152 | Embracing AI with Humanity | Scott McInnes & Wema Hoover

Scott McInnes talks with Wema Hoover about integrating AI into organizations without losing the human element. They argue AI becomes a competitive advantage only when paired with clear guardrails, intentional leadership, and a culture that frames it as complementary rather than a job threat. The key is addressing employee anxiety through change management, reverse-mentoring across generations, and letting people co-create their evolving roles.
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This is the value that AI is going to give us. This is going to actually allow us to not only have the competitive advantage but help us do what we do at a higher, much more focused and impactful way. That has to be done. Once you have that, that is your, you know, your, your, your route that your sales are, are, are going towards, right? And everything else will be able to follow.
Inspiring change, we help our clients build work cultures that bring out the best in their people. We created this podcast to share real stories and insights from those who are shaping better workplaces every day. You're very welcome to the Building Better Cultures podcast. We're excited to have you with us. Hello and welcome to this episode of the Building Better Cultures podcast with me, Scott McInnes. Before we get into today's guest, just my little broken record ask to please take 20 or 30 seconds of your time just while you're listening to this episode of the podcast to just give us a rating on whatever platform you're listening on or give us a little comment. And don't forget, click the follow button on whatever platform you're using because that means that you'll get brilliant episodes like this one today straight into your feed as soon as we release them. My guest today is actually no stranger to the Building Better Cultures podcast. Emma Hoover, who is the founder of Be Limitless Consulting, was actually with us back in August 2021 in episode 80, if you want to go back and have a little listen to that, 70 episodes ago, where we had a brilliant conversation, a brilliant conversation about unlocking the power of diversity. And we'll build on that today because Wayma's focus, whilst I know is still very heavily on that, has also moved into the space of AI, of culture, of capability building, of trying to work out that when strategy and human-centered leadership and technology like AI, which we're going to spend a good bit of time chatting about today, when they all crash into each other, what happens? And how do we make the most of that? And how do we make sure that we take the goodness and we don't get swallowed up with all the madness of particularly all the AI stuff that's going on at the moment? So, Weimar, hello. It's lovely to have you back again.
Hello, Scott. It's a pleasure to be back and always excited to join you and join Inspiring Change.
Great stuff. You're very kind. Thanks. So listen, let's kick this off. Give us your thoughts on where we are at the moment. I think that AI at the moment is running at a million miles an hour. I know that somebody said to me recently, you know, when we went through the industrial revolution change, that was about 15 years. It feels like the AI change that we're all on at the moment, that change curve has been about 15 months. And the change that it's bringing to the world of work, to the world of people, to the world of leadership and culture is enormous. And I wonder what your thoughts are on where things are right now.
Yeah, we're in an interesting time and moment right now because AI is seen as this really sexy, beautiful, new shiny toy, which has all these bells and whistles that everyone is trying to implement, pull into their organizations, and make sure they get the first and the best version of it. The challenge with, just like anything that is coming new and out, is that you have to really think about how is it supporting the work that you How are the employees not actually seen as this is going to be something that is taking my, my job and, and making things going to be kind of streamlined or taking away, but how it's gonna be a complementary asset for me. You know, right now I think there is this push for organizations just to pull AI into everything. And although we are in an experimentation phase, there still has to be some type of foundational elements that organizations and companies really put guardrails around an understanding of what and how they feel the best capabilities and way to absolutely maximize the value that AI can bring. And I think where we're seeing organizations maybe have some difficulty with their employee base actually doing an adoption is when it's just kind of thrown at them without any, this is how we see AI supporting our work more moving forward. This is how it helps us deliver better customer service. This is how it helps us have better patient outcomes, but not really dictating what and where that actually can be done. And so I think that it's causing a lot of fear and anxiety with employee bases, where there is a lot of opportunity that, that could be made in terms of how to maximize that relationship between the human and the technology and AI. And I think that that's going to have to be a learn process and a learn experimentation that has to be adopted by manager capabilities and how the leaders show up.
