[00:00:00] Hi, Steve and Vivienne. Thank you for joining me. Steven Vivienne are the co founders of premier design agencies, 500 Designs and Design Force, and they’re here today to talk about their journey to AI adoption. So with that said, I’ll hand it over to you, Steve and Vivienne, to introduce yourself and tell us a little bit about your role and your businesses.
[00:00:19] Hey, i’m steve the ceo co founder of 500 designs. Typically within 500 designs i’m part of the sales process I get on two calls or clients when they’re looking to figure out what their overall strategy is for their projects they just help on the on that side just to Make sure that we’re You know, setting our clients up for success, and then, of course, running the team.
[00:00:37] We’re a 120, 130 person team, and so working very closely with Vivi to figure out operations. And then we’ll suppose we’ll get into AI and how we use that later. But It’s over to you Vivi first.
[00:00:50] Everyone I’m Vivienne and chief creative and also operations. So I typically play in the intermediary of. And, it’s, fun being able to work from, understanding the quality side.
[00:01:01] So typically my day to day, goes from really, overseeing the work, of the team, understanding the quality and venturing into more around the efficiency side. So my. Key goal of what I typically do is making sure that there’s a balance between being able to be quick, but at the same time, also bringing across the quality of the team.
[00:01:19] So being in both ends, especially when it comes to operations, my key role there is to oversee what is working, what isn’t working and ensuring that there is , efficiency and drilling into the root causes and figuring out how we might be able to make something better. So that’s about it.
[00:01:37] Awesome. Thank you both, and thank you for being here. Let’s go ahead and dive right in. The, first topic of discussion today is going to be about your motivation for AI adoption. So Could you unpack that with us and tell us what prompted your agencies to explore AI what were some of the goals and challenges or client demands going into it that led you to this decision and trying to find an AI. Solution for your teams. I can start with this one so As soon as we saw this technology pretty early on, we immediately saw this as a potential disruptor for the agency space in general, some of the things that we saw I could do at that time. This is back in the early days of, chat GPT 3.
[00:02:20] 5. even then, we could see what I could do there was definitely Could help in certain areas of what we do, but the potential kind of forecasting how quick this could grow. We started to see that this could potentially disrupt a lot of what we do, and I would say disrupt is a I’m saying that in a broader way, in the sense that it could very much enhance what we do use the right way.
[00:02:41] But if we decided not to go down the AI and went, Oh, no, we’re humans. We got to do it the human way and not be assisted by technology. I think we would have been disrupted by those that were using AI very effectively. So it was a very conscious decision Vivi and I sat down and had a very deep conversation about how we’re going to think about this and very early on, both of us are, nerds at heart, like we love technology anyways, and anything that will help us, provide higher quality to our clients, as efficiently as possible sign me up.
[00:03:09] We’re there. It was a very conscious decision very early on, and then, what we thought, and maybe I’ll give a sense of what we thought was going to happen and then maybe what ended up happening. So we thought everybody would adopt this really quickly. We thought that everybody would be like jumping on and changing the process of processes and procedures really quickly and adapting a little bit with this, locking something down, trying it for a while, measuring to see the outputs, and then, tweaking the process at a later point.
[00:03:33] That’s what we thought was going to happen., the journey was not like that., when we first introduced it to the team,, there was apprehension and people felt a little threatened, to be quite honest, especially in the early days when people didn’t fully understand how, what this technology was. Once we got to a point of getting, everybody feeling comfortable using it.
[00:03:49] We started to see massive improvements across the board around efficiency, but quality being a huge part because of the depth we could get into projects in a shorter period of time, being able for certain key points of the process, being able to have all this information readily available the AI is able to.
[00:04:06] Once they comprehend, but it’s able to help our team comprehend it at a deeper level, therefore leading to higher quality outputs. and then, the result being even though that had a, an impact, we figured, okay, there’s a new process. This is how we’re going to do this going forward.
[00:04:19] But honestly, the technology moves so, so quickly, and we’ve been advancing in areas that, we could do with Aurora specifically, that we’ve been constantly now improving and tweaking and applying new things and evolving with the technology as it goes. so that’s my kind of the first part of the question.
[00:04:36] But, Vivienne, over to you. Is there anything you want to add to that?
[00:04:39] Yeah, we first found out about, AI or gen-AI. In general, one of the key things that came into our minds is especially for from my opinion or from my side when I’m looking into AI. The biggest part is I’m looking at the challenges because I’m so ingrained in operations.
[00:04:58] And also, the day to day on how the team works on projects. One of the key things that I’ve constantly seen and also battle around is we, as a company, we have a specific goal that we wanted to achieve. There’s a specific number and where we want it to head to, but, at the same time, also when it comes to.
[00:05:17] The work itself. Sometimes it takes a lot of time to get through to the next side. But then now we are basically measuring or looking against, profitability versus the output and also the cost of running the business itself. And so the reason why agencies, or at least for us, it is so empowering to hear.
[00:05:37] And, like when we first heard about Gen AI, it’s so eye opening. It’s the amount of time it will take to be able to get to an output as compared to just manually working on it. through it ourselves.
[00:05:50] One of the key places that we see again and again, is team members getting stuck with not knowing the solution to get to the next step.
[00:05:58] There’s, like it’s the work itself, it’s getting from A to B. So having, Gen AI or having some if you need something to be able to help support that it makes it so easy now, instead of, let’s say, two weeks of work on brand strategy or anything like that, because of how easy it is that our team members are not stuck on, let’s say, Not having an answer client or not needing to go back to a project manager, needing to go back to the client, being able to tap into specific knowledge, being able to utilize AI, to jump straight in, to get an answer and then unstuck themselves and get to the next step in their way, it just creates a fluidity.
[00:06:34] In work, so that was the part that kind of, the aha moment when we saw, gen-AI, at the very beginning, it’s just how quick we are able to get to without putting too much cognitive load in work. We do.
[00:06:46] All right. So this is a good segue. You guys were alluding alluding to some of these in, your previous responses, but let’s talk about some of the pain points before AI adoption and drill into those you mentioned operational.
[00:06:57] Bottlenecks. That’s a challenge. Maybe expand on that and then touch on some of the other challenges that you had before adopting AI and what that looked like.
[00:07:06] Do you want to start on this one, Vivi? Yeah sure. So Before AI, so there is for an agency, right? The delivery team is what creates the output or the delivery of work and what they do whether it’s efficient or not plays a huge role in the outcome of the company in general.
[00:07:25] How we typically dissected is that we have the administrative team and then the delivery team. The delivery team typically works more closely with the clients being able to deliver the projects and the administrative team typically works. It. That includes HR operations. Finance typically works around to help support the delivery team to do a better job.
[00:07:41] And whether it is jumping on into review a whole entire process of strategy all the way to design to the delivery of the project in development stage, that’s all intertwined with each other. So as a remote agency. One of the key thing is that we have global team. Everybody is all in different locations.
[00:08:01] We hire the best. And the key is that if when we have the best team that we have compiled, the biggest challenge that we can’t change is time zone and what time Prevents us from doing is being able to get information in real time. In that stage where, let’s say, for example as onboarding our clients at the very beginning and not being some team members not being able to directly access clients means that they’ll have to either.
