B2B Inspired
B2B Inspired, the podcast by BlueOcean - The B2B Agency, is all about exploring the ins, outs, ups and downs of B2B Marketing here in Aotearoa, New Zealand. We'll uncover emerging trends and thinking while sharing inspiring real-world stories from B2B Marketers here in New Zealand. With the goal of supporting New Zealand’s B2B Marketing community in becoming one of the best and brightest anywhere in the world, let’s roll up our sleeves and take on tomorrow together.
B2B Inspired
Freeing Smart Minds From Tedious Work with Dave Howden
Discover how AI is shaping the future of business in New Zealand with Dave Howden, CEO and co-founder of SupaHuman AI. In this insightful episode, Dave shares his journey from the UK to New Zealand and explains why he believes this environment is primed for AI’s transformative potential. We explore the powerful role of large language models and multimodal technology in reshaping business landscapes, highlighting why understanding an organisation’s core values and processes is crucial for AI integration. Businesses that embrace tailored AI solutions can enhance efficiency, drive growth, and stay ahead in the adoption curve.
We also uncover the key inefficiencies AI can address, from knowledge retrieval to outdated systems like CRMs and ERPs. Imagine significantly reducing the time employees spend searching for information and transforming complex tasks into simple queries. With AI’s growing intelligence, businesses can streamline operations, generate synthetic customer insights, and refine their value propositions. Instead of fearing AI, now is the time to embrace its potential to solve productivity challenges and revolutionise customer interactions, ensuring long-term competitiveness in an ever-evolving technological landscape.
For more B2B insights, ideas and opportunities, head to www.blueoceanagency.co.nz
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Let’s roll up our sleeves and take on tomorrow together.
Thank you, people from within our ecosystem. We're here to help the New Zealand B2B community to become one of the best, boldest and brightest anywhere in the world. Now if, like me, you live and breathe all things business to business and you're looking for a place to connect, learn and be inspired, you have come to the right place. Kia ora, and welcome back to B2B Inspired. I'm joined here today by Dave Howden. He's the CEO and co-founder of Superhuman AI and we've crossed paths a little bit through a few mutual contacts along the way, but one thing that really really really struck me about this business was actually their tagline Freeing smart minds from tedious work. Now, I'm not someone who signs up to tedium I don't think any of us are but there's so much opportunity in this space. But that comes with some caveats that we'd like to unpick and some considerations that we'd like to talk through here for the B2B community with Dave today. So, dave, welcome. Happy New Year. Happy New Year, welcome back. Yeah, I feel like the jandals are a thing of the.
Speaker 2:You've still got the summer shirt on, so there must be something in the air that you know summer's still around until it's not.
Speaker 1:Yeah, yeah, exactly. I mean, you've got to try and manifest these things, Cool. So a few things to unpack in the conversation today. But what we'd like to start off with here is, first and foremost, getting a bit of a gauge of who you are, because it's always good to kind of get to know the messenger before we unpick the message. So tell us a little bit about yourself, about your journey and what led you to founding superhuman yeah, cool, um.
Speaker 2:so look, new zealand is now my home and I came over to this part of the world from the uk in 2016 and I don't know about, uh, you or you, you're from portsmouth, right, originally. So you know australia here. You know Australia here. You know we both had the luxury of being accepted into this awesome, awesome place, and that's what kind of drew me here is that you know this little, as Jacinda would put it, the team of 5 million that we've got allows us to do some really cool things with business and not necessarily get drawn into the hype that happens in the other larger markets, where there's just a lot of noise. But we can kind of go, okay, how do we get to the root of the problem here and solve for that with a bit of number eight wire, but turn that into quite some meaningful businesses. And yeah, that's kind of why I decided to invest my time and come here.
Speaker 2:But I'm an engineer by trade, started in the telecommunications days of 2G, 3g, and helped the world get connected, and ever since then, I've just applied my experience and muscle to the different technology trends that have come through and built businesses around those technology trends.
Speaker 2:Prior to this, I operated New Zealand's largest managed service provider from Microsoft called Umbrella, which we exited in 2022. Umbrella, which we exited in 2022, and now decided to pull together the talent that was needed to help New Zealand organizations embrace artificial intelligence, which feels like you're jumping into a bit of a hype cycle, but where there's mystery, there's a business to be made normally. So we're helping New Zealand and Australia businesses unpack that. I'm by no means a deep technologist. I'm a business guy at heart, but with a respect for engineering, and we're really enjoying helping customers become more efficient, grow and manage their risk when it comes to actually applying AI to help them sustain business in this economy. But outside of that, father Hazel, my poor suffering partner, deals with me on a daily basis. Yeah, just love committing to this part of the world and making it happen for the superhumans, everyone around us, our customers, and having some fun along the way.