It's really interesting that AI, I read the other day, has been around since I think it was 1956. Yes, yes. And the military have had it for 70 years and it's been used for years and years. But of course, it's only really exploded onto our desktops probably in the past, I don't know, 2 years, 2 and a half, 3 years perhaps. And I think absolutely to your point, that idea of guidelines, of guardrails, of policy is so fundamentally important. And it was interesting that I was out for a couple of drinks last night with Denis Doolin from AIB, who's also a former guest on the podcast. And we were talking about AI and the impact of AI. And I was saying to him that I was talking to you about it on the podcast today. And he was saying, isn't it interesting that it's not going to be until 10 or 15 or 20 years further down the line that we fully understand the impact that this change is having right now. I think when mobile phones— we were talking about it last night— when mobile phones came in, when he and I were working in London in the '90s, we had mobile phones and you just literally played Snake on them and you rang people. But now, of course, we know that with the algorithms and everything else that we're being sucked into our phones and our kids are being sucked into their phones. But it's taken us two decades to recognize that. It'll be the same with AI. So I wonder what organizations can be doing now? What more can they be doing, particularly when it comes to the people side of things, that the AI doesn't just come in and take over and we just literally blindly let it go wherever it wants to go?
Yeah, you know, that's a really good question. And I think one of the things that companies need to do is really looking at what are the human-centered behaviors and human-centered engagement that you want to actually maintain? What is important? I had a discussion with a gentleman who's leading a major healthcare organization and, you know, working in a role of a COO and was saying that, you know, for the medical profession, medical doctors, AI has really helped them have better patient-centered connections. So where in the past the doctors were coming into the medical rooms, taking copious notes, really not having the eye contact, the connectivity to the patients. Now they have, um, an agent model that actually does that. And they see the value that it is going to help them have better patient engagement. It's going to help the patient have a better experience and thereby really serving them at a higher level. But this is what this healthcare system did before they introduced it. They did the work. And we, we talked about earlier, had the knowledge in saying, we see this as a value in this capacity because it's going to help us serve our patients, be better, have better engagement, and in, in turn be able to deliver high, better healthcare outcomes for the people that we serve. And I think that has to be the staple of all organizations there. Is that element of experimentation, which is great and which I think that should be encouraged. However, I think at the same time, so that you have your employees that are using, understanding, and trying to determine how it can help them drive the better, be actually more efficient, and even have more ideation, that has to actually be saying, this is going to allow us to free up our human time, right? Are those things that AI cannot drive— curiosity, connectivity, engagement, that exchange, that collaboration that comes through the human interaction, where and when that can be determined and outlined and actually kind of positioned as a behavior that actually goes in tandem with the AI, I think that that's where success comes. But right now, I think there is this race, if you will, who is going to adopt it better and how are we going to kind of not only shift the way that we work, but use it to really have kind of savings and reduce our overhead. So, I think that people element is what's missing the most right now. And that was what I think in 10 to 15 years, we will see a major impact. Yeah.
So, it's about— so, if I take from what you're saying, is it about intentionality? Is it about finding a specific challenge, a specific problem in the healthcare example you gave there of the doctor always be taking notes and therefore not able to actually engage with the patient, whereas now, presumably, there's some listening device or something else which is just listening to him talking and able to take the notes itself.
Yes.
Being very specific about the problem and how you can use AI to address that specific problem, as opposed to saying, okay, everyone, here's ChatGPT or AI, applaud, go, go, go figure.
Yes, yes. And what that's going to do, and when you do that, you actually, you know, do the opposite. You actually, instead of the excitement and the motivation around AI, you actually get fear and trepidation because there is going to be an automatic inherent assumption that this tool, this technology, is going to be used to replace the work that they're doing, what they're leading, doing quicker, faster, to actually then they're working themselves out of their own job or career or profession. And I do think that it will behoove, and it is extremely, extremely important right now that organizations really look at what is their human-centered people value that serves in their company, in the work that they do. And all, every, every industry, every organization, every type of business has this. And I think once you identify that and really have that being the foundation of the behaviors, really show up in the purpose-driven work that you're doing, then it will be very easy across all of the functions and sectors of your business to then align the AI then to support that. Because we are really looking at how are we doing our job better and using the innate abilities that only humans can bring. Again, the curiosity, the empathy, the exchange, the collaboration to allow us to do work at a higher level and with higher impact.
How do we protect the humanity of our organizations so we can continue to be human-led and human-focused with our customers? Because ultimately, it's still going to be people that are buying what we do, whether we sell baked beans or bank accounts. It's still a person selling something to a person. The AI is just helping to smooth out that process in some areas where it's better. Yes.