[00:08:25] We watch a video or a recording of the meeting or getting second hand information. However, this is the challenge that we typically see. It’s not just about the the ability to pay attention to the video, but it’s also about human psychology, right? Because every single time when we are coming when it comes to work, it’s not just the work itself, our own mentality, our mindset comes into play and what happens.
[00:08:48] sometimes is that if information is not firsthand given sometimes we weren’t able to immediately grasp the idea because there’s not ability to ask the right questions to get to the aha moment quick. So I have noticed that sometimes our team has questions, but not being able to ask until the very next day when the project managers jump on.
[00:09:08] Board and provides them with the answer, and then they would be able to get it. But when they got it, it’s already a daily. And so that is something that we have been constantly Meddling with that’s just one example. Of course, there’s many other things when it comes to the timeline or timing of work.
[00:09:22] And in the remote company as well, communication being able to understand something requires someone to not. Being able to just tap onto another person’s shoulder and say, Hey, could you help me with this items here? It now depends on the other person replying to that email or that message.
[00:09:37] And so that’s the challenge that we wanted to solve. And with. AI or with Gen AI being in place, that really does change a lot because now having that information, because typically when it comes to, let’s say onboarding our clients, we have the discovery documents all set up. And we have all the transcripts from clients and everything all as a knowledge bundle.
[00:09:59] As long as we are able to utilize Gen AI our team is able to grasp information and knowledge a lot quicker. One of the key things that or at least this is what our the work that we do typically, it’s not e commerce, which is very easy to grasp. It’s anywhere from fusion in technology to understanding the that science behind how biology works to technology to different.
[00:10:22] Fast, advanced and deep understanding. The deep knowledge type industries. And so getting our team to comprehend all those in a short amount of space without AI is Impossible. It typically it used to take at least a week, two weeks to on board to really, truly grasp everything before the team can actually start working.
[00:10:44] But now with Gen-AI being able to provide an understanding to the team, provide inspiration, provide a way to create and craft with the knowledge that was given to them. It just makes it [client onboaridng] so much easier. So as I mentioned earlier, it went from Two weeks of brand strategy deliverable to becoming two hours or three hours to be able to truly grasp how to actually get a very good high quality brand strategy equivalent to the time that was spent two weeks in the past.
[00:11:15] What I can do is maybe share some actual practical things like that are like you mentioned, but ask for the bottlenecks. I can tell you like some of the ones that it’s had the biggest improvements on just very quickly.
[00:11:24] So I’m going to start with the very starting point of engagement with an agency and a client and that’s the sales. It helps on marketing too, but I’m just going to go to the first conversation we have. In the past, we would be relying on notes from calls before we had, AI note takers. Now we’re able to take a transcript and bring it, build it into Aurora and create a entire proposal in a matter of minutes.
[00:11:44] In the old days, I would have to read through deep, sometimes 30, 40 page RFPs to really understand what the client needs. Now I get Aurora to do it for me. And I just verify and check important pieces of information. As a result, our. Sales proposals are created now in a matter of minutes, not hours or sometimes verified over a couple of days to make sure that multiple people look at it.
[00:12:05] It can now be done by one person, not two people or three people verifying it. And then the quality of getting them right the first time is they’re always right the first time. In the past, we would go and make a proposal and they’d be like, Yeah, we think we might need this as well because something was just overlooked on a conversation that didn’t seem like it was important at the time, or somebody just forgot to add in something simple.
[00:12:25] So that’s a very practical example on the sales side. On the onboarding side, as Vivienne was mentioning, the time it took to get team up to speed was a bottleneck. Now, we do that by building all the the onboarding materials into Aurora, so everybody has access to the same knowledge, and you can break it down.
[00:12:39] What’s the most important thing? What do I need to pay attention to? And ultimately, instead of we have, which happens to, but a director level person spending hours going through and comprehending everything to a point that they could cleanly communicate and under can we communicate it to their team?
[00:12:53] So everybody is working from the same knowledge. That’s no longer required. Aurora now teaches all of our team the project so they are up to speed on the project in record time without needing a director to go through it and verify. So and again, this is done very accurately because the A. I does not make assumptions.
[00:13:08] It is. It is working off the information and then The frequency of repeated information across the knowledge talks. So all that context becomes super valuable on the creative side. Now it opens up to, okay. Based on all the knowledge, give me some ideas of places to start, which massively reduces procrastination.
[00:13:24] Because sometimes if you’re ever faced with a very complicated project, no need to get it done. It’s oh, let me check my emails first, because I better make sure there’s nothing that’s going to distract me. Let me just go and check the mail like, down the road and I better walk the dog before anything else.
[00:13:35] And I dive into this because you’re really just nervous about getting started. It can happen to some people. So this is just help me get started. Where do I start with this? Give me some ideas as a starting point. And when you see those ideas, it’s wow, that’s super cool. I got it. Okay.
[00:13:47] And now you’re inspired to get. Action. Now you enjoy what you’re doing. So things get done faster by removing that initial like apprehension or anxiety of getting into a project in the first place. The other thing, which is a great example. I won’t name names. This is one of our honestly, a world class designer.
[00:14:02] One of the, I genuinely think one of the best in the world. But when it came to communicating the ideas back to clients. She struggled initially because it was something she hadn’t practiced very often. And then I remember jumping onto a call with a client and I was just there in support. It was a very complicated project and oh my God, did she nail it?
[00:14:20] And I remember jumping on. I said, wow, the difference between a few weeks ago to, to where you are today, how did you do that? And she said, oh, Aurora did it for me. I was like, what do you mean? And she said, what I did was I said, here’s the creative output. And then here’s the points that I want to communicate, go back and look at the research material and connect all the dots for me, and then give me a simple way to explain this to the client.
[00:14:40] And so she said, because of this, and because of this, and because of this, hence I did this, and then I did this, and then I did this. So this is the result. Does that make sense? The client was like, love it. I love that you connected like it back to the research. So to do that in a a standard I guess the standard, the traditional way.
[00:14:55] Would take that person hours of going through the research and really finding the key points again to connect the dots and then preparing her speech Aurora did that for her and in like seconds Or you know what? I’ve heard a lot from the creative team is just stuck as Vivienne said on questions I’m not sure what I should be doing here.
[00:15:12] I don’t have to go and read and try to find what was mentioned in a document anymore. I just asked the question, can you tell me and remind me what the persona was and what is there? I guess key pain points again, and then boom, there’s the details. And then I can ask a separate question. I go deeper and that is keeping all of the other materials that are reference context for the project.
[00:15:28] So it’s not just answering a single thing about the persona. It’s keeping that in mind with the overall objective of the project and all the other pieces that connect into that, but contribute towards a conclusion, which is incredibly powerful to the QA side where it’s verified or checking the team can grab a screenshot, throw it in and say, proofread this for me.
[00:15:44] Boom, there you go. Done. There’s a nice mistake there. That one should be capitalized. Like that just saves hours on the QA side and the copywriters. And then even down to the project management from planning, coordination messaging. One of the team again, no names, but one of the team was I guess back from a vacation, had this gigantic long thread of all these messages that went backwards and forwards by, but the creative team and the client and multiple people in the client copy and paste the entire thread into the project folder on Aurora and just said, get me up to speed.
