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The show for leaders who want their technology investments to work and understand that starts with fixing the operating model.
- We talk about the work that happens before the system gets switched on.
- We unpack the messy middle between “strategy approved” and “technology delivering value”.
- We teach the execution disciplines that make tech adoption stick.
Biz Bytes
Technology as Value Creator, not Cost
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What happens when you stop treating technology as a cost centre and start viewing it as a strategic enabler for your organisation? Anna Campbell, Chief Support Services Officer at Whakarongarau Aotearoa (New Zealand's telehealth services), provides compelling answers in this thought-provoking conversation about breaking down traditional silos.
Anna's unique portfolio encompasses technology, data, people, marketing, and Māori services development – creating a powerful integration point that puts service users at the heart of operations. Rather than maintaining artificial boundaries between departments, this structure focuses everyone on a shared mission: delivering essential 24-7 health and wellbeing support across New Zealand, helping one in four Kiwis access care when they need it most.
The conversation explores how organisations can shift from viewing technology initiatives as budget items to seeing them as strategic solutions for real pain points. "Keep your mission critical and strategically aligned," Anna advises, emphasising the importance of measuring impact and articulating value in terms that matter to the broader organisation.
Particularly valuable is Anna's insight into responsible AI implementation. Starting with clear ethical principles, Whakarongarau Aotearoa has developed governance frameworks that prioritise privacy, transparency, and data sovereignty. From internal efficiency tools to clinical note summarisation, their AI applications follow the guiding principle of "nothing about us without us" – ensuring that technology enhances rather than replaces human connections.
For leaders navigating technological transformation, Anna offers practical wisdom: understand both the capabilities and limitations of tools like generative AI; focus on reimagining work rather than merely automating existing processes; and remember that change management requires acknowledging what's not changing alongside what is. By meeting people where they're at and maintaining trust throughout the journey, organisations can harness technology to deliver truly human-centred services.
Ready to transform how your organisation approaches technology? Listen now for insights that bridge the gap between technical possibilities and meaningful organisational impact.
Today's episode features a valuable discussion on how businesses can strategically align technology, people and processes to drive genuine impact and achieve sustainable growth. We move beyond viewing technology merely as a cost and instead focus on its role as a core enabler for operational excellence and competitive advantage. I'm speaking with Anna Campbell, the Chief Support Services Officer at Whakarongarau Aotearoa, the New Zealand telehealth services. Anna's unique portfolio encompasses technology, data, people and marketing, providing a compelling case study on breaking down organisational silos. In our conversation, anna shares how Whakarongarau Aotearoa leverages integrated solutions to deliver essential 24-7 health and wellbeing support across New Zealand. We explore the strategic rationale behind their consolidated structure and the clear benefits it brings to both service users and internal teams.
Speaker 1:We also delve into the critical topic of artificial intelligence. Anna offers a pragmatic perspective on whakarongura Aotearoa's responsible and ethical use of AI, from internal efficiency tools to enhancing clinical support, always with a strong emphasis on privacy and multi-data sovereignty. This discussion offers direct insights for any lead in navigating technology transformation, aiming to optimize operations or seeking a clear path to AI adoption. Anna's advice on shifting the perception of technology from a cost to a value add and the importance of foundational principles is particularly relevant for driving tangible business outcomes. Join us to gain a clearer understanding of how integrated strategic thinking can truly fuel sustainable growth in today's dynamic environment. Kia ora Anna. Welcome to the show today.
Speaker 2:Kia ora. Thanks for having me. I'm looking forward to it.
Speaker 1:And great to have you as a guest as well. I'm going to ask you to talk a little bit about your background, because it's an interesting topic that I talked on a couple of episodes ago with Moderna's merger of HR and IT functions, and it's something you're living as well with your organisation and we'll journey down that one in a moment. But talk to me about what your role is in the organisation you're working for.
Speaker 2:Yeah, sure. So I am the Chief Support Services Officer for an organization called Whakarongaro Aotearoa. So we're the New Zealand telehealth service for the country and our job is to put health and wellbeing support in the hands of all of New Zealanders. So generally, we help one in four New Zealanders get the right care in the right way, and we're a social enterprise. We deliver free, government-funded national telehealth services 24-7, across a number of different digital channels. We've got 30-plus services that we offer. Probably the most well-known one's a health line, which is the line that you call in the middle of the night when your child is sick, and 1737, which is our text, mental health network.
Speaker 1:I've been a big user of Healthline. Yeah, it's saved us a couple of times.
Speaker 2:Oh, fantastic, yeah, and I mean that's the point of it. Right is that we are able to triage and get people the care that they need in the moment that they need it, at the right sort of level, and my role is the Chief Support Services Officer there, and so my portfolio covers all the technology data program teams, the people and capability team, maori services development and our customer and marketing team, so it's really across the end-to-end people technology process in the organization that helps our frontline clinicians absolutely do what they do every day well.
Speaker 1:Yeah, nice, and that's something I've been talking about a lot and we talked about before we started recording on this as well which is that technology. When we often talk about IT, it's used as a blanket coverall, but really there is an element of people, process, system and partnership in there. Like I say, you guys have got that structure. What was it that sort of drove you towards having those the two departments particularly, but also marketing. What was the decision to wrap those up under one reporting line?