And we have to also create more familiarity that the AI and human hybrid workforce is here and it's not going anywhere. So we're gonna have the impact, but it's not going anywhere. So in order for us to create that familiarity, create that comfortability, create that adaptability so that you won't have the employees or the functions or sectors that are going way out that gate and really doing the experimentation, using it full-fledged. And you have the resistors because that too, we don't talk about a lot, but there are a lot of folks in the organizations that are adamant resistors and refuse to do it because that fear. You really need to actually think about how to manage that as a part of the change, as a part of your organizational development, as a part of how you are seeing the effects of the behaviors from the leaders, from individual communi— contributors and from the managers? And what kind of teaming environment and expectations are you actually setting in practice so that you can bring everyone along together? Now, naturally, you're going to have those early adopters and those ones that actually get excited naturally because they are tech folks. And I know we all have them. We all have the colleagues, we have the friends that anything that's exciting and new, they're going to adopt. But we all know the ones that all will be resisting. And that's where I feel like literally having that be a part of your organizational efforts for change and for development, really outlining what does our AI and human workforce, the behaviors, but also the assets, and how do we allow people to share, to exchange, to teach in a way that is not forceful, that is not demanding, but actually can be seen as self-development, that it is actually going to help me whether I use it or not. I'm gonna be knowledgeable, I'm gonna have this skill, and it's gonna enable me to understand and be able to navigate in this, you know, not new world, the world that we in now, better and more effectively.
Is it fair to say, or is it maybe simplifying it too much to say that this is just another change? And back to your point about the early adopters and the resistors, we find those in every change that goes on in an organization. So this should be, this should be a program of work in any organization, which is driven by change management, driven by change comms, done in partnership with people in the organization. So So it is just another change, right?
It is just another change. The only thing I would actually say makes this very different is that you have the outside world, right, in addition to it. So I just saw on the news today, they had it on, you know, CNN around these organizations that have popped up that are anti-AI. And I'm sure you've heard the recent news about some AI tech CEOs that have that now are being attacked from it. And so there, it does have to be a balance because you're having, right, all of this noise outside of the world that's either getting, giving excitement, motivation, or really inciting that fear, that anxiety, and that resistance. And so that's why it does need to be managed by a change, by, as a change management. But that's where the organization's real focus on aligning it to its purpose, to its behaviors, to how it's doing Driving work and what is the value that it will serve has to be equally done at the same time so that it's just not a new change, but it's a change that is going to help us in this very specific, relevant, and impactful way.
And I think that as we go through this change, it's probably quite easy and maybe in some cases true to say that maybe some of those resistors or those people more resistant to the change are the ones that are toward the twilight or the autumn of their careers, let's just say, whereas the ones that are perhaps using it because they were almost born with it, are those people arriving into our organizations now, some of those younger generations. When those two collide, how can we get them to work together for the benefit of the whole organization, to see each other's perspectives and to understand and to collaborate and work together towards success?
Yes. And I think, you know, this is one of the— I wrote an article about this a couple of months ago, and really it's around this dynamic that AI is the sixth generation. So you literally have to use it as a 6th generation because it has values, it has a different approach, it has a different adoption, the world that's coming in. And this is where there has to be an actual setting and promotion of exchange and a promotion of working interactions with employees to actually teach and learn. And so, when you're looking at a teaming environment, and this is where I was talking to one of my, my clients, you know, how are we actually making sure that everyone, regardless of their level in the organization, within their teams, are able to give not only ideas, but actually talk about what is the AI solution that is driving that they feel have that they— and actually have them own the skill, have them own the development, have them own the experimentation of it, and actually have it seen as something that they can actually cross and teach people with. And so they still, you know, started having these learning sessions that anyone that actually had an idea that actually worked, they experimented with. And it would be everyone from executives down to exec— you know, assistants or project managers that would actually join just to incite innovation, have that curiosity. Now, whether it's adopted, but literally knowing that these things are happening and, you know, encouraging that exchange and that ability to work across the levels of the organization that, you know, very much often equate to generations. And not having that barrier wall to saying, Okay, this is a tool that the young people play with. I know you just came out of grad school. This is hot and sexy. But giving a platform for that experimentation. And again, they're not saying everything is going to go through, but it's these— literally, they're having these sessions sometimes quarterly. But if there is a great idea, it could be multiple sessions within the quarter. But it's actually given a lot of energy around it and adoption of saying, okay, may not adopt it, may not use that, but I'm becoming more savvy with it. And that is what I think organizations need to create those exchange, those teaming, those, you know, really cross-level hierarchy. So it should be hierarchy-neutral and generational-neutral to really be able to create that excitement and that shared learning.
