00:00:00:02 - 00:00:23:15
Grant McDonald
We hear the word innovation everywhere. But what does it really mean? You and I may have a different opinion on what it looks like, but if there's one area of innovation that is growing across a number of financial institutions, it's AI. At TD, AI has been part of our story for years. In 2018, we acquired Layer 6, a leading AI and machine learning startup, which now forms the backbone of the Bank's AI efforts.
00:00:23:16 - 00:01:03:05
Grant McDonald
And today, we're driving big moves, like launching TD AI Prism, earning recognition for responsible AI, and targeting $1 billion in annual value. But how do we compare globally? That's where the Evident AI Index comes in. It ranks 50 of the world's largest banks on AI adoption. I'm Grant McDonald, and on this episode of The Banking on AI Podcast, presented by TD Invent, we talk with Alexandra Mousavizadeh, Co-founder and Co-CEO, Evident, about what the index reveals and where the industry is headed.
00:01:03:07 - 00:01:18:12
Grant McDonald
Alexandra, listen, thanks so much for joining us. You have such a unique background and I'd love to dive in. You tell us a little bit about yourself and your experiences before Evident, and how you sort of got to where you are right now.
00:01:18:17 - 00:01:44:01
Alexandra Mousavizadeh
Well, thank you so much for having, having me on. I am dialing in from very rainy London here. So, I well, it's a good question. Like, how far back would you like me to go? I can, I can start from the beginning, if you like. So my, so my background. So, as you know, maybe some of the listeners, you know, we started Evident three years ago.
00:01:44:02 - 00:02:09:08
Alexandra Mousavizadeh
I'm the Co-founder and CEO of Evident. It is, and we are, the first to publicly rank financial institutions on their AI progress. So, the progress they are making in investing in all of the enablers, AI enablers of a business, and, and measuring the outcomes and the ROI of, of that, the AI investment and deployment in, in the bank.
00:02:09:08 - 00:02:37:13
Alexandra Mousavizadeh
Or we also look at insurance companies. We also look at payment platforms and asset management and so on. And I got into this space of, measurement of AI development and deployment dome years prior to that, having developed the first global AI index, looking at, nations vis-a-vis each other in terms of their strength of their individual AI ecosystems.
00:02:37:13 - 00:03:04:12
Alexandra Mousavizadeh
So U.S. versus China, Canada, Singapore, UK and so on. And built that index back in 2018 before AI was sort of as much as a top of the, you know, the media feed as it, as it, is today. It was it was there and it was interesting, but it was definitely not sort of top of, top of the media feed.
00:03:04:14 - 00:03:28:18
Alexandra Mousavizadeh
And prior to that, my sort of my whole background is in index creation. I've spent many years at Moody's sovereign team. Was in, you know, a part of the team that was measuring, Russia and Central Asia back in the 90s, also covered the Middle East and, and Europe and many other countries.
00:03:28:20 - 00:03:49:15
Alexandra Mousavizadeh
Was then at Morgan Stanley doing a very similar role. But prior to that, I was, I'm from Copenhagen. I have a degree in mathematics, economics and focused in on game theory, which was, very few people who were looking at game theory back, back then in the mid-80s, but has sort of come full circle.
00:03:49:15 - 00:04:07:03
Alexandra Mousavizadeh
So, you know, with mathematics and game theory, with a deep knowledge of, of, creating benchmarks and sort of spent the last eight years of, of, of really going deep into, what is a strong AI ecosystem, first in nations and now in businesses.
00:04:07:05 - 00:04:24:15
Grant McDonald
You know, that it's, it's fascinating to hear here that that path that you've taken. And I always look at where was that moment when you decided, I think I can start something here? I'd love to dig a bit deeper into the actual origin story. And what really prompted you to, to launch Evident?
00:04:24:16 - 00:04:50:19
Alexandra Mousavizadeh
What the prompt was, because we had at that time being, been knee-deep in the national debate, the debate about, you know, who's leading the race on emerging technologies? And AI since sort of said, as I said, so we built that national ranking back in 2018. And, it was, it was very clear that that was starting to emerge as a priority for governments.