Speaker 1:Fantastic. I mean, it's interesting to hear that your perspective of having chosen to be here in New Zealand and being accepted here as well, I mean I can really really resonate with that. It certainly, I suppose, aligns with kind of my journey as well, and there are some incredible businesses here. I have to say, you know, I never cease to be amazed by the innovation and, like you said, that problem-solving mindset that you have here in New Zealand and that seems to be sort of hardwired and kind of baked in. But when we look at things like AI, I think there are so many possibilities with it that you kind of end up in this what I call the possibilities paradox. Right, when anything's possible, where do you begin? So when you're approaching conversations, let's say, someone comes to you and says, look, it's 2025. This is the year that we want to get ahead with AI when do you start that?
Speaker 2:conversation. It's an interesting dynamic and I'll simplify this, not for the audience's sake, but I simplify it for my own sake. Simple is key, I think in business We've been here before and we'll be here again there is technologies that have happened well before AI, that had transformational promise, and we've had to go through the same cycle, which is right. Well, I'm doing things a certain way now and with the application of technology, there might be a better way. And if there is a better way, what does that better way look like? So we used to market through classified ads. We now market through Google AdWords. We used to dig holes manually, then we bought excavators right, it's the application of the hydraulics in excavation and the application of Google AdWords and the internet through classified ads. It's the same stuff, packaged up in a different way for the purposes of shifting the needle forward, and AI is no different. So if you go back to any technology we've previously looked at any one, right from the wheel all the way through to today, the question has been really simple how does this technology help me grow, be more efficient and manage my risk profile? And if there is a compelling reason to do that with that technology, then let's spend some money, let's invest in that, and if the return is better than the spend, then we're off to the races. Simple. Then we're off to the races. Simple With AI. The application and the return is so great that that's what's creating the tension.
Speaker 2:I think, for the business the businesses, as in there's so many things that you could do. The simple question that we ask our customers is where have you got your smart people doing dumb stuff and do you want them doing that dumb stuff, and where is the most dumb stuff happening? And then you've got your answer. What that normally means in relationship to artificial intelligence is whilst an excavator dug holes, it was very easy to see that a human should not be doing that. With the application of AI, you have a technology that can type at light speed, create things at light speed and can read at light speed. Therefore, wherever you've got humans that are biologically limited. So if you're creating reports, analyzing data, doing complex engineering like submissions, compliance audits, anything where you're constrained to get to the end result based on your human biology, that's a really good place.
Speaker 1:Good place to start. It's such a simple way of looking at it, where you're constrained by human biology, but that's it.
Speaker 2:But that's what it is right. Yeah, like if you were to think about this in terms of doing research for this show. There is absolutely no way you should be reading through my LinkedIn profile, going through the intent, looking through our website. That should be an ask of give me and prep me for this podcast for Dave. Job descriptions same thing. Review of contracts the same thing.
Speaker 2:Ai is a magical. When I say AI, it's a huge, broad topic. I'm specifically talking about the large language model technology, the multimodal. So vision and text creation in and around that, the underlying technology that powers. That is super magical and powerful.
Speaker 2:I think the challenge that people have with it is that it has no concept of who you are and your businesses and the guiding principles about what your organization is. So you get these things like demos on LinkedIn of people doing stuff that's no business context and say AI is going to change the world. Air fryer recipes and dad jokes aren't going to change the world Fun, but it's not going to change the world. So we've approached this and said, well, what does AI need to be able to remove that tedious work? Well, it needs context of your business. It needs context of you as an individual. It needs context of the regulatory environment. You sit in your jurisdiction. Once AI knows all of those things, it's going to act for you and work for you within those boundaries and then you're off, like literally all of that tedious work just starts to drop.
Speaker 1:So what are the barriers to adoption then? Because I mean, when you put it like that, that seems like an absolute no-brainer. So where is New Zealand on the adoption curve, and what are the barriers to us being at the very forefront of it?
Speaker 2:I genuinely believe that the intent is there to not want to do tedious things and our customers engage on that way. They're like, look, there's just a better way to do this. Engage on that way. They're like, look, there's just a better way to do this. I think there's a natural uncertainty about how am I going to get return from this. Is the needle going to move? And you only know that by going down the journey. So those that are going down the journey are seeing tremendous results.
