Trevor Botkin: 0:11

And welcome back to when Leaders Connect, the Corporate Connections podcast, where we sit down with our members and talk about leadership and business, their journey and where they see the world going. My name is Trevor Botkin, I'm the National Director of Corporate Connections, canada and today I have the great pleasure of speaking with Nancy Damaris, the President of Gestion Cope, a dynamic leader in the realm of business management and operational efficiency. Nancy brings with her a wealth of experience and a track record of driving growth, fostering innovation and leading transformative change within organizations. We'll dive into her journey as a leader, explore the values that guide her and uncover the lessons she's learned along the way. I'm excited to learn how she continues to inspire positive change within her company and the broader business community and, without further ado, welcome Nancy to when Leaders Connect.

Nancy Demers: 1:02

Thank you, Trevor, for having me to where leaders connect.

Trevor Botkin: 1:05

So let's talk about it, because, despite the fact that you look not old enough for this to be true, you've been doing as a business architect for over 25 years yeah, around that but before there was even a title of business architect.

Nancy Demers: 1:24

I think back then it just would have been consultant. It was not even consultant at that point, it was just someone working in IT.

Trevor Botkin: 1:31

How did you start on this journey? What brought you to where you are today?

Nancy Demers: 1:36

I've started in IT by doing e-learning. I was in 2000, before 2000, in a journey where people were starting to understand what was e-learning and what they wanted doing things and not repeating, continuously repeating what we do, but innovating and changing the way that people work.

Trevor Botkin: 2:12

So that's how I started my journey and it kept on going that way and it I mean just thinking back 25, thinking back to 2000, and you know Y2K and all of the technology. I mean just so much has changed. I mean, we've had iPhones since what? 2008?, so 2000,. We're talking about Palm, pilots and trios and technology, blackberry, still on dial-up modems, some of us, pagers for others, and so what a huge, monumental shift in terms of technology over over this time span. And what have you seen in terms of how businesses are learning to leverage technology, to, whether it's increasing efficiency or safeguard their data, like what? What are, what are, what have you seen over the last 20, 25 odd years?

Nancy Demers: 3:44

What I can see is that people were tied to their computer before. They were tied to their server and with VPNs and way of working, and now you can work from everywhere. You can do what you need to do basically anywhere, as long as you have internet and you have a good connectivity. That's about it, and some people are working from their iPhone, ipads. Technology has grown so fast that you're not tied to a way of working. You have many ways of working, so you need to adapt to that level as well, because otherwise you're left behind.

Nancy Demers: 4:24

So that's why I'm always innovating, trying to find new solutions

Trevor Botkin: 4:26

Do you think it's a top-down approach or should it be a bottom-up approach when we talk about corporate innovation, especially for?

Nancy Demers: 4:31

the journey of the users, and that's the perspective that we have. How can we secure businesses and leave the employee all the flexibility that they need to do what they do best, because otherwise, why are we paying them? If they're tied to a method of working and only one, they cannot innovate, so they cannot make our company innovate either. So that's the philosophy on where we go to help businesses. It's neither bottom up or down to bottom. I think it's a mix of both. I think it's a center of excellence that company needs to build, to be able to understand each other and to be working together. Innovation doesn't start by working alone. Innovation starts by working with people and understanding their needs and understanding their problem. So if it's only a top to bottom or bottom to top, it doesn't match. It needs both. It needs a vision, a clear vision of where the company wants to go, where the company wants to be, what's their value. How much of your time, then, is spent trying to make sure the top knows what the bottom vision of where the company wants to?

Nancy Demers: 5:44

go where the company wants to be, what's their value and their core. How much of your time, then, is spent trying to make sure?

Trevor Botkin: 5:48

the top knows what the bottom really needs, as opposed to so many consultants. And I know you're platform agnostic, so you're not dealing with any one platform. You're able to pick and choose whatever makes the most sense for your client. But how much of your time is spent?