[00:16:14] What’s completed, what’s outstanding, what are the to do lists, what’s important that I need to know. And then Cool. Here’s a concise thing. Here’s what’s important to you. Here’s the things the team has completed. Here’s the things that are outstanding. And here’s what’s important to know. So you could be back up to speed instead of having to read an entire email tread.
[00:16:29] Now you just go back into the pinpoint parts to find what’s relevant and important to verify what you’re currently seeing from the A. I output. So that’s it. I’m scratching the surface of the things that we’re able to do with this, but they’re just practical examples that I see very directly that has transformed the speed that we can operate with AI and Aurora.
[00:16:48] That’s incredible. You obviously have a very deep understanding of the agency operations and that side of things, and you’re seeing its impact, AI’s impact across the entire operational system. So it’s not just marketing, it’s not just sales, like if you’ve done it, if you do it and you do it right, you get benefits across the whole thing.
[00:17:07] No, absolutely. It is a new way to operate. The old way to operate was fragmented and it was siloed. The new way to operate is you have continuity across all of your material. And I’ve left out just me in my role. The things that I use within my personal workspace that make sure that everything from writing a job description, perfectly on point for the, what we need to the objectives to give to that person, to the onboarding plan that used to take me hours to do.
[00:17:33] And I was just like, Hey, can you just help me do this? Okay. There you go. Send it to the person. We collaborate in real time right there on the document. And then we got clarity and it’s okay, great. They say that in their workspace everything they do while they’re getting up to speed. There’s so many use cases across the entire organization.
[00:17:47] That’s, this is it’s just the new normal. That’s the way I would describe this. Amazing.
[00:17:52] Okay. Clearly you didn’t get here without overcoming some challenges. And during that phase where you were trying to figure out, okay how does my agency adopt AI? What should we use? What solutions are out there?
[00:18:04] Let’s talk about the selection process and the decision making behind that. So how did you approach? selecting these AI tools and or platforms that you’re using. Did you experience experiment with multiple solutions before finding the right fit? And what were some of the key factors that did influence your decision when it came time to make one on what tool to use?
[00:18:24] Great question, I can start that one. So in the early days, it really wasn’t the one that was effective. It was chat GPT as a broader tool. We spotted weaknesses immediately and for how we operate. So the challenges there was it’s continuity and consistency.
[00:18:38] So working with some of the biggest brands in the world, we cannot rely on that tool. And also we have to be very careful. We couldn’t be putting anything proprietary information onto it. tool that the AI might learn from. So it was very immediately for us. We realized we needed to build a more effective tool for the way that we actually operate.
[00:18:53] And I will say one other quick thing on this is that I think a lot of the tools today are, they’re incredible and they’re so helpful and they’re all. Great at doing these pinpoint things, but what we really struggled to find was a system where, AI was just integrated into the way that teams actually operate in a way that it was there across from like I mentioned, onboarding the whole way down to QA and every part in between, so that there was this continuity across teams and this collaboration across teams that was easier to do.
[00:19:21] So that became a key requirement for us. On the that’s on the operating system side. And any advice there I would just say is to try a few things. Don’t be shy. Don’t be afraid. And there’s no, I guess there’s no gain without some level of pain, like there is going to be onboarding pains here.
[00:19:36] There is no doubt about it. If you want to just turn on ChatGPT, or, just tell your team, Hey, just use this and away you go in it. You’re going to see quick benefits for sure. And it’s easy. For sure the pain though is going to become very apparent when you’re six months or eight months down the road He become very reliant on using their old methodologies on these kind of newer platforms, but then there’s that continuity starts to be missing The way that themes work together.
[00:19:59] It just doesn’t quite, it won’t gel as you start to see end to end on projects and then it’s tricky to move around and swap but I would say that trying tools is a key thing. And the more investment you have, like in time and energy to figure it out so that you really understand the key benefits, what it should be used for and you know where it’s beneficial for the team.
[00:20:22] I think that’s really for us. It’s been a function of the leadership team for me for Vivienne for all of the key leads of different departments across the team. We just challenged them and said, yeah, Figure this out, guys. Just go grab a tool, play with it and and just make sure that it’s it solves the problem, but it must integrate with us with the way that we operate.
[00:20:39] So that would be a key requirement for the other tools. Say simple. First one that we did was the meeting. Price. Factored into it for sure. But it needed again to be accurate, needed to not like hallucinate. It needed to give a convey what was communicated and just be a simple and easy tool to use.
[00:20:56] So it just felt like it was a simple for us to pick it up and just start using it today, tomorrow. So those sort of simple tools. That was the key on the visual side. We do play with technology there, mainly to augment what the team does. So within the likes of Photoshop, for, AI assisted, removal of text or whatever the case may be, or using the most more recently Google’s AI studio and playing with the kind of image creation there.
[00:21:20] It’s useful. It’s, it can be inspiring when used right. You can do full campaigns with it. I think at the moment though, it’s probably still faster for our team to go and do a lot of those things. On the, like on the visual side, they still do it. manually, but they can use some of these tools for inspiration or direction or quickly trying ideas.
[00:21:40] Each and here’s how I would break it down. And Vivi I’d love your thoughts on this as well, but I break it down into it must meet these key requirements. It has to be the highest quality. That is something our clients will be looking at and go, wow, you blew my mind. That’s amazing.
[00:21:53] If the AI tool doesn’t get you there. It’s how can the A. I. To assist us to take a little bit of time away from parts of the process so that we can create something that’s spectacular. With the team that we have. The other part then, as we start to drill back to things that are more easy on the strategy side, again, quality must be there.
[00:22:09] It must make sure that the team can collaborate and work well together. It has to be something that we can scale and build our business around. If we start getting into that level of kinda collaboration, it is, if it is a tool that will solve it for one person, for one specific. use case for one specific project.
[00:22:26] It’s just a one off purchase. And yeah, fine. That’s okay. But if it’s something that we want to use it in our the way that we operate we definitely want to make sure it’s a collaborative, easy to integrate and has a large improvement across quality and efficiency. Yeah. I second that as well.
[00:22:43] I think Steve has covered most of the points as well. So it’s more around what is the item that will be able to help us scale into the future. So not just thinking about a system that lives today and dies tomorrow, but something that can lives on with us as a company to grow and venture and scale into the next size that we are heading towards.
[00:23:02] So that is one of the key important features to look at. And at the same time, flexibility. When I’m saying about flexibility, it’s how flexible or scalable the tool is going to be growing in the future. Is it able to integrate with other processes? The team is currently doing. So one of the key things that when it comes to choosing a tool is how much.
[00:23:24] Impact or destruction. Will it actually cost the team? One of the key things that we wanted to think about when it comes to a new tool introduced to the team is because they already have a lot of work their day to day in work that they do every single day. And there’s a specific process that they are ingrained into their minds.
[00:23:41] One of the key things that we always wanted to think about is How difficult it is for us to make sure that we can ingrain this new tool and concept to the team? Is there a small learning curve or is there a big learning curve? And so those are just a couple of things that we look into One last thing, just to add to this, cause I think, as we’re going to say, that’s just popping in my mind.
[00:24:01] I said it early on, but I just really want to stress this point. It is cause it is, it’s critical is understanding the investment that you’re making and understanding that, with all new technology, you start to adopt it. There’s, as I said, there’s a pain point first, like it, it solves things, but it’s also painful, but what’s really painful.