Speaker 2:Those that aren't know they need to and aren't seeing the results right now, which is creating an air gap between their competition and them. I'll give you an example, which we won't name names because the customer doesn't want us to name names. But there are lots of situations where, if you are in a business where your monetizable thing is output, so like a compliance report or an audit, your cost to deliver that is human capital. That's literally time. If you can shorten that from 10 hours down to 15 minutes, which is super realistic like for a lot of this work, super realistic your ability to create gross profit margin and sustain your business is massive. Now, right now, that is a competitive advantage. In two years time it's not a competitive advantage because everyone's doing it, it's table stakes and you're actually out of business at that point. So we won't play the doomsday scenario because that's not a good way to engage trust with our customers.
Speaker 2:But the question is totally like, totally real what's the alternative If you're not going to? Would you still put your adverts and classified ads? Would you still dig holes with excavators? Would you still have your humans like limited by their biology for things they weren't designed to do? And if that's the case, then let's get to work and let's just start, because the investment to actually take the underlying technology create an, a secure, safe environment where you can start to test this stuff out in a way that's meaningful to the business. We're not talking millions of dollars. You can get a long way for like sub 100 000 for totally transforming your business and that doesn't just look like going to chatgptcom and asking a few questions.
Speaker 1:right, what so? What are the? What are the? What are the building blocks Like? What do you actually need in place to actually be able to start freeing smart minds?
Speaker 2:The context is everything. Yeah, okay, the context is everything, and I'll give you an example. So ChatGPT unlocked, democratized the use of language models for the world. Since then, that's just a race of commoditization. Google's models are as good as open AI's. Now, deepseat came out last week.
Speaker 2:We have to mention that we have to mention that because everyone has to mention that, but actually that's just noise as in. If you look back at other technologies, really you've got the same thing. Who's better Amazon or Microsoft, before that? Which technology is better? They all kind of reach a level of they're all great. Some are better than others at certain things. The missing scenario is context. And why is context important? It's because marketers and there's definitely a blame game, but there's a scenario here have rightly said to compete in business, you need to be unique. You need a unique value proposition. What makes you different from your competitor? Which means one marketing agency looks different from another. Their value proposition is different, their processes are different. So how do you then take one technology like ChatGPT and make it contextually relevant to your business if that context has never been documented before? So when you provide that context to the AI, it knows your value proposition, which is unique to you. So you can't just buy that off the shelf, you've got to build it.
Speaker 1:It's IP right. What are your?
Speaker 2:values? How do you talk? How do you talk? How do you act? What regulations do you need to comply with? Who's in your business and what do they know, like, where did Dale go to school? And do I know that he can speak French? And well, you know, like not, that you can speak French, german, german, because all of your business is your business. It's unique to you. It's your people, your processes and your procedures that make it so, and artificial intelligence has no context of that. That's what we're here to do is help customers put that context in place, which essentially means going through a traditional design process, like an agency would, of going. Well, who is company X? What do you do? How do you do it? And a lot of the time, it's never been written down. The most you've got is a bit of a shiny website that's kind of a little bit out of date.
Speaker 1:It's so interesting we hear this conversation time and time and time again, particularly in businesses where the founder is still running the show or it's a family business, where you've got this often innate sense of values that there are a you know, there are a set of cultures and standards that are held up by the person that you know that leads the show, but getting the whole business aligned behind them is not necessarily something that's immediate right.
Speaker 1:It's innate, it's not documented, it's not been shared, it's often not been scrutinized, is probably the right way to put it like strategically. So I actually think that there's in this whole kind of conversation around providing context. I think there's an enormous space in there for the field of strategy and identity marketing and everything that that skillset brings to that conversation, to actually shape AI in the context of a business up for success right, and a lot of these things.
Speaker 2:They can be. The reason a lot of things I think sit with those founders is because you're kind of following the founder right and it's like it's how they talk, how they act, how they do certain things, and not necessarily something you can write down. That said, there are decisions that can be made really quite quickly that allow you to disseminate that essence into an organization very quick. So I'll give you an example Organization and you know they're selling stuff, right. And then we turn around and say, well, cool, what's your sales methodology? And then we go, oh, we haven't really got a sales methodology. The founder does all the sales and okay, cool. Well, what would you say? A sales methodology is like it's probably most like spin or challenger, okay, great. So have you ever written down the sales process around spin selling or challenger selling? Well, no, have you ever trained your salespeople on spin or challenger selling? No, okay, cool. So what you've said? You've got a founder who's mostly doing this in a certain way. We know what that way is. All we need to now do is tell the AI to sell your value proposition, which we've got, in a challenger way. So anyone that comes into your organization that says prep me for this meeting or help me sell this product, or we're selling this product, we want to sell this other one. It's going to enforce a challenger methodology. Now, that's no different from marketing to say, well, what funnel design have you got? Oh, we're going to adopt the pirate funnel, or we're going to adopt whatever funnel. Well, as soon as you've made the decision and told the AI at an organizational level, any time any interacts with, like I want to build a campaign, it's going to enforce or be cognizant of that. This is the funnel that we want to follow. Yeah, and you can make all those micro decisions really quite quick, so great. What personality type do you want your AI to have as it speaks? Well, myers-briggs is a good proxy for that. So, choose one of the personalities you like, because we've never done a tone of voice guide before, because it's money, right? Oh well, we'll spend 10 grand designing a tone of voice which no one's going to follow.