Speaker 2:I think any executive's role in an organization is to put the customer at the forefront of what they do, and we've realized as an organization that, in order to do that, any change that you drive through an organization these days really often is a technology change that impacts your people yeah and then you need to tell your customers about it so that triangle is really an end-to-end operating system across the organization.
Speaker 2:So we just we just think in that way and it's interesting when we put that structure in place. To start off with, there were questions from the team about how is this going to work, why are we doing this, what is this going to achieve? And now in my leadership team meetings regularly the team's talking about the synergy that we get between those departments and that we're able to deliver much better outcomes for our kaimahi. So the people that work in the organisation and our tangatawhai ora, the people that call in looking for support, because we're breaking down the thinking that stays within the functional channel to be much more about what are the outcomes that we're trying to achieve and what are the big problems that we need to go after.
Speaker 1:To simplify or solve yeah, and let's stick with the benefits. We'll come back to the challenges along the way later. But how quickly did that sort of start to happen, and was it an organic change, or is it something that you really had to? And by organic, I mean, did it sort of come naturally to the people around the table, or is it something you had to work on with them to build up?
Speaker 2:I think we were really deliberate about it. So, um, you know, very deliberate and very determined that our job was to make things better for tangata whaiora on a daily basis, and we recognize that to do that, the, the mixed skill set that we had, um, and the diversity of thinking that the different specializations bought was going to help us deliver better outcomes. And really we committed early that, as a leadership group, our job is about experience and it doesn't matter what the title is.
Speaker 2:We're either creating amazing experience for the people that work in the organization, people that the organization serves, or the tooling that you know, the tooling that people use and so that that focus on the outcome that we wanted to and the impact that we wanted to have meant that that team gelled really quickly yeah, and I guess the the benefit that that builds into with that speed of gelling is also that it stops everything else being an afterthought.
Speaker 1:And what I mean by that is I've worked in corporate environments before worked for a bank, where there were a lot of silos because of the structure of the organization and things tended to be an afterthought. You know, a technology conversation can get quite far down the path of delivery before anyone thought to wrap it back to the people or to how we're communicating. But equally, a marketing journey could do the same If you go quite far out before technology got brought on board. You guys are cutting that off, aren't you?
Speaker 2:As much as we can. So that's our intention. You know human nature comes into it, so nothing's perfect, but yeah, we are and we're being very deliberate about that process, and I think any organisation that starts to think really clearly about you know, is this right for the customer, is it right for the people and can we execute it really well? Then you're are delivered in a much more cohesive way, because you've thought about that triangle up front and really, you know, remove technology, remove AI, remove any of those things. A leader's job in an organization is to get people to do differently than they did and imagine a different future. So to do that, you have to bring those three parts of the triangle along with you. So, yeah, it works really well.
Speaker 1:Yeah and look it works really well. Yeah, and look, I agree it's not an all or nothing kind of approach, it's a collection.
Speaker 2:I think my challenge sorry to interrupt you, but my challenge back to organizations is I don't think it needs to be a structural thing though. So for us that structure works really well. But actually silos in an organization is really the result of a question that hasn't been asked yet or a conversation that hasn't been had. So it doesn't matter what your reporting line is or what your formal structure is in an organization. If you're taking that mindset of the outcome that you're trying to achieve and that you need those multi-points of expertise, then it shouldn't matter whether the reporting line is gelled or not. It's about putting the outcome at the front of anything you're doing, and so you're having the right conversations in an organisation, Yep.
Speaker 1:I've often talked about it as being a problem-first approach, which is figuring out what problem you're trying to solve and then working your way back from there to actually solving it. And you're trying to solve and then working your way back from there to actually solving it. And you're right on that one you don't have to have everyone reporting to a single point to make it work, as long as everyone's at least focused on that problem.
Speaker 2:Yeah, I think you know, then, one of the advantages of having that single point is that you've got that broader oversight and you can make the connections for people if they haven't lined those up themselves. So you know, that is one advantage of it, but anyone that's had a tech role would know that they spend a lot of their time politely telling people yes, that's a wonderful, new, shiny tool that you've found. Can you just describe the problem that you're trying to solve and the impact that that's going to have, and the impact that that's going to have, and then let's start at that point and then we'll come back to whether this is going to be the right. If it's still shiny at that point, is it still?
Speaker 1:shiny, is it? Is it? Yeah, yeah, absolutely. And and I've seen it too often with with the we've got an idea, we've got an opportunity, we're going to deliver this outcome. Like cool, what? What problems is this? It doesn't solve any problems. It's just we were promised a deal if we could turn it on by the end of this quarter. This isn't going to go so well for someone.
Speaker 2:Yeah, yeah.
Speaker 1:So what other challenges have you run into? Whether internally or externally, has there been many other challenges in the way this structure has sort of evolved and grown?