[00:24:19] Is getting the team up to speed on how to use this new technology and not feel afraid of playing and experimenting. And so that is one of the greatest investments that it took us to make was to get all the team right on there and really teach them the core skills, like analytical skills, creative thinking skills, system thinking and up and ongoing process.
[00:24:39] So that they could, apply that and use the tool to its greatest advantage. And when we started doing it, there was a moment like, are we too early? Is this kind of crazy? Should we just keep on doing what we’re doing? But we pushed through and oh my God, am I glad that we did. Because where we are today, as a result of that early investment, yes, it took us six months to get to a point of fluidity is it perfect now? Absolutely not. But we have now got the right foundation to build on so that as new technology and tools start to evolve and get even better. We’ve got the fundamentals dialed in like the team are ready to go. Oh, we can do that now. Fantastic. I see where I can slot that into our process for me.
[00:25:15] That is the critical point. So just know it’s an investment. It’s not instant gratification. There’s elements of instant gratification, but it does take a bit of time. That’s ironic, with AI when you’re chatting with it, the response is instant and it feels great, but actually changing the way you operate in the system as a team to build that AI foundation on a scalable infrastructure That takes time. That’s painful. And it doesn’t happen overnight. I watched as an MIT professor talking about this on YouTube. And he said it perfectly. He said, technology moves so fast. But organizations move very slow, and that is it takes time for people to change their habits, and that’s really what I’m talking about in that investment.
[00:25:52] So the technology is going to continue to evolve faster than we can keep up with it. So it’s what you do with the fundamental foundational sense that’s what’s going to create a massive impact in the future. So get your team ready is the lesson learned. It’s so so true, and that’s why having a platform that is user where they focused on UX, they focused on making it so easy to dial in for the users when they jump on.
[00:26:14] It’s more just about the learning that they need to get through, but not being bogged down by the UX or the product itself. That is such an important point. Awesome. Yeah, I feel like every time open social media, there’s oh, this cool new way I tool and it’s all razzle dazzle. Yes, I want to click on that.
[00:26:31] I want to try it. But is it actually going to help me? My team? Is it a long term solution? Or is it just going to help with these one off tasks that I’m working on? So there’s a lot of noise to cut through. And that can be challenging, especially for decision makers and leaders within companies who are trying to champion AI and make that change happen. All right, let’s move on to the next set of questions here. Implementation and challenges faced when implementing AI. So you selected your AI tool or tools that you’re going to scale with your team and build into your agency process. What were some of those obstacles when implementing it with the team?
[00:27:07] Did you face any resistance from employees or clients? How did you address it? Were there any training or technical or ethical concerns that you had to resolve with your team? Let’s unpack all of that. The whole actual implementation journey after you’ve selected your tool or tools and what that looked like.
[00:27:26] So a great question. When we first started it, we were very excited. We wanted to be able to bring everybody up to speed because we can see how this is going to change their lives. It’s going to change our lives.
[00:27:38] But ultimately, I think it’s going to change their lives because of the biggest pain that I see with the team. It’s the cognitive load that they have on every single project, because sometimes they will work 10 projects, 11 projects, not to say it’s at the same time, but they have to hold that information in their minds.
[00:27:55] But that’s not something that is helpful for them. And it’s also Potential to getting to mental fatigue. So where I see the power of AI when we’re we’re seeing it implementing, or at least we’re envisioning it implementing to the team. That’s basically, that’s going to change your world.
[00:28:10] But I think there is. A snag in there, you forgot that there is actually a fear that’s still in mind what if AI is going to replace my work? What if Oh, the company is going to fire me in a couple of months because it’s going to replace me with AI. And to be honest, that is not possible.
[00:28:26] And that’s not what we’re, our intention was. And so the biggest challenge that we faced at the very beginning, as I can see, Steve was nodding away with this. It’s just changing the mindset from. Oh, AI is going to replace me into AI is going to enhance me. So that’s the part that I think because of the unknown, because fear. Kept us alive this long. And I think that’s the fundamental thinking when there’s a unknown that was set in place. That was the first thing like, okay, it’s going to harm me or hurt me. But to be honest, what? What happened as we’re trying to get everybody to the next level?
[00:28:57] I think the biggest Biggest aha moment for us is to help the team understand what it actually does and what it actually isn’t. So that is some of the key things that we and the key components at the very beginning, what we have to build, which is a foundation of thinking, what does it do? What does it not do?
[00:29:13] And at the same time, not only just that, paint the picture of the future of where it’s heading. And why it’s so important for the teams to learn and empower them to learn as much because we are at our company, our goal is to be able to help every single team member enhance and reach their potential.
[00:29:30] And so in order to get there, it’s not just to stay comfortable and with what they know and doing what they love, but it’s also continuously doing what they love, but continuously challenging their minds. Challenging themselves to learn new things to grow in new ways up and making sure that they’re able to stay relevant and in the future down 10 years, 20 years, that’s where the world is going.
[00:29:50] It’s going to be AI enhanced. And so in order to do that, the team has to match their game or even be better than what the market is at the moment. And I think that is the biggest mindset. If I’m going to sum up everything, that’s the biggest thing to say. It’s the mindset. Once we overcome the mindset.
[00:30:06] Everything else becomes a lot easier. The learning, the teaching is not the challenge. It’s the mindset. Yeah, and to add to that then really just continuing from what Vivienne said I can it’s funny I actually got emails when we first started rolling out like we’re using ai for this now I got emails from our team asking me steve genuinely.
[00:30:25] Will I have a job in three months? I remember reading the first time I came along and my eyes are open Why did I say that made them think they won’t have a job like because to me this is not a we cut our team moment. This is wow. We empower our team moment. And if they get more time, they can take on more areas that they can learn and train.
[00:30:42] They can be more thorough on their projects and spend more time without being stuck in the weeds on the stuff that is administrative or is manual, that’s. I can, significantly replace. So I think that was an interesting moment as we started to adopt this. But as Vivienne said, it was clearly the mindset and I just, as that’s what we did to resolve this.
[00:31:00] We, we did, sit the entire lecture in all hands, we sit. So everybody now, but everybody’s at the all hands and we had a discussion around where, the jobs market is going and we use data to as we were assigned, more a strategic backed agency anyway. So we’re doing this on ourselves, but we use the data to suggest what is happening in the industry, what is happening in the jobs market why it’s so important for us to stay ahead of this.
[00:31:22] And we drew the main conclusions of why this is beneficial for everybody. So that was one of the first things we did to let everybody know that, we’re not crazy here like the rest of the world is going this direction for the ones who don’t necessarily always pay attention to technology trends.
[00:31:36] This was somewhat eye opening for them. The second thing we did to change my mindset is find the A. I champion for every department. And for I think for us, that became where we went from a let’s see how this works to an organized approach to adoption with the AI. Champion. They’re, tasked to figure out how to use a I effectively within their team.
[00:31:59] They’re the ones who have to, chapter their team and say, Hey, you Teach me like what have you been doing? Show me some cool things that you’ve been using, encouraging them to play and to explore and to it’s not bad to find faster ways to do your work. That’s actually a positive thing to do.