Speaker 2:Choose one Perfect Sales methodology what makes sense for your industry. Choose one Marketing methodology, and then you're building up this graph of just business decisions that are actually quite quick to make, really hard to disseminate, and then having this intelligence work for all of your people. That's just driving that. Right value statements, right case studies, right tone of voice, the right sales methodologies for your business and that goes. That's not. We're talking about sales and marketing, because that's the world that we kind of live in from a B2B perspective.
Speaker 2:But if you go right down the road of what should or shouldn't happen, in your business as well, you can enforce things like PCI controls for credit card information, iso 27001 standards for information security management. All of those things are purely decisions. What do you want the intelligence to comply with? Once you've got that? That is the context.
Speaker 2:And then you unleash that into Gemini or OpenAI or Anthropic or any of the deep seek, all of the wonderful technology. And it's like, yeah cool, I know all those things, I'm just going to get to work and appropriate them and apply them. Appropriate them, apply them, guide the user on why we're making certain decisions. Or you end up with this trust issue where you're getting really quite good advice from the AI but it's never checked and balanced itself. It's like, yeah cool, I'll give you some tax advice. If you're going to ask a large language model for tax advice and don't tell it what jurisdiction you're in, you're going to get really confident advice that will be inaccurate, but at an organizational level, if it's like, well, no, dave, you're in New Zealand and you're a New Zealander, well, therefore, I'm going to give you New Zealand advice.
Speaker 1:You shouldn't need to make that the business and the world that allows you to automate tedious anywhere you go, so what I see is really interesting in that, though, is that that actual journey in itself, regardless of whether you go in to build a custom AI off the back of it that actual process of asking the questions and defining and setting the you know the context. Like you said, that's a super valuable thing for any business, right? I mean regardless of whether you go off to unleash an AI on the world that changes everything, but that process in and of itself is inherently valuable. So what do you see as the time to value, or what should you look at in terms of time to value on something like building a custom AI?
Speaker 2:Okay, so there's two scenarios. On this one, we confidently have organizational intelligence that knows all of those core business decisions up and running in about 20 minutes. That's the time to value for going. Here's your first version 20 minutes.
Speaker 2:Yeah, confidently, within 20 minutes. That's the core non-negotiables. So I'll give you an example. If I know your business name and I know your country of origin so business X in New Zealand I can pretty much find out 99% of things that I need by doing research Our AI services will go do the research for us and it will build the context engine for that organization and then we're into the decisions that aren't publicly available. So your business has sales and marketing, some form of operational team and some form of finance and administration. What marketing funnel do you use, cool? What sales methodology do you use? What operational standards do you need to comply to to not be on the front page of the Herald and get sued? But they're literally just decisions.
Speaker 2:How culturally competent are you on your AI? How much do you want to reflect to AI in your content and all that kind of stuff? Yeah, and then we just build out the teams in that organization. So who's in what seat? And 20 minutes we're off. And then after that it's just every time you add an extra decision point, the AI will get better and better and better over time.
Speaker 2:So to get to 80% of value, really really quite quick. To get to 20% of automation of work. We then into well, where have you now got that deep, tedious work where we can actually fully automate those processes and we go into more of a deep scenario. But that base organization intelligence 20 minutes and away we go. Now why that's important is that contextual layer is not connected inherently or bound to the underlying language models. So of course, if you want to wedge yourself to Google or wedge yourself to AWS or one of these providers, then there's a load of jiggery-pokery you can do to kind of have that experience there and you can build it yourself. But that whole layer, like the LLM layer, is moving so quickly that this context needs to sit outside of that and then be applied to it. So we take that one context and say, okay, cool, well, we want Anthropic Google and OpenAI in the mix and everyone's available to use that context.
Speaker 1:So we're AI agnostic and provide that layer the front, so somewhere along the line in that whole process. That would be how you go about documenting it right. So you'd end up with some sort of blueprint that outlines all of those key things that, like you said, if you want to get a different LLM, a different AI, on board, that learning process and that learning curve is just as quick, right.