00:04:50:19 - 00:05:22:19
Alexandra Mousavizadeh
You know, the Canadian government launched actually the first AI strategy back in 2016. It was followed by one in Singapore, then China, and then at the end of, you know, I think in 2019, there were about 40 nations that had a sort of specific AI strategy. And, and having sort of spent that, you know, those years looking at what, what does that mean to be really good at something that's quite, you know, specific from other technological transformation times like the internet and so on?
00:05:22:21 - 00:06:00:15
Alexandra Mousavizadeh
Back in sort of the late 80s, early 90s. This was this was very specific and required a specific type of spending, a specific kind of talent, and a specific kind of environment to be conducive for progress on AI development and deployment. But the tipping point to start Evident was when a number of the bigger banks, in the US actually, were saying, hang on a second, we are spending so much money in our tech budget, you know, billions and billions and more of that is going into what we would call change the bank, not just run the bank.
00:06:00:21 - 00:06:26:01
Alexandra Mousavizadeh
And more of that is going into emerging technologies, predominantly AI. But there's also an emerging focus on quantum, which we also track, by the way, and, and when, when a number of folks had reached out and said, could you, could you take that methodology that you've developed on, at the national level and could you, could you apply it to, to us as banks?
00:06:26:03 - 00:06:45:22
Alexandra Mousavizadeh
Could you apply it at an enterprise level? And I must say that in the when I first got the request, I said, I'm not sure that's possible, but when I think request number five came in, I thought, hang on a second, I need to, I need to look at this. And we then spent some time, we spent about nine months developing the methodology for banks.
00:06:46:00 - 00:07:10:08
Alexandra Mousavizadeh
And, you know, it's no small thing to take on something as sensitive as measuring a big company on where it sits on something as existential as AI. But we felt that we, we, we'd been so deep in this, in this world of measurement of AI, to a point where we felt very confident if there was anyone that could do it, it would be us.
00:07:10:08 - 00:07:31:18
Alexandra Mousavizadeh
It would be our team that could do it. And there was absolutely a need for it. But it was also very much driven by the deep belief that in order to progress on AI deployment, you need transparency of what is going on, what are the best practices, what are the best organizations doing? What can others learn from that?
00:07:31:20 - 00:07:53:01
Alexandra Mousavizadeh
When you're investing in this, you know, let's help everyone not waste the dollars, the AI dollars. Let's help point it in a direction so it's really efficient. And at the end of the day, you know, really trying to support the progress of AI adoption because in my view, there are three AI races going on right now.
00:07:53:01 - 00:08:14:07
Alexandra Mousavizadeh
There's, there's a geopolitical race. So that is, you know, who's winning it? Is it China? Is it the US? The second race is technology companies trying to reach AGI. So the artificial general intelligence and you've got that race is very public. And then the most important race in my view is the enterprise adoption race.
00:08:14:07 - 00:08:35:05
Alexandra Mousavizadeh
Because at the end of the day, it all hinges on the ability to adopt AI at an organizational level. That's where you're going to unlock the, the growth. You're going to get the productivity gains. You're going to, you know, get all of that that nations, you know, will progress on. And, and flourish if they get that right.
00:08:35:05 - 00:08:55:08
Alexandra Mousavizadeh
So people who learn to use AI, companies who learn to use AI, and nations who foster the learning and the uptake of AI are going to be the ones that are going to be succeeding in the future. So that was also very much what drove, the, you know, wanting to set up Evident to really help progress that.
00:08:55:10 - 00:09:16:12
Grant McDonald
You know, it's, it's so interesting to hear the AI only works with humans. Like, that's sort of the bottom line and one of the most important aspects of it. And so when I look back as you're starting to talk to more people about AI and you're in the space, you have a much better understanding. Let's go back to 2016, 2017, a lot better of an understanding then I would argue probably most people.