[00:32:13] So don’t be afraid to say I’m What’s going to happen if I can do my job that used to take eight hours and I could get done in two hours? Like I can’t tell anybody that so we turn that narrative around to celebrate those moments and not to try to hide those sort of things So just have the conversation let’s bring it all out and workshops and you know this is only the beginning really of you know the exploration side for us, but Workshops with ai champions leading those and giving the team challenges right there and then and say, okay Here’s a tool Go figure out how to use this.
[00:32:39] You’ve got 20 minutes to do this. Go have some fun with this and really be celebratory around using this technology. And that has been, I think, the way that has changed the shift in the mind of Oh, my God, I’m like, should I be scared of this technology to Wow, this is what an awesome time to be alive.
[00:32:55] We should play with this. We want to learn it more and just become like all AI nerds. That’s really what we’re starting to become now. 500 sites. That’s awesome. So what I’m hearing is there’s a mindset shift that you have to change internally with those who are all about AI and then the ones especially that aren’t who are fearful of A.
[00:33:13] I. And then there’s a leadership shift where leadership needs to Take on the role of enabling their teams and AI champions within those teams to help the rest of those teammates get on board and get excited and feel confident to explore those tools and feel like that they’re not going to get replaced.
[00:33:30] And then there’s an educational shift where you also have to. Help your team, not only learn about the tools and the possibilities out there, but also how to use those tools. And you do that from what I’m gathering is just by playing around, seeing what works, what doesn’t and then working as a team as a group to dial in those processes.
[00:33:47] But let’s drill in on that topic before moving to the next one really quick. Let’s talk about the educational piece here. With AI tools, the AI tools that you have adopted, like, how are you keeping your team up to date on how to use them? There’s a huge learning curve with every kind of tool or new tool that you’re going to implement across your organization and for different teams.
[00:34:08] But with AI, especially being so new and so fresh, like, how are you keeping your team informed and educated on how to apply the tools and the systems that you built or created with AI? Great question. So I’ll start on this one for In the early days, it was truly, I would say, inspire the team because yes, there was a few people that were very, AI engaged in the early days and, as those conversations are happening and we were discovering new ways to apply it If we can, if this is not something you could teach, like you can, of course, and say Hey, just follow these instructions.
[00:34:44] Step one, do this step to do this, but you really have to know how to prompt and to go backwards and forwards and to explore and understand the boundaries. And the only way you learn that is by doing so. If you try to, instruct somebody to follow those instructions, I can guarantee you their output will be poor or weaker by comparison to somebody who really understands what they’re doing.
[00:35:02] So many times I will be jumped up, jump on a call and with a team. And I’ll do something and like we’re communicating something and. Then we’ll take a moment and I’ll just say, Hey, let me show you this really cool little thing I just did and show them something that they just didn’t know how to do before it happens pretty much still to this day where I could be the last week we had a call with HR team and right there and then on the call.
[00:35:22] We asked the team, so how did you do this? Like, where did this come from? And then they showed like the way they used to do it in a more traditional way. And then this, then we shared screen. In fact, Vivienne shared screen and said, let me show you something really cool. And got excited about it, showed the enthusiasm and then like on screen, just demonstrated you can do this and you can do this and this.
[00:35:37] And because knowledge is here, tagging this and tagging this with this sort of prompt and teaching the method behind the prompt. And then when they see it, jaws and eyes, I just wasted three hours and Vivienne did that in five minutes. You kidding me? So now they’re motivated.
[00:35:50] So that is a different approach to training. I think it’s a good approach to training anyways. But I think Gen AI, because of the, it’s low technical knowledge required to do this. It really means, makes it acceptable to everybody. So all you need to see is this little bit of inspiration and go, I didn’t know I could do that.
[00:36:09] And now when you see and you try to do something like that yourself Everybody is a you know their own creative genius. They will start to say wow if I could do that there Maybe I could apply that same method by using this Relative or this context or this knowledge and let me try this and then they start to see More and more possibility.
[00:36:25] So I would say as a starting point that’s been the key thing is inspire the team, not teach the team. Second of all, I think the the workshops where again, in that scenario where you have a Like here is an objective that we want to achieve. We want to do this using AI and only AI go play have fun.
[00:36:44] So learn by doing in that respect I think is a is a very helpful one And then there’s definitely certain areas that let’s say it’s a core leader And there’s somebody new joining the team who doesn’t There’s not up to speed with the overall process and the procedures that we might do and it’s very complicated things So that’s where we build out these smart, flows or smart workflows because here is all of the knowledge of the most senior people on the team instructing the A I that this is the framework to use.
[00:37:10] This is how you look at knowledge in order to conclude something which leads into the next step. And that conclusion from here feeds into the next part. Now you knew new contextual information from knowledge or you create something and you add that to knowledge. And then you work with that in the backwards and forwards way.
[00:37:26] Those smart flows are really helpful then to teach the team as well, because one, they’re learning our methodology. They need to understand a little bit of the framework, but behind the scenes, the skill level required to execute at the most expert level. From somebody who is maybe say on the way up there that gap now is very much divided.
[00:37:44] So as long as you have a very strong base methodology or an approach, you can empower somebody who’s a little bit more junior or still getting up to speed to execute at a level that they just couldn’t do without having somebody literally over their shoulder and say no, that was the wrong conclusion.
[00:38:00] Let me show you how you can apply this in a different way. The AI is very powerful there. And then I think. The other thing I will say here is we’re still learning. Like we have definitely not cracked all codes for everything. I think we’ve done a solid job so far, but we could probably have done better.
[00:38:12] And I’m sure we can do better in the future. This is a constant learning curve for us. And as I mentioned earlier. I don’t think this is a evolution to a point where it’s okay, this is the new future. Let’s just do this. I think this is going forward is going to have to be this constant adjustment that technology now enables this.
[00:38:30] Oh, let’s replace this one extra step in our process. With this. Oh, we can now do this. Wow, we should just change that on this in order to speed up the process or increase the quality or just make it more fun for the team to interact with. And that’s why, again, going back to important to have that fundamental platform that we can build on top of rather than trying to, always use these fragmented tools because they’re just not connected so well.
[00:38:51] But yeah, I think that’s it on the educational part from our side of what we’ve observed and how we’ve resolved it. Over to Vivienne. Anything to add to that, Vivienne? Yeah, I think the other part that we do basically agree with everything that Steve says. It’s just more so about conversion and divergent thinking at the moment, because at the end of the day, what Gen AI or AI tools are here to help us do is to enhance our output, whether it’s more efficiency or better quality.
[00:39:16] So with that said, one of the things that I think it’s helpful for the team is with The champion with many of the other influences to help them spark inspiration to get to the next level. The goal just what Steve say is not to limit the team on anything that they do at the moment. So it’s more like the divergent thinking at the moment.
[00:39:34] So it’s more Hey, just do whatever just be creative, but remember the output or remember the outcome along the way we’ll start we’ll we came across frameworks that would be able to help the team to become more of a convergent. Thinker because it’s important to think big and think small.
[00:39:52] So think big is we the goal is to be able to try as many different solutions. To find a pattern once you start finding the pattern now, you can be convergent thinking now You see the pattern to be able to create a framework to start guiding the rest of the team So that’s basically the stage that we are at is just to allow the team to be as creative as possible To find patterns to find ways To to make something better, having that goal in mind, but not limit them into specific systems in place at the moment, because that’s not the right time at the moment, especially in learning a new tool that is so destructive, that’s basically what we’re doing.