Speaker 2:Even the sense, though in terms of I'll say it as how I see it. So what, who cares? With the greatest respect to how much money has been put into the research elements of AI, who's got the best model, the fastest model, the most inference context window sizes? My customers want to be able to grow, be more efficient and manage risk. The nuances of the model don't care. So what, who cares? Just get it done.
Speaker 2:What that means in practicality is we need to bring the best technology to help our customers grow more efficient and manage risk. Now, 18 months ago, that was GPT 3.5 Turbo, then it was GPT 4. Now it's 4.01. And now we're going to get 4.03 soon. Plus, all the anthropic models have moved forward. Now we've got all the other open source models coming to the table. Our job is to not have that problem pushed onto our customers. So why I'm saying this is a lot of our clients. It's not one model. There's like five or six different models that are there to do different things, because some are better at reasoning, some are better at quick, fast decisions. Yeah, some are better audio and visual and the user should not have to make a decision. They're like I just want to do my work, and then our technology will decipher which service is the best one to use, apply the context and then so I suppose all that is to say is that you don't need to be an expert yourself to be able to actually unleash the capability.
Speaker 1:I just don't think you can be an expert that's a great way to put it because it's huge. I mean the field is evolving so fast. I don't think you can be an expert that's a great way to put it Because it's huge. I mean the field is evolving so fast?
Speaker 2:I don't think you can. I mean, we are a team of 30 people. You know 75% of them have either got a master's or a PhD in machine learning and AI, and we could have the whole of that team just doing R&D all of the time on stuff that's moving, and we can't do that because we've got a business. We are in that swim lane of unlocking the smart people from tedious work. That's all we do and there's not enough time in the day, and there never would be enough time in the day. Yeah, so we've made it quite clear for ourselves Our customers are there to be in business.
Speaker 2:We want enterprise-supported technology only. So if it's not available through Google, microsoft or AWS, we're not touching it. Yeah, because otherwise it's just noise. We'll allow them to do the vetting for us and then we go to work with their technologies From our customer's perspective. You arrive and you drive. You come in, you log into your custom workspace that looks like you a private chat, gpt-like environment that's got all that context built in and you get on with your tedious work or, more importantly, you outsource your tedious work to the AI.
Speaker 1:So what is the most common? Let's look at tedium quickly because, like you said, it's going to exist in just about every business. I think one of the things that it's good to understand is what are the common areas? To actually look that okay, cool, there is a use case here. There's a use case here. There's a use case here. There's a use case here. There's a use case here. What are the most common areas that you're seeing? Businesses can use AI to get ahead quickly.
Speaker 2:There are two things that I think are coming to fruition. They're just becoming more evident as days goes on. The first one is knowledge. Right now, for most businesses doesn't flow freely at all. Marketing have got their SharePoint folder over here and sales have got stuff in the CRM, and then there's stuff in the ERP and trying to get a view of what product's profitable and how to sell this certain product. Data is siloed and knowledge doesn't flow. Yeah, that is a time drag on everyone in the business. A McKinsey study about six months ago said about 3.6 hours a day is wasted on knowledge finding when do I find stuff and how do I find it. Per person, per person.
Speaker 2:Per person yeah so close to half the time of a business is not actually doing stuff. It's finding. It's looking for stuff, trying to find where it is. Where is this thing in Google Drive? Where's that deal in mondaycom? What's happening with SEM rush? Like it's looking for stuff. So, to go to like the efficiency angle, depending what studies you read, mckinsey was the most aggressive at 3.6 hours a day. Other studies say around two to two and a half. If you said three, right. Either way, even if it's half an hour, it's too much. So when you look at that, across 100 people spending close to 50% of their time looking for information and knowledge, that creates two problems. One is there's too much time looking for stuff. The second thing is when people join your organization, their time to efficiency is far too long. An organization we're working with right now who have got 60,000 products, say they reckon that their sales team aren't efficient for 12 months Because they've got to learn 60,000.
Speaker 2:SKUs 60,000 SKUs. Where is the stuff? What relates to what? How do I price those things? What's the nuances of all of the different elements? So scenario one is knowledge doesn't flow freely and again you're limited by your biology and the ability to find stuff and read it.
Speaker 1:So if you had something that was essentially new at all, you should just be able to ask so is that a recognizable moment when you've got people who are always turning left right over their shoulder to ask the other person, hey, where's this, hey, where's that? So if you're hearing those questions in your business, that's a question that you should be asking AI.
Speaker 2:You instantly know yeah, if you've got people looking for stuff to answer questions or quick queries on anything for their own job or for a customer, that should be nothing more than either the customer asking and getting or the employee asking and getting, not searching. Because we've been brought up especially probably our generation we've been brought up on a generation of search right. We were the Google generation right Yahoo, google, altavista.