00:09:16:14 - 00:09:37:12
Grant McDonald
So when did you kind of realize AI was different? Like there was something a lot more transformative about this when you compared it to you know, maybe other technologies? And I'm sure the main comparison you always get is the internet. But I'm curious where you saw that difference and how you saw people slowly beginning to understand what AI kind of means?
00:09:37:14 - 00:10:00:10
Alexandra Mousavizadeh
Yeah, I think I mean, I think there's, there's it makes a lot of sense looking back at the sort of age of the internet, because when it comes to the debate about job, you know, you know, replacing jobs, augmenting jobs and so on, we should keep in mind that this exact debate about concerns around disruption in the workforce, was, was very prevalent back then.
00:10:00:10 - 00:10:23:20
Alexandra Mousavizadeh
And there was the same debates, you know, oh, this is going to erode, you know, our method of learning. We are, it's going to disrupt education. It is going to remove jobs. And, you know, you could argue that, yes, it's, it's had some you know, there's been impacts of that that are, that are negative, especially on sort of social media side of things.
00:10:23:21 - 00:10:55:05
Alexandra Mousavizadeh
And you know, but you could argue that sort of the collective knowledge and the ability to share it has only enhanced our capabilities. And, and also, I would say also to our education as well. The job loss debate was, was very, you know, was, was a big one back then. But if you look back and you look at the data in hindsight, there are lots of studies on this and I think it is for every 1 million jobs that were lost, I think it was 5 million jobs were gained.
00:10:55:07 - 00:12:42:20
Alexandra Mousavizadeh
And we're sort of seeing the same thing in, in this, in this transformation. But I do think we're in a, in a very different, and probably it's a much more revolutionary technology. And if you just look at pre gen AI, right? So pre-November 2022. When we had the release of the first, you know, ChatGPT. AI was very much there. Right. Financial institutions were, had been using AI for decades, traditional AI machine learning and so on. And that was really good for parts of an organization, parts of a bank or an asset management company and so on. All of a sudden, you've got gen AI coming on stream. And what that meant is that AI was not going to just touch a part of an organization.
It was going to touch the entirety of the organization. Because traditional AI can solve certain problems. Right. You've got to sort of if this, then that. Right. It's very linear. But then you all of a sudden have a different kind of AI that is all about, you know, knowledge generation. It's, it's, free based.
It pulls information together. It doesn't give you a linear answer. It gives you an example of a good answer. Right. And the more it gets trained, the better it can do that. So with the combination of the two types of AI, you know, deterministic and non-deterministic AI, it sort of covers everything. And once we really see the gen AI capabilities seep through and into and that deployment coming through alongside, of course, traditional AI, you, you're going to reach a tipping point where you're going to have AI in every nook and cranny of an organization.
00:12:42:22 - 00:13:02:19
Alexandra Mousavizadeh
It will do everything, right? And we're still very early days, just in the foothills of this transition, and it will probably take, you know, a handful of years before it really starts to hit the bottom line. And we're starting to see now these use cases coming through. And you're starting to see that it's, you know having that impact.
00:13:02:21 - 00:13:23:11
Alexandra Mousavizadeh
But we're only in the early stages of agentic AI workflows. And once we have that really coming through that's when I think we're going to see sort of the, you know, the fire being lit and we're going to hit that tipping point and it will be completely transformative. And so it is different. You know, it's a different kind of transformation.
00:13:23:11 - 00:13:46:18
Alexandra Mousavizadeh
But it's definitely, in my view, much more sort of revolutionary. And then you've got quantum right on the horizon, which is probably going to be ten x in terms of, you know, revolutionary powers, because you're suddenly got, you know, your two types of AI combined with an incredible compute capability, which will be able to do things that are completely outside of our imagination today.
00:13:46:23 - 00:13:59:16
Alexandra Mousavizadeh
But we're not quite in the quantum age, we've maybe got a couple of years before we hit that, but it's all pointing to that. So, I think we are, you know, the world is going to look, you know, very, very different in about 5 to 7 years.