Well, it helps people to see each other's perspectives, doesn't it? Because all those younger generations perhaps going, you know, about me, might be going, "Oh, Grandpa, shut up. This is the way forward. Yeah, you probably are going to lose your job. And look, the job that you're doing now is not the job we'll be doing in the future. And you're nearly done anyway," not thinking about the human behind that role perhaps. And similarly with the young bucks coming into the office now, maybe an older person's perspective on those people, that shared understanding, but also then the ability to collaborate and co-create. And in the context of all of those feelings and all of those backgrounds and all of those experiences, come up with something which is probably really good.
Yes, yes. And, and what it does, it also really dispels that anxiety and that fear because you are now bringing people and colleagues together across level, across organizations and functions for something that is kind of energetic, exciting. And, you know, now there is this competition about who can adopt it, what are the pilots going to be? But that's the energy that you want. And quite frankly, if you think about change management and you think about any type of organizational development or organizational effective initiative, that's what you want to do, right? You actually go where there's pull. You actually see where the energy is. And you actually try to really incite this almost kind of amplification through the people that are excited, have it, that you can then not force it on them. And that's where I think that there is a juxtaposition, right? There's this deliberate actions and effort that organizations have that we know we need to adopt it. We know that it is going to be the future. So literally everyone has an expectation to implement in some capacity. And that is where we are seeing the bottlenecks. That's where we're seeing the even pushback and the resistance. That's where we're seeing, you know, the ones that are going way out in excitement and then the ones who are absolutely— because I have had many examples of that happening, that there is just, "We are not doing it. We're going to do it the way the resistance." But when you are able to have and do these experimentations, go where there's energy, pull from the excitement, and then have a platform of exchange and collaboration, it then becomes something that, "OK, I'm not going to risk showing that I'm a senior leader and I don't have all the answers. And now, my reputation and how I'm actually viewed is going I'm going to have a risk of losing credibility or losing insight. But instead, it's almost that reverse mentoring and that like, OK, how are we kind of bringing it up? How do we spread this? How do we allow people to have that and encourage it, right? That encouragement. But again, I can re— I have to reiterate again, this has to be done after the organization comes together and says, this is the value that AI hat is going to give us. This is going to actually allow us to not only have the competitive advantage, but help us do what we do at a higher, much more focused and impactful way. That has to be done. Once you have that, that is your, you know, your route that your sales are going towards, right? And everything else will be able to follow.
This episode is brought to you by Inspiring Change. We work with senior teams to help them be clear and intentional about the culture they need to be successful. To communicate change in a more human way, and to give their leaders the skills, tools, and confidence to be amazing catalysts for change. To learn more about our work and who we do it for, just pop along to inspiringchange.ie. Well, I guess you've set out your stall, right? You said this is where we're going. This is, you know, it ties back in many ways to purpose and strategy because it has to. So, it's got something to anchor into. And we're just simply using AI as another tool to help us get closer to where we want to be. Okay, so it would be really easy for us two super positive people to keep talking about the fact that we can experiment and we can collaborate and we can intergenerationalize. Not even a word. But of course, there is the flip side. And the flip side is, and you talked about it there, the anxiety or the fear of what it might do in the workplace. And we know already, because we're hearing it, that the Big Five are bringing in less graduates, accounting practices are bringing in less graduates. Those jobs that you and I would have done in the very, very early days of our careers aren't really there anymore. And similarly, Dennis and I chatted about it last night, when we worked in PR in London, we would start off, somebody would hand us a very boring spec for a server or a printer, and we'd have to write a press release that made it interesting. We'd hand that to an account manager or an account director. They would redline it. We'd get it back and we would learn from the redlining and we wouldn't do the same thing again. What's happening now is that perhaps some of that early work is being done by machine, which means that when people like I was then get to become an account manager or an account director, I haven't cut my teeth doing those jobs.
Exactly. Yes.
So, so what happens?