[00:40:28] It’s just learn as much and then we’ll go from there. Awesome.
[00:40:32] Those are amazing insights. And throughout your responses you were, it sounded like you were alluding to some very specific features within specific tools, which is a good segue to this next set of questions. Let’s talk about the A. I. tools and solutions that work for you today. So what did you land on? Tell us about the tool you’re using or the tools that you are using in which departments have been positively impacted. Okay, cool. Great question for us I mean the most important one was the foundational tool I mentioned many times earlier that making sure we have a tool that we can build on top of is critical and Something that we can easily collaborate and that works in the flow of how we operate as an agency was critical for us So we use aurora.
[00:41:17] So hiaurora is The URL, I think, but it is what makes it really powerful is that every project, every team, every client that we ever take on basically has its own workspace on there. And so in that space we can add in all the documentation, all the onboarding materials. We can load up all the smart flows that we’ve been building on there as well to help our team execute these various different projects.
[00:41:38] But on there, and this is why we love this tool, is that once you’re working with intelligence, which I think it’s it uses the open AI latest model as the intelligence layer. But once that is, you work with the knowledge and intelligence, you can easily create documents right there onto the product. And so on the document side, it’s like real time collaboration.
[00:41:57] So people can be working on it at the same time. And it works like Notion. It’s like a Notion doc. So very easy to just, add sections. It’s like a block editor essentially. But then what’s really powerful is I can actually turn that doc into an knowledge doc. So it can either sit there as an Aurora doc, which is just like a We’ll call it a dumb document unless you tag it.
[00:42:14] But if we put it into knowledge, it’s now contextual information for every other conversation that we have with intelligence. And for us and the sort of projects that we work that’s been the game changer for us. That’s the part that speeds up everything because I go into the workspace on a particular project have the sales conversation in there.
[00:42:30] Have the transcript for onboarding calls in there have all the documents that they shared that the onboarding documents that they did what the team has been concluding so far, and I can just go in and ask get me up to speed or I’m jumping in on this particular point like. I want to, get me summarized on the competitive analysis, the market analysis, the persona analysis and anything that the client said on the previous goals that might be important for me to know during this, whatever I’m working on and then just boom, like there you go.
[00:42:55] It’s everything is right there. And then. And then a feature I’m really looking forward to is the presentation creator. So then I can, once the knowledge doc is there, we build out the say, a brand strategy, just click on, turn this into a presentation and, the presentation is done, send it to the clients, leave comments, like all that other stuff.
[00:43:09] It’s very powerful in that respect. Aside from that, I think on the image creation side, mid journey. I will say I’ve seen the journey fall behind a little bit. I think Google is starting to step on their toes now with the most recent version of Gemini Flash 2. 0 for imagery. It allows you to do more modular based things.
[00:43:28] So Vivienne and I were playing with it just yesterday and we did, just a particular graphic and then we can add to it, take away from it. We can it’ll keep the fundamental Or focal points. I create a cat like the cat that’s there. If it’s a photorealistic cat, that cat stays there.
[00:43:42] I say, okay, put a hat on the cat. It’ll keep that exact cat and not change anything. It’ll just put the hat on there or I can bring in an image with with something and I can remove all the text. Like that sort of stuff is pretty cool. For research, open AI is deep research. Very cool. So we can do competitive analysis, market research and find all the sources really quickly.
[00:44:01] And then for kind of Shorter, typical things. Honestly, I think the Aurora does all of this anyways, but sometimes will the team will just go into the free version of perplexity, but just that one quick, double check sort of scenario where they want to find certain sources and just make sure that they’re going in the right direction on that side.
[00:44:20] On a personal side as well, I also, I like the ChatGPT voice, so I can actually just turn on the voice when I’m in my car, and I’ll just grab the notes from that conversation, so I’ll be just thinking about things and just getting it to take my thoughts and organize it for me, but as soon as I get back home again, I just copy and paste and put it into Aurora, because it’s more powerful for me in Aurora.
[00:44:40] At least it works with all my other knowledge. And so yeah, I think they’re pretty much at the meetings or things is coming into Aurora as well. For now we use Fathom, but other than that, I think that’s my repertoire of AI tools, my go tos. Vivi, do you have any other ones? Yeah, similar as well.
[00:44:54] It’s all the things that you have mentioned about definitely use the Aurora probably the most alongside with some parts of items that use chat GPT on so Aurora for Aurora, what I would use for and how I see the team work on it. Mostly it’s more around things that needs long that needs to stay in a longer term a client project that lasts three to four months or maybe longer.
[00:45:14] Okay. Maybe a retainer projects or company knowledge from the HR site and from the administrative, it would be around policies and things like that. Things that needs a certain part of continuity so that we would be able to build on top of.
[00:45:26] And when it comes to just a quick answer let’s say the other day we were in events. We are trying to wonder what is that food that we were eating? It was a type of grain. So take out our phone scan it and say, oh, it’s a food. So basically those are the things that we would be able to do, which was super powerful with having a GPT on the phones and the other one that our team used quite a bit is real loom.
[00:45:48] Real loom is a a AI powered wireframe builder. Basically they were able to, as long as the promise good, but that they were the team was creating, it’s able to immediately instantly create prompts or wireframes out of the prompts. So that was super powerful. So the team typically used Aurora for more of the tech space or directions or anything that needs strategic thinking.
[00:46:09] They rely on Aurora a lot. And perplexity sometimes if they needed to do a little bit of a deeper dive onto research and reloom for when they are working on wireframes. Okay, great. So it sounds like there’s not a one size fits all approach when it comes to adopting the AI tools and technology that you’re using today.
[00:46:27] You use each tool differently depending on the nature of the tool. What I’m hearing is Aurora is more of a strategic tool that hosts the knowledge for long term projects and helps your team collaborate in real time. In this AI system, you use other tools like ChatGPT Perplexity for more individualized tasks or one off prompts or questions, things like that.
[00:46:49] And then you have these design tools peppered in to take some of the text or the knowledge or whatever that you were able to create an Aurora and then turn it into something visually powerful and refine and work from there to get inspired or like you said, create a quick wireframe with this as a very short prompt.
[00:47:08] And You have a mix of solutions in there, and there isn’t a one AI tool to solve everything. Yeah, I would say that’s fair to say. And I will also say if you’re I’m assuming if there’s any agencies watching this, I’m sure you’re probably, our ChatGPT probably your go to maybe ChatGPT teams.
[00:47:25] So you’re working together on that. And so there’s a lot of things you can do on that for sure. For us, though, Aurora just was, I guess it was just designed very consciously to work with how teams actually operate and not kind of everything. It feels just a little bit more siloed the way it works on ChatGPT.
[00:47:40] So that’s why therefore all the team projects or anything that is has complexity to it, Aurora is our go to. If it is, I need some recipes for some cooking or I need to work out something, probably ChatGPT it’s easy on the phone, right? And so that’s just become the default because Aurora stole the show for us.
[00:47:56] But that’s, as you said, there’s no one size fits all. I think it really is. Try the tools. That’s the best way to do it is just jump on, try the different tools and try to apply it to how you actually operate and find your sweet spot. Every company is gonna have different ways to operate.