Nancy Demers: 6:04

trying to either deprogram business owners from what they think they need, because that's what the latest Forbes article says, versus making sure that you understand the real needs of the client, based on what the employees are either using or lacking in their day to day. Right.

Nancy Demers: 7:00

I always say there's three types of processes in businesses the process that the boss wants to have, the process that he thinks he has and the process that the employee really do. And more than often they don't know about that one and they don't know how it is on the day-to-day scale and everything. So that's where I spend a lot of my time, because owners know what they want and we know they want efficiency, innovation, differentiation and stuff like that. But employee they want to be powerful, they want to be having the right tool to do the right job. They have other concern and they want to make sure that all they do is perfect so they don't disappoint their boss or whatever. But that's one of the main thing.

Nancy Demers: 7:52

So many times they have some processes that they do that no one knows and the only way to find out is by looking over their shoulder while they work. Otherwise we cannot know it and in meetings it won't go out. They'll just say, yeah, the numbers are okay or everything's okay, but they will be working. Two or three processes on the site. I remember one day I arrived and there was a pile of documents and I would assume that a lot of your process is obviously understanding the problem and the need and balancing those two.

Nancy Demers: 8:36

But then making sure that when you implement, there's a robust training program around it. But if you don't teach them how to use it, they'll continue to use whatever tools they've been using. That's the main problem. More often than ever, employees don't trust the softwares. They don't know why. They don't understand why. So the culture of change in an enterprise is very difficult to adapt in that point, that is for sure. And they, if they, don't trust the system.

Nancy Demers: 9:24

If you don't prove to them when you implement a new system, that it can be stressfulful and that it does exactly what they need, they won't be using it. They'll keep on putting data in. But then your data? Is it the good one, the proper one, at the right place? They don't even know sometimes be happening into AI with the AI and into technology in the next couple of months, and we're in. What we see is that data is not clean, so they don't have the right data. The data is not in the right place, so we cannot leverage what the enterprise has to be able to make it more performant than just having what they have, and we cannot scale it. We need to clean it. We need to clean it, we need to validate it and make sure that it's safe and it's the proper one, and more than often they keep everything just in case, but it's no longer the good way to work, unfortunately.

Trevor Botkin: 10:24

So, if I can just unpack that, because it's a pretty profound statement to say that there's something inherently, I think historically, we've always said more data is better than less data. But you're saying that.

Nancy Demers: 10:37

Not more than less, but good data is the quality of the data that needs to be assessed and what's no longer good in a company shouldn't be available to an employee to look at or to base their opinion upon it, and that is law 25 or government law that tells you to clean up the data is one of the thing is because, first of all, there's an impact to the environment. If you're keeping a lot of data for nothing and you're not using it, it costs you. You're spending too much money. It has an environmental impact because servers cost a lot into eco-friendly world that we're in to cool down and everything. So it has an impact everywhere and people don't understand it.

Nancy Demers: 11:28

Sometimes you'll see on a file server or online version one, version two, version three, version four, revised version five, sent to the client but revised twice, and you have all those type of names in behind. That is the same document, but 20 place different. Clean it up. So we're sure that it's going to be the proper information that is going to go out. You can keep it, but in a safe place, not everywhere and not for everyone to be playing with it. If it's archive, it's archive. Archive your stuff and it will help everyone in the company in the long term.

Trevor Botkin: 12:05

Feels like you just described my OneDrive folder structure.

Nancy Demers: 12:09

Everyone's folders, everyone's OneDrive, everyone's. That's been working with IT for a long time has that problem. I was making a joke the other day with one of my colleagues here because I asked for the recipe of doing something, but I used the word recipe in English and it literally gives me a recipe that I had in my OneDrive. So clean it up.