Speaker 1:Exactly right.
Speaker 2:You ask for a question, you get a million more ways to answer it, but then you've got to go and actually find the answer. You've got to go and pass that information. Pass that information, the AI is pre-parsed, so you move to the situation of an answer engine. Now answers come from multiple different sources. So, for an example, I use this one quite a lot, and I use it because we're in a studio. So if I were to change the light bulb over there, if I go and read the article that's from that light bulb provider that says this is how you change the article, right, okay, cool, well, turn it off, take the light bulb out, put a new one in, right.
Speaker 2:But if I'm in a business and I want to change that light bulb, I actually have to consider multiple different things. Where do I get the light bulb from? What's the health and safety policy about interacting with electrical equipment? Who do I need to let know in the building that I'm going to turn that light off? So I'm going to use a ladder. So I've got to be cognizant of health and safety. Then, once I've got health and safety certified ladder and all these bits and I've gone to procurement and got the light bulb.
Speaker 2:I then can go and change the light bulb, but if I was to just go to the Google scenario of that, I would have all these different things that I needed to read. Now what I should be saying is how do I change this light bulb? And it will say right, fill in a change request form, let everybody know, go and get the thing from here, step, step, step, step, step, step. That's taken all of this different knowledge and compiled this one thing. Now that's no different from creating a sales proposal which needs pricing from one place, contracts from another, legal from another. It's no different from any operating procedure that's needed to do something. You should be asked and given with all of the knowledge taken into consideration, and we've not talked about duplication. A lot of time, knowledge is duplicated and out of date, so you need the intelligence to be able to go well, what's most relevant and what was the last one? Out of all of these millions of versions of the same thing, whose spreadsheet is the most up to?
Speaker 1:date.
Speaker 2:Whose spreadsheet Right? But again, that's just logic. I'm going to use the one that was edited last. That make sense? Yeah, by the most senior person.
Speaker 1:Yeah.
Speaker 2:So cool, we'll assume that that's going to be the right one. Is it perfect? Absolutely not. Is it better than a human would do? Yeah, it absolutely is. So that's scenario number one. Knowledge needs to flow freely. That's mouthful and that is immediately in the efficiency column of how do you just drive that efficiency? The second thing is deep work, and what we mean by deep work is we use that 10 hour to 15 minute scenario.
Speaker 2:You may have all the knowledge in your head of how to do a certain type of task, but if you had an AI that could do that, how do you turn that knowledge, work that would take you 10 hours into just an ask for it? So, audit, compliance, reporting, creating long resource consent documents you know where it's just. This sounds negative, but it means it's just maths and engineering, as in like. If you look at what organizations that produce these like compliance statements are paid to do, they're paid to take the liability. They're paid to be the person who can Exactly right, is this correct? And if it all goes wrong, who signed it? Yeah, but the creation of that, the typing of it, the 30-page document that goes to council, all those things, that's not the monetizable. Doing the work is not the monetizable thing. The output is the thing the output and the adoption of risk. So that's the second column. Which is what businesses have got, those biology limiting monetizable units, and how do we turn that into something that's a pure request?
Speaker 1:So in areas where you said where you actually are outputting like a packaged, either product or process is probably the right way to put that. Yeah, pretty much.
Speaker 2:So think of things that just take loads of time Doing due diligence on an acquisition. You've just got to read through far too much stuff to try and find things that are going to put the deal at risk. That should be nothing more than having the AI give you those jeopardy reports Auditing things like. I can't give too much away because we're in kind of client mode with a lot of these things. But in the medical field, you're going to keep tabs on what's happening with a patient over time and at some point they're going to keep tabs on what's happening with a patient over time and at some point they're going to get audited. You want the AI to be pre-auditing all of those things to go well.
Speaker 2:Where did we screw up? Why did we not follow a procedure? Because at some point that's going to come and bite us in the ass. And then, how do we make sure that we're getting in early, is limited on all of those things, and when the ambulance is at the bottom of the cliff it's too late, right? You submit a report to council and it's inaccurate. The whole thing has to start again. You do that in the medical field, right?
Speaker 1:And people die.
Speaker 2:And that's kind of the origin story of superhuman in a way. I mean it's not. In a way it definitely was. I mean after I mean I lost my friend to best mate to bowel cancer in 2016. And the investigation to her death was it was administrative failure, like there was just bad administration of her care which led to far too long getting seen what you need to have done, misadministration of drugs and she died and you're like, well, like 2016 was a different time. Ai wasn't the thing that it was now. Well, 2016 was a different time. Ai wasn't the thing that it was now. But we look at these things from a superhuman perspective and go that is a ticking time bomb for someone and it needn't be, and it needn't be. So how do we solve for that? Now, not everything leads to people losing their lives, but ultimately people losing their jobs. 100% buildings being built wrong, like cost time, everything cost time.