[00:48:08] Find that sweet spot. But, I would not land on a tool and say this is the one and we’re going to use it until you’ve tried a few of the ones in the space. Makes sense. Reoccurring theme is to send it, just do it, try it, see what works. All right. So let’s talk about some of the impacts that you’ve had not only internally, but with clients, like clients are the whole point of agencies, you’re in service of the clients that you work with to help them achieve a specific goal or outcome or project, right?
[00:48:35] And AI, while it’s immensely helpful internally, what are the benefits that clients are experiencing through the result of your AI adoption? Wow, that’s that’s a huge topic in itself. I think on the client side, there’s been well, very quickly in the earlier days, we saw a lot of some of the bigger clients hesitation.
[00:48:52] Like we walked into a room and they were like, no, no takers. No way. I know nothing. That’s the terms. And some one of their client actually had it in their agreement that we’re not allowed to use AI, But that has been such a shift to now we’re being chosen because we’re AI first, because we are faster and we are more, thorough across the board.
[00:49:11] And we achieve amazing results because we are, we’re bullish on AI. So I think clients are it’s been a very interesting swap of we’re scared of AI, so we don’t know how to do it to now you guys use AI and sound like you’ve got a good approach to using it and that’s what we’re looking for.
[00:49:25] So that’s a very interesting shift I’m seeing in these bigger clients and what they need and what they’re looking for from their agency support in terms of the impacts though. Speed is a huge one, like the ability to be able to operate very thorough and very effective with really high quality at fast, a faster pace is I think the major thing, a number of if anybody’s familiar with this, but there used to be like that little triangle, like I would say.
[00:49:48] fast high quality and cheap and there was always you can only ever pick two. You can’t have all three And I think you know 500 designs is not a cheap agency because we really do phenomenal work But there’s now an ability to be able to reduce the amount of hours that it takes to do something and the clients benefit too because instead of having to charge them this huge amount of time for Very complex things.
[00:50:08] We can be fair and very transparent on our pricing and say we will be able to do it for this price. And when they ask the question, which I get on calls, believe it or not on sales strategy goals they’ll ask how come this only takes this much time? And then I show them. And then their minds are ready straight away because they see while you’re not compromising on.
[00:50:24] Quality, you’re just working smarter, not harder, and they like that. I think, speed is a big thing that does impact the price for sure. But the most important for an agency of our side is just the overall quality of output. It is improving every, the quality of interaction with our clients at all points from sales.
[00:50:41] We don’t have to ask them to repeat themselves. We don’t have to come back to them with questions they’ve answered already. All that’s clear because we. Got it. And the eye is able to use that to create the perfect proposal in terms of onboarding. We make it so much easier for clients. Now, instead of having to labor over all this stuff, give them access to Aurora.
[00:50:58] They could jump in and use what we set up to get them on boarded at a much quicker pace. And they appreciate that to the communication at each point in the project to the planning of the project. All that now is AI enhanced So therefore, the client is just appreciating all these smaller touchpoints that are more precise, more thoughtful, and, obviously, AI enabled.
[00:51:19] And then, of course, the quality of the work it’s just so thorough that we are easily able to connect the dots back to the research so that gives the team, the creative team, time to spend more on the exploring of design to try a couple of different flows in the UX that if, in the past, the hours were limited because they spent so much time trying to understand Fundamentally know what need needs to be what should contribute towards quality, good strategic design.
[00:51:44] Now they’ve got more time to do the explorate exploring and the creative side. And that only benefits the clients because they’re seeing this like really thoughtful approach. This, I’ve gone through so many different options, but here’s what I think is gonna work best for you based on my expert opinion and.
[00:51:59] Yeah, that means the bar moves up in terms of quality of output as well. So it’s massive That is a huge topic. We could be talking about it for days but I all I can say is that we’ve not had a single client come back to us and go we’re not happy with the work that you’re doing. On like across the board Since we started to implement this.
[00:52:17] So it’s a very big testament to well, our team’s ability to adapt this technology and use it. But also the technology itself enabling us to be just operated a different level. I think that’s just as I mentioned earlier, the bars changed. We’re just moving with that bar as best we can.
[00:52:32] Yeah, that’s so so true. Because sometimes clients would reach out to us as well to say that, Hey, can we meet this timeline? Because we are like adamant that this is when we need to launch because there’s something that they need to do for their marketing goals. And in the past, sometimes we have to turn down on projects that are urgent.
[00:52:48] And part of the reason is because our team can’t have the capacity to work on the sudden addition of work, but now the team has a little bit of time to take on those additional things or being able to say, yeah, I’m confident that we are able to make this specific timeline because we are able to really deliver within the timeframe that the client is looking for despite it being urgent or despite the it needs to be a little bit faster than the original timelines.
[00:53:14] Awesome. As you two were talking, I was drawing a lot of parallels between the employee, like the internal side of things and the client side of things. There’s fear on both ends and it comes down to resolving that fear. It comes down to transparency and education and inspiring, like showing them what you can do with AI as a collaborator, not a replacement as an enhancement.
[00:53:35] Not something that is going to disrupt the quality of your work. It’s been very insightful so far. And I’ll move on to the next set of questions now. Let’s talk about the future of AI in your agency. How do you see AI evolving?
[00:53:47] What are you excited for? Do you have any predictions that you’d like to share? Yes, lots. Okay. I think, on Aurora is one thing we know this, that the presentation builder. Having a document and turning that into a stunning on brand presentation and with literary, the click of a button is phenomenal.
[00:54:03] Being able to share that with a client and capturing their comments and feedbacks right there and then being able to Just click one more time to say apply those comments or approve this one. Don’t approve that one to make changes to individual slides or an entire deck based on new information.
[00:54:16] I think that sort of stuff is going to be very powerful. I think we’re going to start see platforms where Based on the topic and based on what you’re doing The output from the AI at the moment is all purely text or you know Some charts and graphs from time to time and with Aurora more soon on the presentation side of things But imagine it being able to know, it’s working on something like I know simple example is an email so i’m working on an email and i’m there’s a an agent that is looking at over my emails in the morning and it is able to draft out all my replies.
[00:54:44] So should the interface be a chat interface or should the interface know to adapt that I’m working on some emails here? So let me give a better presentation and an easier way for the for, the human collaborator to look at what’s on screen and make very quick determinations of whether this is approved, not approved and understand the context behind it.
[00:55:02] So I think it’s going to have to evolve the way that we think about UI in the design world so that we can, create intuitive experiences and the danger. This is the thing. I think what’s going to have to be solved with really effective UI and UX design.
[00:55:15] The danger is are we making any assumptions here? Or has there been any misstep along the way?
[00:55:20] So I think where AI agents start to become much more able to create a automated approach to things, there’s going to have to be an intuitive way for the user to dive in deeper, and click and see behind the scenes a little bit, but in a way that allows them to, get a simple output that You know, meets a certain criteria.
[00:55:40] But if you’re not sure, you need to dive in to understand where do things go wrong. And what was it that led to this conclusion? That was very simple example and probably not a strong use case. But as the agents become more capable of executing autonomously, these much more complicated multi step especially in the creative side, creative processes.
[00:55:57] The output is one thing, but The reason behind the output needs to be understood and, there might be a scenario where you just go again and it gives you a different output, that’s not strategic. That’s guesswork, and I think, for an agency like us, we will always look towards the reason behind a conclusion, like what’s causing this understanding cause is critical.