Trevor Botkin: 12:36

Yeah, it's really fascinating. And again, you know we talked, obviously for those who weren't with us on the weekend Nancy was one of our presenters at the Canadian Leadership Summit, was talking about AI, which was a profound discussion, and I know a lot of people. It was a bit of a paradigm shift in terms of how they're looking at technology. But what I've seen myself and you're way deeper in this than I am, obviously because it's what you do, way deeper in this than I am obviously because it's what you do what would you say is the most exciting thing with AI right now, as you look forward towards the end of 2024 and into 2025?

Nancy Demers: 13:16

There's a lot of things coming for business needs, business users and employees. I would say that it's going to change the way that people are working right now, the time that they spent right now just cleaning their inbox, just knowing what they missed last week. It is a total shift of paradigm that is coming and that is what is the most important for a company to drive in, plunge into it and go in and look at it, because if they don't change that way of thinking of doing things, they won't innovate. And I think that is what's coming in the next six months is that people will realize what they need to do to be able to leverage what's coming. You know it started we're going to have everything in our glasses we don't. Even in a couple of years we won't have any computer with a mouse and a clavier. Sorry about that.

Trevor Botkin: 14:16

Keyboard A keyboard.

Nancy Demers: 14:17

Thank you, I was losing my words. It's all going to be vocal. It's all going to be. I want to do this and you'll be able to see it in your glass, and Ray-Ban and Meta had already started on that journey, and it's not going to be far ahead. So what I think is that people won't be sitting in a desk working alone. They will be working from everywhere and you won't even notice that they are.

Trevor Botkin: 14:44

They're going to be in the bubble. That to me though it it feels and I mean there's an incredible author that I've read most of his books, uh, called cory doctorow. He's canadian but he lives in the great britain some real interesting technology books and he was writing some of this stuff back in the 90s, even before. I mean, it was the first place I'd heard of an onion router and in some of you know uh, augmented reality, artificial reality, and one of his was I think it's called down and out in the magical kingdom man. It was post-apocalyptic kind of people living in disney world. But one of the things that was interesting was, um, the ability to take phone calls internally and just you, you know someone would you'd be talking to someone in the checkout cause they were answering a phone call, but it was all in there and so kind of a neural link to be able to that.

Nancy Demers: 15:37

It started already. That is started, but we won't see it this year. Maybe in five years it's going to be more expand, but in in the near future, it's the keyboard that's going to be laughed out. There's a mouse Uh, we won't see it next year, I believe into our desktop. It won't be there anymore. So it's getting there and you see all these um headphones that now you don't put them in your ears, but in your temples or in behind your ears. That's exactly where we're going. So it's not going to be even words spoken, it's going to be vibration that's going to give us the information. So that's why they've started on that journey.

Trevor Botkin: 16:15

But what are we and again, this isn't necessarily your field of expertise, but what's the risk? What are we risk losing with the speed with which technology is evolving on us? I don't mean like Terminator level of, you know, ai machines taking over, but what, what?

Nancy Demers: 16:34

what is it? It started in a certain way and I'm sorry to tell you because either models of our training the models and making the models better already. So maybe it's narrow AI that we're speaking of, but narrow AI I mean for specific needs, for a specific problem to solve, not general AI where they need to know everything. But in the narrow AI field it's already started. So it is frightening when you see that and you hear about it and you know how, what the level of the scores they're getting to phd levels and all of those stuff we're being surpassed by their intelligence. So we need to be careful onto that. I think that's something that worries me and keeping keeps me awake at night, because if the model can train their own model to be more performant, where are we going?

Trevor Botkin: 17:30

Is there? Well, let me ask it this way I don't want to scare anyone, by the way.

Trevor Botkin: 17:37

No, but I think people should be, I think people should know we should be going to this eyes wide open, wide open. And I think you know the conversations around what happened last year with open ai and kind of the the reshuffling of the board as that company pivoted from a not-for-profit structured around some more of this holistic viewpoint of it where they've gone to a for-profit model and and some of the people on the board who were kind of trying to keep open AI open.