00:13:59:19 - 00:14:33:00
Grant McDonald
That is fascinating, fascinating stuff. I always love, anytime I'm chatting with AI experts like yourself. You know, as I say, you know, where's your aha moment? And everyone's like November 2022. That is flat out the conversation where it starts and where they saw that change come. And so I like the idea of our minds not even being able to understand where we could go, but I'd love to touch on AI maturity and what that looks like from your perspective when you're trying to figure out, like how you land on the different standards that you use and how do you use those to assess the banks?
00:14:43:10 - 00:18:14:20
Alexandra Mousavizadeh
Yeah. So there are two sides to measuring maturity. One is looking at the investments into the capabilities. And so what do you need as an organization to be really good at this? You need talent. Right. So we take a really close look at what is your talent stack in your organization?
Then you've got your, are you investing in and all of the innovation levers that you can pull? You know, do you have your, you know, teams producing research that is feeding into the understanding of how your solving particular problems, you know, problems? Some do it through research, some issue patents. Then there's the whole ecosystem of investing in AI companies to get access to that knowhow or partnering with vendors, to solve, you know, you know, problem solve internally.
S. And then we look at sort of what's the leadership composition. If it's a very AI-first focused organization, you'll see that in the way that the executive committee is, is composed.
You'll see it in the narrative of the organization, because external positioning is actually quite important. To make sure that shareholders really know what, you know, that you are on the right track, that that journey has progressed. But, absolutely. Also, to attract the talent that is needed to execute. And so that's looking at the enabling side. And then we also look at the outcomes of all of this.
What's, you know, how are you translating the investments into all of your enablers? How is that translating into outputs? So, then we look at, you know, where are your use cases in the organization? Have you been able to bring down that time to production? We're moving in to show us, you know, show us the impact, show us the ROI, moving into scale.
.[AG1] So it's a real full sort of 360. We're completely data led. But of course, with the data-led approach, you know, the understanding of what really good looks like, what's the state of the art and sort of what's really beginner? And so sort of drawing that out and then we sort of hold organizations up against that, sort of that structure of what is, what is basic versus what is advanced?
And then, and then assessing where, where the companies sit along that line.
00:18:14:22 - 00:18:35:18
Grant McDonald
You know, you pulled it out a couple of times. And I know, you know, boardroom tables around the world are saying, ROI, what do we get out of this? And I'm always really interested in what it looks like for someone looking around. They don't know too much about AI, but everywhere everyone seems to have some sort of AI element.
00:18:35:20 - 00:18:55:15
Grant McDonald
In your different marketing that you're seeing and different items that you would never assume would have anything to do with AI, how do we kind of cut through that noise and that is that sort of where you see a lot of your major value being offered in this index, and how does that help companies and just the general public have a better understanding as to what your point is like?
Good and maybe not so good?
00:18:55:17 - 00:19:18:11
Alexandra Mousavizadeh
I mean, that is actually the question. The biggest question, you know, for CEO, for a board, you know, for the senior leadership is, is where are we today as an organization? And what does good look like? Where should we invest our AI dollars, so to speak? How much should we be investing and what does what good look like?
00:19:18:11 - 00:19:37:06
Alexandra Mousavizadeh
That's definitely what we can show in all of that data. And so that real understanding of, of, of where I can be of use and to my point earlier, you know, it's really to be used everywhere, but, we can sort of help sequence, you know, where to start, where to go next. And what is state of the art.
00:19:37:08 - 00:20:02:16
Alexandra Mousavizadeh
But when it comes to, to society, I think, you know, I think there is there's, there's we all have to help advance the understanding of what AI is and what it isn't. And we've had a debate over the last couple of years. I'm sure all the listeners will be very familiar with existential risk. And we should be really fearful of AI, and we should stop the research.
00:20:02:16 - 00:22:02:15-
Alexandra Mousavizadeh
And, we all know you can't stop, you know, technological advancements. It's on a train and it keeps going. And at that, the speed of which the train is going is only picking up. And so we need to really fully understand, sort of, what are the impacts? And I think we need to have these debates around what is it actually doing to the labour force? What kind of skills are required?