Speaker 2:Yeah, everything hits the economy is people's jobs. It's trusting the technology that actually, you know it's not technology's fault. Um, and that's what we're on the hunt for. Is that? Where are those? Where is the tedious work? Where you've got smart minds are just doing the tedious stuff to help you grow, be more efficient and manage your risk.
Speaker 1:So any business that you'll go into will have their rhythms, their ways of working, They'll have their systems and they'll have everything else like that. And you used the example before of okay, where's the deal in mondaycom and how much have we got in stock and everything else like that? And what's the? How much have we got in stock and everything else like that, when are we at and what are the next steps around connecting fragmented systems? Right, Because I think that's going to be one of the challenges for a lot of businesses is that that all sounds great, but I'm using this CRM and ERP system that was built specifically for, let's say, the motor industry and it's, you know, hasn't been updated properly in 10 years. And how do we connect all that stuff?
Speaker 2:That's our problem. Yeah, and I say that everything's easy when you say it quickly. Yeah, but ultimately, how do you get information free-flowing across an organization? Now, historically, when new technologies have come along, they've been additive. So most businesses have a CRM, some form of ERP for managing stock or doing stuff. Some don't, but generally a CRM, some operational system, and then something like Xero to kind of buy it together. But yeah, there's different flavors of all of those. If you were to change your CRM out, you really don't get any more value. You get a better CRM, but your users don't get any more value. They're just kind of like this is painful. I've got to learn a whole new thing. It goes from being orange to blue. Yeah, that's right. Yeah, Same with the ERP and same with your accounting package. It's just cool. We've got to change it out.
Speaker 2:Intelligence is different because it sits across the top of everything. So if we can get access to the API or the underlying database, the LLMs are smart enough to be able to query them without needing to do a whole lot of engineering. Okay, so, for example and again not to go too technical but if your underlying infrastructure is on a, your data is on a SQL database, the AI can write its own SQL queries to query that database. Now you don't need to pre-can all of the SQL queries.
Speaker 2:You've got some sort of structured information in there that the AI can go recognize the structure, understand the language, then write the query yeah, because it's a better developer than developers, because the world knowledge is epic, yeah, and it only gets better. So can you access the knowledge and data through an API? Yes or no? Can you access it through a database? Yes or no? And then that's where we get to work, to create that integration layer and apply the context, and then away we go.
Speaker 1:It's such a fascinating space.
Speaker 1:I mean looking at it in in the marketing world.
Speaker 1:Um, one of the things that historically has always, always, always been a huge time and costing for a lot of businesses is actually generating customer insight right, and what we're now starting to see is the ability to create synthetic customer segments, customer surveys, interrogate them as a group of people and then arrive with something off the back of that which is 90% accurate to having done the huge, long thing yourself and you look at time to value that piece is a huge, expensive, time-consuming thing to go through and do.
Speaker 1:And what I find interesting in what you're saying is that there's just going to be so many different pockets within a business where this applies, and there was a quote I saw the other day which I thought was super profound, which was that AI right now is the stupidest it's ever going to be. It ain't going to go backwards. So actually recognizing cool, there are opportunities here to say, okay, let's get something at least plugged in here to try and free up smart minds, because we have as a country right, we have a productivity problem, and I don't think there's a business owner here who wouldn't want to get more out of their people and more out of their teams. But there's this, I guess knowing what's possible and then not fearing it is the critical piece right?
Speaker 2:Yeah, there is the same questions that come into conversations we have with customers around. Well, how do I know this isn't going to be relevant in a year's time, and exactly the same answer that we provide AI right now is the worst it's ever going to be. And you know, 18 months ago we were at 3.5 turbo. We're now here and all our customers benefit from is, as the tech gets better, the overall intelligence gets better. What doesn't necessarily change at the speed of that technology is what your business does, the value proposition it drives to your customers. So the intelligence gets better. Your context remains relatively static. If anything, your context has the opportunity to get more refined because you can now do far more better research, customer testing. Yeah, and you're benefiting from this hyper-accelerated intelligence, and away we go.
Speaker 2:The evolution of technologies is not new either, right, you know, from a marketing perspective, you've gone from early versions of front page websites, which were knocked together through, to now having low code, no code, like web flow environments. Customers want to be marketed and get their value out of this. They can create leads and grow. The underlying moving parts just move, and it's no different. It feels different because I think we're in an age where social media and media has never been more prevalent in our eyes, and I think that kind of goes. Let's go back to 2000, when Amazon was being built and the whole dot-com bubble was pushing. If we had that much social media at that time, we'd be all saying the same thing about the internet. We'd be like, well, what if the internet is superseded in next year?
