 I want to maybe talk a little bit about, in your article, you spoke about how power stations were built in 1881, but as late as 1910, manufacturers were still relying on steam power. My question to you is, why was that the case? And do you think that we're going to be experiencing something similar with digital transformation, where it's going to take corporates maybe 30 years to start embracing data science, AI, and other forms of technology in their business? Yes, I mentioned that example in the article. And I think, I mean, I was also quite surprised when I read the facts about the electricity industry and how long it took for it to become mainstream in manufacturing. The issue, it was quite an interesting one. The power was available, but if you think of factories, factories were set up in a way that was consistent with the previous source of power, which was steam power. So that meant that instead of having what we recognize today as a production line, the activities in the factory had to be organized so that they could draw the power from the steam pipes that had to be orchestrated in a very specific way. So what that meant was that when the electric power was available, substituting the source of power from steam to electricity didn't change that much and was not very easy, because while the source was there, the business was not ready to change. And that's why it took 20 years. Factories had to be rearranged, rebuilt pretty much. You had to remove all the shafts and all the pipes that were there to support the delivery of steam power. They had to be rearranged because with electric power, you had a flexibility that you did not have before. And that's when production lines, as we recognize them today, started to appear. And that took 20 to 30 years. Now, when we think about what does that mean for fintech and data today, I think the first thing it suggests to me is a degree of caution about those statements that things are going to change tomorrow. Now, that does not mean that they're not going to change. And those that do not change, it could become like a codec. But I think it's a little bit of the reassurance that it's not immediate change what we are looking at here. It's more about that long-term change that unfortunately is easy to postpone, because it's not today's problem and that there may well be bigger problems today in any one business. But it is something that you have to tackle sooner or later. And I think that there is also that little bit of generation that unfortunately plays a role here. People are driven by perhaps also by first impressions. So for example, like it or not, when people think about blockchain, they are thinking about cryptocurrencies. But you know, and I know that there are two very different technologies. But in people's minds, there is an association there that perhaps doesn't help the blockchain technology to be adopted as it could if we never experienced cryptocurrencies and all the other comments and uses that we've heard about the cryptocurrencies. So I think there is the time in terms of that is needed for the business transformations and the perceptions that have been generated that don't really help them. But I'm optimistic in the same way that electricity is today a fact of life. I think that with many of the technologies that today we regard as novelties, there will be business as usual within five or 10 years time, that they may not still be mainstream entirely and they may not be everywhere, but there will be much more prevalent that they are today. And let's not be also very, very harsh on ourselves when we are, I mean, one of the things about artificial intelligence is that we are using a lot of it without realizing already when I'm typing anything on my telephone, the spell checker is already, it's using artificial intelligence. In fact, I like to see how, I enjoy seeing how it learns what I type. So, and that's just a token example that there are many more and better examples about how technologies, fintech, AI is already shaping a lot of the things we do in financial services and elsewhere. So I think I was listening to someone yesterday speaking of the, of the inflection point in an exponential curve. So I think we may be on the cusp of that change. So suddenly it looks big, but not big enough. But I think it's, we are at that time when it looks like it hasn't been changing for a long time, but it should have been changing, but now it's starting to change. No, I mean, you look at those hype cycles and you have the innovators, the people who create the new technology. You have the early adopters who try and get in the door quite quickly. And then you have all the various different stages. You even get the final ones that they call them the stragglers, who kind of like say, fine, we're going to adopt this. We don't want to, but everybody else is doing it. And if we don't, we might as well close up our shop. And I mean, as a risk practitioner, where do you see most of the resistance coming from within the corporate? Is it the tone at the top? Is it the board members who are saying, okay, maybe let's wait until tomorrow? Is it the executive team? Or is it just the employees who maybe don't want to change the processes that they've been doing and want to rather stick to how things have been always done? Where would you say that the biggest resistance is coming from within these businesses to the digital transformation? I don't think there is a generic answer to your question. I think different businesses have different pain points. So for example, in some cases, it may be a matter of priorities. So the business have more pressing priorities in the short term. I think there are also other cases where the challenge with fintech is that it requires a certain investment in technology, which are feasible if you've been keeping up with investments in technology over a period of time. If you haven't, then there is a significant gap there that has to be addressed before you can make investments in fintech. So that's a very different scenario from the first one. I think in all cases, you've got an issue with employees because the perception or the misperception perhaps is that you're going to lose your job. And I think that people react to those misperceptions because that's all there is to be honest. So that's also another consideration that has to be taken into account in any program of this nature to ensure that the human side or the human risk is being managed appropriately. And not only in terms of avoiding the bad outcomes happening, but also in terms of getting the best out of people. Because if you think of those scenarios where we were describing earlier about the radiographer that gets now the predictions from the AI machine, he needs to understand what he's getting. You know, it's all very well to have someone that designs the actual model and maintains the model, but you then need to ensure that many people in the business that are not specifically AI practitioners can understand and take delivery of those outputs and make use of them in the normal course of work. So that requires a significant engagement with employees to ensure that they achieve that level of competency. No, look, I mean, it's been interesting talking to some of my friends who are also consultants and going into the business. And some of them, especially here in South Africa, the mining industry is quite big. And they say they've had quite a little bit of frustration with the older generation, who in some ways don't even want to move to computers or scanning documents or anything like that. They want to maintain a paper file system, which for me, I think is absolutely crazy because I've grown up with Excel and computers and technology. But I kind of hope that I'm not going to be in the same boat maybe say 30 years later, because technology is going to keep increasing. And I might become a little bit stubborn or stuck in my ways and say, no, this is the software I like. I don't want to change to the other ones. So it's interesting to see that human resistance. Of course, there's also the stories of some people might think, oh, the machines are going to come in and take away my jobs. So we are purposely going to try and avoid using them or something like that. Of course, these are extreme stories to just try and make that point that there is that resistance coming from the business. And like you say, it can sometimes come from different aspects. Isaac, I am aware that we are coming up to the end of our hour. I think we have 15 minutes left. So I want to use those 15 minutes maybe asking you to talk more about this dinner that will be hosted in September. What can people expect? Who should attend? And what are going to be some of the highlights? So I think this dinner on the 19th of September will be a good opportunity to have a discussion with the senior risk practitioners in the industry about ideally how they can be part of the answer and how they can help support the business go through the transformation that everyone I think agrees needs to take place. But where we see that there is a degree of reluctance to fully embrace it, it will not be a conversation where we all come out with an answer. But hopefully there will be an interesting conversation around the table where we all feel that we've learned perhaps something that might help us progress those conversations because at the end of the day, many of them are happening today. They may not be progressing at the speed that the technologists might like. And they may not be happening at the speed that the CEO would like to enhance the bottom line, but they're happening. And the question is what can be done to support those activities? And so if everyone that comes to the dinner lives with one idea to explore something back in the office about how to support the business or how to use risk management to support the business, I think that would have been very worthwhile. Okay, fantastic. Look, I'm going to hopefully be at the dinner. I just need to sort out my visa in order to get into the UK, yeah, which is going to be a little bit of a painful to swallow. But hopefully I'm going to be there. I'd love to see you in person and continue this conversation further. And to all our listeners, thank you for staying tuned. And like I say, please check the description of this video for more information about that event. Keep well. Cheers.