What kind of policy support should a government give, overall to, to businesses, to help them advance their AI adoption in a safe way? You know, so from a societal perspective, it is important to know, you know, what are all of these opportunities? And I'm, you know, I'm very close to this technology. I'm a huge optimist because what I see how it's being implemented, there are, you know, by necessity, especially for financial services built in guardrails.
No one wants to put out AI tools and capabilities that are rogue, or who are suggesting something to clients or interacting with customers in a way that's not good. No one wants that. Right? So if there ever was a blueprint for, you know, for any company in terms of how you regulate and how you think about deployment, it really is actually the banks, because you've got such a strong, you know, there is such a sort of, you know, strong oversight from a governance perspective.
You've got your first and second lines of defense in terms of safe architecture testing, testing it in your second line, all of the validation. And, you know, every company should follow that exact blueprint. And so from a societal perspective, I think it's important that, you know, think that it is communicated that this is, you know, we should do everything we can to deploy with care, and that there's a lot of thought that goes into these guardrails.
00:22:02:18 - 00:22:21:13
Grant McDonald
You recently came out with your third annual Evident AI Index. So first off, congratulations on that. I'd love to, to hear from you some of the kind of the emerging trends that you're seeing, sort of as you evaluate the evolution of it and especially when it comes to the evolution of, you know, AI maturity within banks.
00:22:21:13 - 00:23:32:09
Alexandra Mousavizadeh
= The most, I would say sort of the most striking result that came from, from this year's, ranking. As you know, we released the ranking mid-October, the 2025 annual ranking. And it was the fastest growth in AI activity that we've ever seen. I mean, our three year history and maybe not surprising to see that level of activity because we're moving from a phase of testing and figuring out how does this work and how do we select the things to go for, and how do we prioritize, and do we have the right talent to now in
this phase of deployment and sort of show me the impact? And so, maybe not surprising that we're seeing across the board a really big ramp up. And so all of the banks shifted up, all of the insurance companies shifted up and so on. But what was really interesting to see is that we could see that the gap between the leading organizations and the lagging was growing really quickly.
00:23:32:10 - 00:23:59:23
Alexandra Mousavizadeh
And so the sort of the gap between the leaders and the laggards was just, you know, they were they were pulling away from each other. And the concern that I have with that is, are we reaching a point where it's going to be really difficult to keep up because the leading banks are entering this, positive flywheel effect of having in place the organizational structure to really move quickly.
00:24:00:04 - 00:24:33:03
Alexandra Mousavizadeh
They're starting to see the results really quickly. So they're starting to be able to take some cost out of their operations. They can do more with the same or even they you could argue they're doing more with less. And so they're growing their market share. And all of that is now starting to, to accelerate. And so if you haven't started, you know, your AI strategy or executing on that AI strategy is just going to take, you know, longer to get to a point where you can compete.
00:24:33:04 - 00:25:00:21
Alexandra Mousavizadeh
And maybe we're getting to a point where keeping up or even just holding your position is going to become really difficult. And so you might start to just slide out of existence over time. And that is a concern. So when we're talking about sort of where we might see disruption, I think it's much more around the, you know, organizations that are not leaning into AI that go out of business.
00:25:00:21 - 00:25:30:14
Alexandra Mousavizadeh
It's not the organizations that lean into AI because they actually tend to be the ones that even they talk about reducing costs and taking some headcount out, actually, the data shows that they're actually adding headcount overall, they're hiring more AI talent, but they're also hiring more overall. And they're, you know, growing. And, you know, we're seeing a lot more sort of new jobs cropping up in the organizations that are leaning into AI.
00:25:30:14 - 00:25:48:08
Alexandra Mousavizadeh
So I think one should also dispel this thing about leaning into AI cuts jobs. I'm not sure that that is true. I think that data from the internet days is that the more you lean into it, actually, the more job growth you see alongside it, and the more job creations you see on the other side of it.