[00:56:16] And I think the products and the platform is going to have to make sure that they adapt their UX to make that easy on the end consumer. But I think, I said this on a previous conversation with another AI nerd like myself and like the media as well. Today it’s like the wild West.
[00:56:31] Like today it’s gunslingers. And, it’s just there’s so many tools coming out now that there’s not one clean direction I think what’s going to happen in the long term is consolidation. Microsoft and Google, they’re still fast to build the LLMs, but they’re slow to build the user experience and the new process because organizations change slowly and that’s their mainly their private, their primary target.
[00:56:53] So these newer companies are going to really disrupt. I think everybody’s saying it, it’s safe to say that a lot of these companies will succeed and they’ll do so with smaller teams than ever before, but they will start to, pierce a hole in these big organizations and they’ll either be acquired and it’ll create consolidation over time.
[00:57:09] Or maybe a new player will start to emerge. ’cause they have fundamentally got the forecast of AI, and they’ve built a strategic approach to get there. Yeah, I think that’s a broad answer and definitely a long term outlook on how this goes, but that’s the way I think personally, I see things shaping up over the next few years.
[00:57:28] Yeah, it’s going to be around continuity for sure. So I think where the world is going to be it’s based all around continuity, seeing the future where there’s things that currently what we do, it’s still repetitive.
[00:57:39] And it’s a lot of dependencies. There’s a lot of people needs to work on the same project or task together. Imagine a world where continuity is one of the key things that comes into play where knowledge or information is basically able to be sustained to be able to support making decisions and help enhance The workability across projects, across tasks that we do this is what I’m imagining in the future.
[00:58:03] It’s a project management tool. That is a I based hopping on to meetings, being able to swap it into actionable points and then some parts of the tasks that was the actionable points are being completed by AI itself. And some are human interaction. And so that is basically all automated so that it just makes our lives a lot easier where we get to do what we love to do most.
[00:58:25] And the tedious task is actually being able being done by AI. And then one last little piece of this, cause maybe you just reminded me of one thing, I think. We’re starting to get to the point. AGI is promised this year. I think if that comes out, it’ll be a very basic version of that.
[00:58:41] And it’s definitely a step in that direction. But time will tell, and maybe OpenAI will blow our minds, who knows. But I think when we start to see the AI writing the code for itself to solve something new that it challenged itself to do, Is where the game starts to change. I think there’s early conversations about how this might work I just don’t know there’s enough data to support The decision making there and I think that like the innovation curve, typically you’ll see like every new new technology.
[00:59:13] There’s this very quick growth. It’s very slow for a long time. And then suddenly it goes hockey stick and it’s like the technology evolves so so quickly, but it eventually starts to curve out a little bit. And I won’t say plateaus in this particular space. It probably won’t plateau per se, but it’ll certainly start to round off and the speed of that innovation is going to slow down.
[00:59:29] I think we’re already seeing a little bit of that around the core intelligence of the LLMs, like going from ChatGPT 2 to 3, 3. 5 to 4. 5 and these reasoning models, there’s been a very quick rate of change, but the most recent ones are not as broad a percentage gain by comparison to some of the earlier leaps and bounds that were made.
[00:59:47] So it’ll be interesting to see that. And I think there’s as AGI comes out, we’ll probably see another level of. Okay, basic AGI slow rocket ship, and then it starts to curve again. We just have to keep an eye on as the game changes with this new technology and then keep on forecasting because I, if you go back to the first days of the smartphone and think I phone and where we thought it might go.
[01:00:09] I think a few people could have guessed. I think a few people would have thought this is the way the world is going, especially once it’s the at the app store is created. I think, we know that this is where we get to and there hasn’t been any. Phenomenal breakthroughs or enhancements to that technology since the early days of the smartphone I think with AI though, this is probably different because it’s tricky to comprehend What it’s what’s possible because it’s just it’s vastly different.
[01:00:33] So this is uncharted territory I think anybody who makes a prediction right now is Probably going to be proven wrong in five years. I think we can probably predict carefully the next Maybe a couple of years after that, though, goodness knows. But you just think about the fundamentals like humans will be involved.
[01:00:50] Humans will not be fully replaced. That is, for certain roles will be replaced or certain parts of what they do will be replaced. And that would be completely autonomous. But the human will still be in the loop. I think the next one is That the there’s core analytical skills required to know what to do with the AI as it starts to evolve. So system thinking, creative thinking, analytical thinking, and those core skill sets are something that everybody should maintain and be aware of. And then the other thing I would say, as Vivienne said, it’s that continuity, like no matter what knowledge it’s the glue, right?
[01:01:23] If you get intelligent people the same amount of knowledge or the good knowledge to work with, they will make solid conclusions. So the knowledge and the data that’s feeding all of this is so critically important. So knowledge management and then knowledge management across a project or a team or a department or a whole company That’s continuity.
[01:01:41] And so I think those are the fundamental things that need to be nailed. And then of course, to have the team interact with it is the skill of strength. Awesome. Those are some crazy predictions and it’s going to be very interesting to see how things unfold over the next three to even just five years and 10 years and beyond.
[01:01:57] There’s no telling what will happen, but that concludes This interview this chat, and I want to leave the audience with one final thing from each of you. If you could give other agency owners or founders one piece of advice when it comes to their own adoption journey, what would it be
[01:02:20] I would say that if there’s something that every single agency owner could do is. Don’t be afraid to try different tools out there and just find something that would work for the future proof your agency. So I would say that would be most critical is that there is going to be a shift and also a disruption with AI, with using AI in the future. So how might we be able to start utilizing it is by being preemptive is to start implementing is to start getting the teams on boarded to using AI definitely agree with that for sure. I think the other thing is. To bring your team along for the journey and, figure out a way to, change the mindsets of the team.
[01:03:08] If the team are already very bullish on AI, then great, that’s a great place to start, but make sure it’s a unified movement. Don’t allow like a. A lone wolf to go and figure out a particular process and go their own way, because when they leave your agency, at some point, they’re taking that knowledge with them.
[01:03:23] Building a system of how we use it together, building a system of how we learn how to use it together and something that you as the agency owner, if it’s an agency owners Giving them the advice that the platform that they use that you’re able to retain your procedures, your processes, like it’s all there.
[01:03:41] It’s documented. It’s part of the core of the intelligence. And so therefore, no matter what happens next, you bring a new person onto your team. It’s easy to slot them in versus that person goes and takes away a little bit of that secret sauce. And you’re scratching your head and figuring out how did that person do it?
[01:03:55] I don’t get it. Whatever the case may be. So definitely try platforms. Experiment and play around a little bit and bring your team along for the journey amazing Thank you both so much for joining me. Your insights are incredible and I can’t wait to see what happens in the future with 500 designs and design force and then all the other tools that you’re using and so with that said I want to leave the audience with one last thing.
[01:04:17] Go ahead and try aurora. There’s a transcript at the bottom of this page. Copy that transcript, create a free Aurora account, paste this transcript into your workspace as a knowledge document, and start working from there and see what can happen. Ask for a summary, ask for insights, ask for action items.
[01:04:36] Go ahead and give it a try but that’s it for today. Thanks everyone.