Yeah, I mean, that is a reality. The way that we work is going to significantly change. The roles that we have today are not going to be the roles that we have in 10 to 15 years. Not optimistically, I'm saying, but, but just I do believe that that piece of it, because even what you say, giving the example that you had about writing copy and having the editorial position, you still do you have to have that human element to understand how it's anchored into the message and engaging that. And you can have that absolutely been machine-driven, but there's still going to have to be that element of human understanding, of connectivity, of intent that goes into that. And this is where our, you know, the students that are in college, the graduate students that are being used are really fostering. I have a daughter in college right now, and it is amazing to me how, one, they make sure with their assignments that it's AI-proof because they make everything very personal, personal. But what they're doing in their projects that they're given, it is so much now with the interviews, with going into data, with going to historical records, to understanding, to connecting, to looking at the human global citizenship and what's happening in other countries. Because I do think that our education system is really focusing on making whole and well-rounded, you know, human citizens that are just not going to go to machine learning. And I also, you know, would like to say with, you know, AI, and of course companies are bringing in to reduce headcount and looking at how to do work, you know, more efficiently. The reality is that AI is not 100% fail-safe. It is not. And those disclaimers are very very known, very broad, very loud. And so there does have to actually have some type of controls, if you will, and ability for organizations to bring those, whatever you want to call them, into your process. So when you're using AI, the efficacy of it is, and the integrity of the work that you're doing is not compromised. And that will be human, that will be led by people, by leaders, by managers who are understanding and will be the ones that have to make sure that the integrity of what you're delivering and what you're doing is not compromised. And so, this is the world. This is what we're living in. But I do think that you're going to see individuals and not only companies, but you're going to see more employees kind of co-creating their roles. The ones that are more savvy in AI, they are going to be the ones first at it and say, "Hey, AI does this, but this is what I I am delivering. This is how I am partnering. This is how I am utilizing it. And this is what the role should be. And I guarantee you, as we are going on in the next 18 to 24 months, you're going to see a lot more very tailored, structured roles that employees themselves are going to be co-creating because they're the ones that are intimately understanding and familiar with the mechanics of what they're doing, but how AI can support it, but also the value that they play. As individuals.
So, in the context of all of that, Weimar, one thing that struck me recently was that I think it's really easy to see ourselves as different to AI at the moment. But as AI gets better and better and better, actually what you're starting to see is perhaps that an agent could be working on my team isn't even a real person. Yes. But they're called Sarah or Bill, and they've got an avatar, and the avatar looks like you or me, and they speak with voice and they speak as a human and we can ask them questions, they can call us up, they can send us team messages as if a human would. And I wonder, when we get to that level of AI, is that going to make it harder for us to see the line between the human and the computer?
You know, probably so. I mean, it will absolutely make it harder. However, It will be interesting when we— when that happens, what the quality and the connectivity would be. What, if any, if there are going to be any difference or change. Personally, I do think that you will be able to actually see the outcomes, be able to assess the quality, the, you know, all of the metrics that you have from a customer service perspective, how that is either enhanced or limited. But here's also the reality, Scott. Some companies may not care. That may not be a rubric or a metric that they're interested anymore because they are able to accelerate at such a quick path with AI. That may not be a metric that means anything anymore. But what we talked about, to the point we talked about earlier, humans are purchasing, are the consumers here. At what point will there be a demand for more focus-centered customer service, patient service, more identity. At what point? I don't think that we're there now because there is this kind of excitement, the newness, this fast adoption. But once we get, I would say, 10 years, not even 10 years, I think it's probably coming in the next 5 to 7 years. And we're able to see the difference in quality, the difference in impact, the difference in outcomes. Then you will have really formidable metrics to be able to see where there is value and there is necessity and need and where you can use agentic models. Because right now I feel like they're throwing everything in the kitchen sink, everything in the bucket and kitchen sink. Everything is going in because it's that experimentation. But I do believe that that's going to come into a position where there has to be anchoring and enrooting and an assessment based on what are the outcomes How is this impacting what we do and how we do?
You think about those outcomes being driven by the organizational culture, then what impact do we think that AI and agentic AI is going to have on culture? And how can organizations either see that off at the pass or lean in to that so they can continue to build strong and engaged cultures that really deliver for their people?