00:25:48:10 - 00:26:09:10
Alexandra Mousavizadeh
So, so I think that is yeah, that's sort of that's definitely what we're seeing from this latest drop of the data, the sort of growing gap between the leading and the lagging organizations. And, and we see that, you know, in the US, we also see it in Europe. So the leading banks in Europe are leading more.
00:26:09:12 - 00:26:38:07
Alexandra Mousavizadeh
The lagging banks are falling behind. So back to the sort of the, the back to the just sort of nations leading, if they lean into it, the nations that, you know, don't spend time and money on it will will be takers, not makers. And likewise on the organized and on the enterprise adoption side, you will have those that are leading and capturing the market share.
Alexandra Mousavizadeh
Those that are not might, might have difficulty keeping up in the long term.
00:26:38:09 - 00:26:57:12
Grant McDonald
I mean, that's a pretty clear picture in terms of what's happening, what I, what I like about the index as well as at it, you kind of evaluates subcategories as well. So you're looking at leadership, you're looking at innovation and, and more. One subject that we've been looking at is AI talent. And so I'd love to get a sense of what is Evident,
00:26:57:12 - 00:27:10:23
Grant McDonald
What does the index kind of say about that and about the evolving sort of race for talent? I think you touched on it to a certain degree, where if you're investing now, you're going now you're seeing that potential job growth. But I'd love to get a better sense of the from the talent perspective, from you.
00:27:11:02 - 00:29:54:16
Alexandra Mousavizadeh
So there is this war on talent, as we all know. It is, you know your progress on adoption, it's really only as good as your talent can do it. I think that, you know, essentially your talent is your destiny. And so getting your talent piece right is incredibly important.
And so there's a lot of thinking going into how do we as an, not we, but how do organizations, put their best foot forward to attract the best talent? And so a lot of things go into that. You know, first and foremost, organizations are really thinking about what is it that attracts strong AI talent. It needs to be, we need to show that we are AI first.
We need to show that we are, you know, we're really working on really interesting problems and that there is value creation. So what you will be doing if you come and work here, you'll have a real impact. But talent is, is also that kind of talent is also looking for maybe being able to, you know, do research that they can present at an academic conference because there's a lot of pride in this work, or maybe even being able to file a patent, be among like-minded people, be among their peers, you know, and so a lot of thinking goes into talent attraction that is very different from sort
of pre '22. And I think that sort of in this era, you know, it's you're looking for very specialized talent and they have very specialized needs. And we're seeing, you know, that being a really important component for an organization's ability to attract talent. But the talent, you know, the talent needs are constantly evolving. You know, there are, you know, what is needed to build is slightly different today.
You know, product managers, and really skilled product managers that can come in and have that mindset of, let's sort of rethink about this, you know, how does this process work? How is this process working now? How can I completely rethink it? A lot of that mindset is being pulled in to the banks from big tech.
And so we do see that flow coming in from big tech. That's increasing. But it's super competitive because it's very hot in the tech sector as well. So, and they can pay a lot more often than the financial services can. And so there is this tug and war. But you know, if we are, if we are in a bubble, which we may or may not be, you know, there might at some point be some outflow of that talent, which would serve the financial services really well.
00:29:54:18 - 00:30:18:08
Grant McDonald
It's so interesting to, you know, to think about it from that perspective. And the, you know, I'm always curious as well as you're putting this index together, you have such a unique opportunity to kind of analyze AI practices quite closely. There's a lot of people, for whatever reason, they're a little hesitant there. They're not sure if they want to jump into it and they're concerned about, you know, making it responsible.
00:30:18:08 - 00:30:29:12
Grant McDonald
AI. How are banks doing on this when you're looking at those broader trends? And what characteristics should kind of clients look for when they're going to determine how well banks are doing?