Nancy Demers: 18:09

Which is not open at all.

Trevor Botkin: 18:11

It is not open at all and now it's part of the bigger structure of the Microsoft, the Apples, these for-profit businesses that may feel benevolent but aren't. But when we look at our children I know that you've got adult children and I have an 11 year old the world that we grew up in doesn't exist.

Nancy Demers: 18:38

Oh, no, no, no, no, not at all.

Trevor Botkin: 18:40

And, and so how do we? And I guess it's twofold. So how do we look at this from the aspect of being a parent, and how do we help our children understand technology? And then as a business owner, because, again, this is where leaders connect. But as a business owner, how do we look at it in context? And you talked about this on the weekend Our employees will use it, whether we make it available or not.

Nancy Demers: 19:03

Bring your own AI. They will bring their own AI. At the beginning of the year 2000, when you were mentioning about the phone and everything, they were bringing their own AI. At the beginning of the year 2000, when you were mentioning about the phone and everything, they were bringing their own AI, and that was the cell phone that they were bringing. Now the technology has shifted and now it's AI that they're bringing, not devices, no more, but it is AI.

Nancy Demers: 19:22

And kids at school. They need to learn how to prompt, they need to know how it works and how, and some people will say, yeah, but they won't learn. They will learn because it's another way of learning, because when it gives you an answer and you look at it and you need to make sure that the AI is correct, they will make more search on it than just grabbing the information. They will be more aware of where to look and how to look at specifics than we are. And that is one of the problem in businesses right now is people don't challenge what AI tells them. They just take it and it's not always good, because they will hallucinate If they don't have an answer. They will hallucinate when, so they will give you up and feed something that does not exist, and they will put you on a wrong path, but that is, for sure, something that you need to know and validate.

Trevor Botkin: 20:21

Because artificial intelligence doesn't have the moral. I mean it's kind of like people who factually cannot tell the truth. I mean they will make anything up, they will say anything.

Nancy Demers: 20:32

They're born to tell you something, so if they don't have an answer, they'll build one.

Trevor Botkin: 20:38

They'll make it up. They'll make it up, but it sounds like, whether it's our children or our employees, we need to do a better job at helping them understand the mechanics of problem solving not necessarily.

Nancy Demers: 20:53

And the ethic as well.

Trevor Botkin: 20:55

And ethic.

Nancy Demers: 20:56

Because there's a lot of ethical aspect that needs to be looked at. What can you do with AI? What do you want your business to be able to use as AI and in what terms do you want your business to be able to use as AI and in what terms do you want them to use them? And that's up to the business leader to put that in place the governance, what they're entitled to give to the client. How will you share your experience with the rest of the team?

Nancy Demers: 21:23

When we're talking about big businesses, they have the structure to leverage that, but when we're talking to small and medium businesses, they don't have the time and they don't know and they don't know where to look into it, and that's basically what is refraining them from adopting it and leveraging it in their businesses, because they know that they have those aspects, but how to do it and how to start that journey, they're left alone. Top EMJ Deloitte. Are big businesses that will help big businesses Too expensive for SMBs. So small and medium businesses need to be able to count on people internally suppliers. But suppliers they're there to sell licenses, sell product, to implement things that they sell, and they know of not looking over and knowing what you need. So that's why I think that consultants that are going into businesses should have that approach, even though they have a product to sell, because it's ethic from my side.

Trevor Botkin: 22:32

So that brings up a wonderful point. I think it's a great kind of segue into if in small and medium businesses is, I would say, the breadbasket of Canada, that is, the vast majority of business owners in Canada are in that small to medium, sometimes hedging on the smaller side depending on what province you're in. But where, if you could give kind of a top five, or where should a business owner start if they're looking at how can they dip their toes into technology, feeling already that maybe they're behind the eight ball on whether it's AI or on technology within their business?