Speaker 1:you know it's like that classic beginning of the year predictions for this year. It's always this is going to die and it's the end of this and the new evolution of that. Yeah, but things like you said, they kind of have a tendency to either move incrementally or to just kind of continue in that trajectory.
Speaker 2:Yeah, and we're seeing the moving parts. I mean DeepSeek, interesting story. But again, so what? Who cares? I mean the shareholders of video will care, but ultimately what we're seeing is the frontier guys, the opening eyes of the world and the early movers. Yeah, it took a lot of money and capital to get to these points and we're just seeing that change Again. But whether it's true or not, who knows how much money was actually put into?
Speaker 1:that yeah. I mean, I think $6 million is the claim that they built it for $6 million, and who knows? I mean you can yeah, who knows?
Speaker 2:But again, I say this with the greatest respect so what, who cares? We're here to grow businesses, be more efficient and manage their risk. And yep cool, we'll take it, bring it on like if it's. If it's safe, secure and adds value, then we'll bring it into the suite.
Speaker 1:I mean that that piece around being safe and secure, I think, is definitely a consideration. I think, certainly from the conversations that we have, that's one of the perceptions here is like, how do we make this, how do we go under, how do we go through a process here where we can use ai but without giving our secrets to, yeah, to the, to the greater wide world? Yeah, yeah, um, so we're we're getting surprisingly low on time, which is unbelievable. I'm enjoying this conversation a lot, um, but we're in 2025, in january 2025. Here we've got a year ahead of us where the mindset in new Zealand in 2024 was survive till 25. Cool, we made it. We are here in 2025. The optimism is surprisingly buoyant, let's say cautiously buoyant. If businesses want to make 2025 the year that actually things do turn around, what are your? Let's say two to three pieces of advice in the context of AI for business owners, marketers, salespeople this year.
Speaker 2:Because I work in artificial intelligence, it's easy to think that my answer is going to be around the tech and AI. The reason I talk about growth, efficiency and risk is that ever since I started working in business, that's been the core of whatever every business owner and CEO or director is wrestling with. So, whatever time span in the future, how do I make the best of the capital that I've got, how do I grow and how do I make sure I don't go out of business or get on the front page of the Herald all the way? That's the common scenario For this year. I think it's important to look at what is the alternative to doing things the same way that you're doing them right now. You don't dig holes by hand, use an excavator. You don't go and classify ads anymore, and this is now the same for how you humans get work done.
Speaker 2:If you can stare at yourself in the mirror and say, yeah, in 2027, 2028, I'm still going to have people typing at a keyboard to do the majority of this long work and you think that's true, then that's great.
Speaker 2:But if you can't confidently hold that answer and say, look, there needs to be a better way to keep myself competitive and help my growth story and be more efficient, then now's the time to start laying the foundations.
Speaker 2:And the foundations are pretty simple and this sounds like a mercenary comment, but I'll say it how I see it Local specialists get going and don't fall into the hype, and it's surprising how small the investment is to actually do something that's pretty meaningful for your business. So that's kind of how I would anchor it back to is that, if you're looking forward to 2025, it's that honest conversation with yourself about, like, if knowledge is not flowing freely, you've got up to 3.6 hours a day that is just leaking out and you won't be seeing it. Yeah, and how you realize those benefits is totally up to you. In terms of growth agenda or cost out agenda. However, and other than that, how's the work getting done, like? If you're still wedded to a keyboard for all these things, then it's it's time to start building that context and getting those, getting those wins fantastic.
Speaker 1:Well, I think that's kind of wrap us up. I mean, that's a, it's a great outlook for the year that was good, cool.
Speaker 1:Thank you so much. And, um, yeah, if there are any other resources that come to mind, we can share them out when the podcast goes live. But thank you so much, dave, really really appreciate the conversation. All good, thank you. Fantastic Thank you. That's that. Thanks for listening to. We Do B2B by Blue Ocean Now brace for CTAs. If you want to join and grow the community, make sure to subscribe. Wherever your eyes and ears absorb information, don't forget to switch on notifications so you know when the latest episodes drop. And for more B2B goodness, be sure to follow Blue Ocean, the B2B agency, on LinkedIn. Now look, you know how this next piece works. The more reviews we get, the faster this thing grows. So please do for us what you hope your customers would do for you Leave a review and share your thoughts. Let's stay connected and keep the B2B marketing conversation going.