00:30:29:13 - 00:31:09:19
Alexandra Mousavizadeh
It's, it's an interesting debate because doing, rolling out AI responsibly is of course, at the end of the day, the most important thing, for the bank itself, for everyone they serve. And there is no one more worried about making sure that it's safely deployed than the banks themselves. And so I think we're in a phase now where responsible AI is almost assumed. There will be, you know, banks are putting out, you know, great and important statements about the principles that they follow, the governance structures that they have in place to make sure that there's no bias.
00:31:09:19 - 00:31:50:13
Alexandra Mousavizadeh
And it's all very fair. But I would say that that is very much a given. And those foundations are really there in the financial services. It's moved into the knotty questions around model risk management and how you design your relationship between your first and your second line of defense, with a technology that doesn't behave very well in a model validation because it can never produce the same result each time, which is what traditional AI could do.
00:31:50:13 - 00:32:23:17
Alexandra Mousavizadeh
And so, there's a lot of thinking about how do we evolve our governance structures for gen AI and agentic AI-specific behaviour. And, and right now that's sort of where we are. A lot of AI has been used to make sure that the data sets that all of this rests on is cleaned up for bias and fairness, and that the data itself has, has, you know, a full representation to it.
00:32:23:19 - 00:32:40:14
Grant McDonald
Alexandra, I could talk to you all day about this. It's every question I have, you have fascinating answers for. But I do always like to end by saying, what is the kind of message that you want to. you always want to make sure people walk away understanding, like this is the most important thing that I have to tell you today.
00:32:40:16 - 00:32:45:10
Alexandra Mousavizadeh
Yes, I mean, can I say 20 things or can I just say one thing?
00:32:45:12 - 00:32:48:09
Grant McDonald
We'll do the top three.
00:32:48:11 - 00:33:15:09
Alexandra Mousavizadeh
I mean, from our perspective, it is, you know, it is, I mean, we used to talk about banks that were too big to fail and, and very much so what we're looking at now is, it is, you know, are you too late to compete? And I think that is something that comes back at us every day, all day long, you know, at what stage is it just too late to compete or can I, can I leapfrog?
00:33:15:09 - 00:33:39:22
Alexandra Mousavizadeh
And I would say, yes, there's absolutely your opportunity to get moving. Move fast. But I would say, you know, it is a race. So I would absolutely make sure that if it isn't, you know, top of the agenda, it really should be. And I think also, one of the things is what it takes is great leadership.
00:33:40:00 - 00:34:15:10
Alexandra Mousavizadeh
And I think that we shouldn't underestimate the role of CEOs in this. And it's bigger than I, you know, I anticipated I thought, oh it's like really the CTO and the CIO and it absolutely is. But if the message from the from the top, is this is important and making it very clear both to the outside world, but even more importantly to the, to the company itself, that this is the most important thing for, for us, for us as individuals and for the organization.
00:34:15:11 - 00:34:37:07
Alexandra Mousavizadeh
I think that's really important. But also to remember that, you know, the CEO messaging, the senior leadership messaging is very important. But we're also in a in a phase now because we're in sort of more of an execution phase that the responsibility is being is being pushed one level down to the heads of the lines of business.
00:34:37:08 - 00:35:00:13
Alexandra Mousavizadeh
And there's an enormous amount of responsibility put on the shoulders, of heads of lines of business, of that, senior management, not the C-suite, but the senior management that are taking on an enormous, enormous burden. And I think we have to keep in mind that, that's really exciting to think through how my function can be different.
00:40:32:16 - 00:40:53:10
00:35:00:15 - 00:35:21:08
But we also really have to equip that senior manager with the, you know, alongside him or her that there is, expertise, there is support, there is budget and so on, to embark on that journey. So I think if that was three, maybe four things, those are the things that I think are the most important today.
00:35:21:14 - 00:35:27:06
Grant McDonald
That's fantastic. Alexandra, thank you so much for taking the time to chat with us today. It's really appreciated.
00:35:27:08 - 00:35:29:04
Alexandra Mousavizadeh
Thank you so much for having me. It's a pleasure.
[AG1]This feels super in the weeds, but may be interesting to those that are really into the ranking. Potential to trim.
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