Yeah, I do think that there literally now needs to be kind of leadership intervention. Where you talk about and organizations identify what are those leadership behaviors, what are the leadership expectations, you know, where do— are they most valuable within the work, whether it is pulling kind of centralized, decentralized functions together to really drive to the same goal, whether it is, you know, focused on a particular product. But that those behaviors and really identifying from a leader's perspective how they are using and what their expectation is. But also what we talked about, the experimentation. But where is that human-centered capability and value add? And that goes from the organization, but that has to not only be adopted but very well known. And just like we talked about inclusion, engagement, maximizing potential of every workforce, I believe every leader needs to make meaning for themselves. Because it's going to be different, right? You're going to have some leaders that not only are early adopters, but are good at it and can train and teach. But then you're going to have others that that connection, this exchange, this ability to have a real dialogue, to see facial expressions, to understand, that is going to be their magic, right? Their superpower. And there has to kind of be that balance of them. But I do believe organizations need to start with, what does that look like? What is the expectations? And how are you honing and developing leaders so that they can find it for themselves and really then support the teams and the development of their teams? And I also think that from, you know, individual contributors coming in and just like we saw, talked about earlier around particular roles now being completely be wiped out and no longer even in existence because of, you know, AI. How are you now still having a pipeline for development? Because you have to have, you have to have some talent left, right? And what is, and what are, what are those, what is that criteria? What are those skills? What are those, you know, really intangible things that is going to differentiate that you still want to have these individuals coming in? And even if there's not a job, still learning what those roles are, what those skills, what are the responsibilities so that they can grow into higher-level roles and really be able to have leadership impact.
Yeah, and imagine what it must be like working in an L&D role at the moment, trying to work out over the next 1, 3, 5 years, what are the skills that we need to lean into more? What do we need to be giving our people? What do we need to be taking away? It must be an absolute nightmare.
Yes, yes, yes. And it, but it has to be customized. It has to be relevant. It can't be something over the— and this is what my, you know, more concern right now is that I don't think it's customized. I think that it's a shiny new toy. Everybody's going to the store to get it and they're throwing it in and over or the place.
One size fits all.
Yes, yes, yes. But I do think that there will be a point that we get to that organizations will see we need to, we need to stop, right? We need to ground ourselves. We need to understand. What are we, though, going— are using this for? How are we expecting our workforce? And what are the leadership parameters and behaviors and expectations are we setting up to drive this? There is going to be— there's no way that it can't because in order for you to have efficiency and to use it at its highest value, that needs to be done. That litmus test has to be done. And the experimentation is still going to continue. But you have to have evidence to support In what ways? At what speed? At what level? At what adoption rate? And then how are you making sure there's shared learnings across roles, across hierarchy, that that traditional hierarchy between, you know, I'm the executive director or manager and I'm an individual contributor and I can't speak, those go away. So that learning could be really fueled and the momentum could be managed and really put at the Let's embrace it.
We're nearly out of time. One last question. And as you know from having been on here before, that I'm always a big advocate for practical advice and really practical takeaways for listeners that perhaps they could do this afternoon, this morning, as soon as they finish listening. But what do you think are some of the practical ways that organizations can build really resilient, high-performing teams in this era of change where we're hearing that, you know, there's no point doing any training that you see online because by the time that training was thought about, created, and published, it's irrelevant because the technology has moved on again.
Yes, yes, yes. I think from a practical standpoint, and especially where we are with AI and just the fast and furious nature that we are experiencing right now, the best things organizations can do is create a platform for learning and exchange. Create that interactive ability, that free-forming, that there is a consistent platform and environment that there could be learning, there could be exchange, there could be experimentation without any type of kind of forceful adoption. I think where you are able to allow and empower your employees and empower your organizations to feel free and open to talk about the experimentation. And I would also say, internally in the organization, but also in your personal life. Because maybe something that you can use, you know, AI, you know, can be a wonderful asset in your personal life that actually will help you do your, your life better. But I think that that would be the number one thing right now, because I think that learning is also going to help the organization be able to identify how the value and the importance of the value that AI plays in their strategy, their purpose, driven work really can contribute to that. So practical advice: create forums for exchange, collaboration, and shared learnings.
If you want to learn a little bit more about Weimah and her work, you can pop along to weimahoover.com. We'll put a link in the show notes, and we will also put in a link to the article that Weimah referred to earlier on around the, the sixth generation of intelligence. So I'm looking forward to reading that as well. Weimah, As last time, it's been an absolute pleasure having you on the podcast. Thanks a million for taking the time.
Thank you, Scott. It's always a great conversation.
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