Nancy Demers: 23:17

I would say the first thing they need to know is to know what they want to do with AI. Ask yourself what's your vision about AI. Is it to create a new product? Do you want to innovate, or do you want to just leverage what you have and make your employee be better, and not replace them? And for us, every business owner here, don't think that you're going to be able to replace your employee with AI. If you're a small and medium businesses, it won't happen in the short term. You will spare them time, they will gain in efficiency, but don't replace them. It's not the way to go and it's not the way of thinking, of approaching this. So that's why I'm talking about ethical way of leveraging AI in your businesses and also make sure that everyone understands what is AI and how they can use it and what they can do with it.

Nancy Demers: 24:10

So take a course to understand AI, understand what it can do and understand and talk to your employee for the Center of Excellence that I was talking about, what they see as their pain point of the day, what they don't like to do. Start by those. You know Moderna has 200 GPDs to do what they need to do every day, and that's only for the Laval here estate. So 200 ways of leveraging the capability of OpenAI and ChatGPT in their business. Openai and ChatGPT in their business, but be careful on what you allow your employee to put on open platforms. We hear a lot about Microsoft with the Bing chat enterprise and people. There's two ways of understanding this. We don't find what we ask the model and we lose our research because they don't keep your information. As of OpenAI, they keep your research and they feed their model with your research and with the document that you give them.

Nancy Demers: 25:19

So think about is there proper I'm never going to say that word a document that you need to be aware that's not going to be there and tell your employee the risk of putting information onto an AI model that is not secure and that it's not in your environment? It depends what you do with it, it depends how you want to start with it, but if you want the whole world to know what's going on with your business, put it on an open model and they'll know, they'll be able to search and they'll learn and they'll feed their model with your information. So your good way of working is not public and everybody has access to it.

Trevor Botkin: 26:01

Well, I mean again any company that has proprietary information. Obviously you want to. You want to protect that, you want to protect that. But I guess the other way to look at it is to say that the other model would be to say that ideas are less valuable than sometimes we put on them. It's execution that matters, exactly.

Nancy Demers: 26:30

The idea that you're going to be putting into it will be served for your enterprise in one way and on the other way, it will serve the collectivity. It is a good thing for some general things that's why we call it gen ai but if you have a model of working and some specific for clients for example, data and everything like samsung put their database a couple of years ago into it with all the names of their users and their email, that was a big flunk and it was. We were able to find them on the the open AI model. So that's a problem that that I'm talking about.

Trevor Botkin: 27:01

Yeah, but I and I think that's interesting and sometimes we talk about that within our own community, like, do we advertise who are our members? Because if I, if I put my members up on the web, then other organizations that maybe want to get in the same space now can target my members or can use that as profiling. And I think the one thing that people forget or they discount is the relationships, and that's something that technology to date cannot recreate or cannot leverage in the same way that you know the interpersonal relationships, and I think that's something that sometimes we forget. And you know, when we're talking to employees about, hey, we're going to make AI available to you, the first thing that sometimes they come back is saying am I teaching my replacement? Am I training?

Nancy Demers: 27:52

That's why I say you need to approach this with an ethical way and telling your employee why you're training the model. Yes, it will be trained to replace your day-to-day tasks that you don't like and you'll have more time to do more tasks that you like and that can make you evolve. And that's the way to look at things and tell your employee where you see them as well in terms of jobs. And yes, you're going to train the model for doing repetitive tasks that you don't have any value doing, you don't even like doing, so let's replace them and with what you do best and you can learn, and you can leverage and learn more and bring something new to the business. That's where you need to look at. That's why I was saying don't think about replacing your employee, but leveraging what they know and their knowledge to another level for your business.

Trevor Botkin: 28:52

Beautiful. What do you see in the short term In terms of business owners? What do you see right now? What's your prediction for the next six months in terms of?

