture. Another tough one. Yeah. Um, what advice do you have for businesses looking to create a culture that embraces

Hanh: 00:34:43
AI adaption and continuous learning?

Jennifer: 00:34:46
I think it's important to constantly promote the human and AI collaboration. How do we as humans interact with AI so that we become more effective? And I think it's taking away some of that fear. And replacing it with curiosity, and so I think people are then a little bit more accepting of what I might be able to do for their organization. If you stop talking about it from a is going to come in and completely replace this particular workflow. It's human and collaboration.

Jennifer: 00:35:22
I think that we have to consistently talk to our clients about.

Hanh: 00:35:28
That is so true. I mean, do you think the AI is more like a GPS? It kind of guides us, it gives us options, it uncovers information that perhaps we didn't know. So it's kind of like the GPS. But we're the driver, right? We steer it. We provided input, uh, data and so forth. Right. So it's, it's collaboration of the two. I don't see one replacing the other.

Jennifer: 00:35:56
I completely agree. And I think we're always reminding our, the executive level of the clients that we're dealing with, that they need to promote that from within. Yes, we're an outside consultancy and that could come with some credibility, but if the C levels are not on board and they're not promoting the human and AI collaboration throughout the organization, this is where we see we hit a little bit more friction when we're trying to operationalize AI solutions in production. So my advice definitely is ensure if you're going to embark upon this

Jennifer: 00:36:30
journey and you're going to augment. Your business objectives by implementing AI solutions, you have buy in from the top. And sometimes that means they need to be educated just like the rest of the workforce.

Hanh: 00:36:44
So true. If it doesn't start from the top, I'll tell you, uh, the folks under maybe using AI, but maybe hiding it, for example, and they're really not fully reaping. Um, all the benefits. So you're right. It starts from the top. It starts with a cultural, a paradigm shift, um, education and promoting it as a collaboration instead of a replacement. Right? Right. So no, that's great. Now, how do you foster collaboration

Hanh: 00:37:10
among your own team, um, team members and with your clients to drive success in your various AI projects?

Jennifer: 00:37:19
So, NLP Logix has a phrase, and we have it painted on our walls, we have it within our slide decks, and we share it with every client that we talk to. "Data science is a team sport", and that is not just our internal teams that we're calling a team. We are a team moving towards a common goal with our clients, so we embrace them. We pull them in there in our internal meetings. They're listening to our daily standups and our progress. They're watching us hit the bumps in the road and openly talk about

Jennifer: 00:37:52
what we're going to do to mitigate a risk within the projects and the solutions that we're implementing. So being completely transparent, I think, and that open communication gives you your camaraderie within your team. It's building that trust. Why would we have a very, what could be a private conversation to NLP logics directly in front of our customer when we know it might make them a little bit uncomfortable because if they're watching how we work. They're going to watch how we get through the tough parts.

Jennifer: 00:38:26
And if they have faith, they're going to come right along with us. They're going to be on this journey with us and we will navigate. We've done this before, hundreds of times, and we just want to make sure that everyone understands there will be bumps in the road. But if we're doing this together and we're being very transparent about it, we really can over, we can overcome anything. Just be direct.

Hanh: 00:38:48
That's so true. There'll be many difficult. Um, conversations, right? But there also will be some big rewards. So those difficult kinds of conversations, uh, will uncover so much. So that's great. Now, what advice would you give to entrepreneurs or professionals looking to build a career in AI solutions?

Jennifer: 00:39:16
I think being willing to embrace failure with a smile on your face, this is, these are the times when you are going to learn the most about yourself. Um, things that you like, things that you don't like, maybe in the career that you think you want to pursue. It's okay if you don't like every aspect of the role that you're seeking, find out what motivates you. What you're passionate about, if you're passionate about it, it's not going to seem like a job and it should always keep you curious and wanting to constantly learn, but learn from your failures.

Hanh: 00:39:49
Mm hmm. Mm hmm. So true. Well, we're at the end. Do you have anything else that you would like to share?

Jennifer: 00:39:56
Not that I can think of. We covered a lot today.

Hanh: 00:39:59
Yeah, we did. Thank you so much, uh, for sharing your insights and your passion for using AI to transform businesses. It's very inspiring. So as a director, Yeah. As a director of the product at NLP Logix, um, you're at the forefront of driving AI adoption. And you and your team deliver some real results for your clients. So congratulations. Um, your expertise is clear. You skillfully tailor AI solutions and you navigate adoption challenges.

Hanh: 00:40:29
Uh, and you foster a culture of innovation. So this is like a testament to your leadership in the field and your company as well. So we appreciate you taking the time to share your journey, vision to the audience and to the folks who's listening or watching, thanks for tuning in. We hope that you found this conversation as enlightening and thought provoking as we all did. Um, and. As we continue, uh, to push the boundaries of what's possible with AI,

Hanh: 00:40:58
let us remember that the true power lies within us, and it's in leveraging technology to create meaningful value and to elevate the human experience. So again, thank you so much for your attention. Take care.