Nancy Demers: 29:06

AI or technology. It will be the security issues for businesses that they'll need to look into, ask themselves are we doing the right thing, do we really need to do this and put their business processes up front instead of in the backlog, like we were saying? They think that they have a model, they want to have a model, but it's not what's happening in behind. Try to learn what's really happening in behind and try to look at it in another perspective, not of replacement or not, but to leverage what you all know to make it better. And that's the way to approach and the job that needs to be done for the next six months, I think for employee to secure their information, clean up what they want, make sure they know where they're going, train them, train them and retrain them, because it's so evolving and fast that what I'm telling you today, as of September we're on the 19th and I'm specifying the date because in a month it won't be the same, and before Christmas it won't be the same, and before Christmas it won't be the same.

Nancy Demers: 30:24

A lot of companies are holding their AI and we don't hear about success with AI. They don't talk about it. They don't want to talk about it because they're afraid they're going to be stolen their idea and they're going to lose their advantage, but it is working. And, yes, we hear bad things, but there's good things as well happening in that world that we don't know and that they're leveraging it and using it every day. So train people. That's your main goal for the next six months, I would say, and understand what they do very well.

Nancy Demers: 31:00

It's crazy that it's changing and moving so fast where your data is weeks Just at the beginning of the year I wouldn't have the same speech with you, I wouldn't talk the same way with you than now. And it's nine months and I've started to play with co-pilot for real in the Microsoft environment. In February we went was lunch for everyone. I was one among the first ones that had the co-pilot in my enterprise and I'm telling you I'm saving about two or three hours a day writing, scoping my meetings, sum up my tasks of the day, and it all does it for me. I don't have to worry about missing something, no more. Uh, it looks for it and it tells me, and it's not a spy, but it is a kind of a watcher for me.

Trevor Botkin: 31:59

Powerful. Well, look as first, first off it's. It's a bit overwhelming, I get that. I think everyone probably feels that way, unless they're sitting in your chair, which is I'm still overwhelmed.

Trevor Botkin: 32:14

That doesn't. This doesn't help anyone. Just fake it. Just say oh yeah, no, I'm, I've got this. Look, I will. I will make sure, for those of you listening, that you want to reach out to Nancy and connect with her. Obviously, she's comfortable in English. She's even better in French. I can attest, as I again appreciate you doing this in English with me. It's my pleasure. Heartfelt thank you, Nancy, to joining us today and for these insights on AI security and let's talk about the future of business and technology. So thank you for being here.

Nancy Demers: 32:48

Thank you for having me Trevor.

Trevor Botkin: 32:50

I appreciate that and to our listeners. Well, we've explored these powerful technologies and how they're reshaping how we do business and we didn't even get into really La Loi 25 or Law 25. We didn't get into what's happening.

Nancy Demers: 33:03

C-27 for Canada, that's coming as well.

Trevor Botkin: 33:08

It's coming for the rest of Canada. I think the EU will not be that far behind. I think they'll be revising GDPR based on what we've been doing here in Quebec. I know California is getting close to doing the same thing. Everyone's looking at what we're doing in Quebec. I know California is getting close to doing the same thing. Everyone's looking at what we're doing in Quebec. So the fact that you were here first you're government certified to be able to be delivering this and handling that from a government aspect is powerful. So I'll make sure that your website, your LinkedIn, are in the liner notes so people can follow up with you directly from that aspect.

Nancy Demers: 33:42

It will be my pleasure to follow up with them, as well, perfect, and to all the members across the country.

Trevor Botkin: 33:46

Thank you for your engagement, thank you for the relationships, thank you for everyone that was in Yellowknife with us recently and for contributing to an incredible community leadership summit, and to everyone else listening. I hope you will tune again to future episodes and, if you haven't already, go back and check the back catalog Again. Nancy, thank you so much.

Nancy Demers: 34:06

Thank you for having me, and we'll see each other soon.

Trevor Botkin: 34:09

And I encourage you all to continue leading with vision and purpose and with authenticity and, as always, this is where leaders connect.