Speaker 2:Yeah, um, no, actually it's been. It's worked very well for our organization. Um, obvious normal teething structure changes that you have when you're setting up a new team. Um, but actually as a, as a leadership team, we've worked really hard to make sure that everyone in the wider team knows each other as people, understands our mission as a team, understands how the work that they do every day fits into their overall picture and why they're part of that broader team, and actually that's been a really fun process. And so, as a result of that, if you take things like I don't know, an induction program or something like that that touches all of those functions and so they understand each other's input into it, I think appreciate each other's work a lot better. Um, understand what those different teams are trying to achieve and then how collectively it rolls up to serve the um. Our tangatawhai ora um on a better on a better way.
Speaker 2:Nice, have there been any?
Speaker 1:and I'm going to come out here on a better way. Nice have there been any? And I'm going to pick on other roles in the organisation here when I do this. Have there been any challenges from outside your team? I'm looking at finance, because they often can be a barrier to driving change, but have they bought into this as well?
Speaker 2:Oh look, we're a small, tight team. Our finance team is fantastic. We have a great team model where we have robust debate in our organisation. We love the Lencioni model. So we start with a basis of trust, have great debate and then move to agreement and accountability so that we're delivering results results, and so we focus on trying to unlock capacity in the organization capacity and creativity. We have um a whole lot of clinical experts that, um you know, our job really is to make sure that we're unlocking their, their capability, on a daily basis, and I think you know the finance team and us are really aligned on that and actually they've been really helpful in helping us define. What does capacity mean?
Speaker 2:and how do you unlock capacity and how do you actually measure that, rather than focusing in on this function is around just cost saving or you know a lot of a lot of functions. A lot, I think, focus in on how do you use tech as a cost-saving device rather than a value-adding device. And you know, while, like all organizations, we definitely have goals around streamlining our technology, making sure we don't have any redundant services, making sure that we've got it right size for the organization redundant services, making sure that we've got it right size for the organization we are all really aligned on making sure that we are safely delivering good services and we're helping our frontline team be able to do that to the best of their ability. So, you know, I think finance helps us in that respect a lot.
Speaker 1:Yeah, nice, nice. And one of the things I did want to ask you about was on that cost center versus value add piece. So let's go there now For anyone listening to this who's exploring a change, transformation and it doesn't have to be as bold as starting to align these services the way we've been talking starting to align these services the way we've been talking but what would be your advice to someone who's about to embark as to how they approach that technology as a value-add mindset.
Speaker 2:It's tricky right, Because technology functions often have the biggest budget in the organisation. So if there's any financial pressure, that's the area that people come after to try and deliver cost savings and efficiencies in the organization, and I think that's a realistic part of the role that you've got to understand. However, if you are going after the right things in the organization and you are understanding the drivers of the organization, where the pain points are in the organization, then you can really quickly flip that conversation to be a value-add conversation.
Speaker 2:So it kind of loops back to what we were talking about before really understanding the problems that are going to have the biggest impact in the organization and are going to take away pain points for the people that work in the organization or the people that use the services of the organization, and so to me it's about getting real alignment to what is the strategy of the organization, what are those pain points and then what are the big problems that we're trying to solve, and then being very rigorous around prioritising around those aspects. Second, I think, is measuring your impact and being able to talk about the impact that you're having. And third is really knowing your numbers so that often you need to make an investment up front to be able to deliver either savings or capacity or problem solving. Being able to really articulate that in a way that makes sense to the business and loops it back to the issues that the business is trying to solve. So you know in a more succinct way, it's like keeping your mission critical and strategically aligned.
Speaker 1:Yeah, yeah. And it's interesting there as well, because for many New Zealand businesses putting this into a New Zealand context for many of them their technology team I'm using quotes here is largely outsourced. They're using tools that they've picked up off the shelf, and it's more than just the traditional tech functions. They've got an HRIS, maybe they've got well, they've definitely got a finance system of some sort. So when you look at it from that sense, traditionally many organizations don't have ownership around those. They don't have someone owning finance. It's pretty clear that it's owned by the finance department. But a CRM or an HRIS gets a little bit vaguer as to who's responsible, and what you've kind of got here is actually we've got a function who's responsible for not just the people that deliver tech but the systems that our people use as well.
Speaker 2:Correct. Yeah, I'm really keen on co-ownership as well. The tech has to work and it has to deliver to the people. So if you think about our structure but again structure agnostic you know there's a human experience, there's customer experience, there's your tech experience, everyone is experience owners. So if you put the experience at the forefront and the impact and the problems you're trying to solve, then actually we all own those things.
Speaker 2:We have the functional ownership in the HR team for an HRIS, and we maybe have the functional ownership in the HR team for an HRIS, and we maybe have the technical ownership in the tech team, but ultimately, if the system doesn't work, it doesn't work and the people who are trying to use it suffer. So, rather than arguing about who owns it, actually, if we focus in on who's using it and what's the experience that they're having, we can have a much better outcome as an organization yeah, absolutely, and I think that that line of sight and it's a good way to put it back around is the impact on the user base.
Speaker 1:But that also you've got better line of sight than a lot of organizations, I see, where there's just no one in the middle between the user base and the decision makers, so the decision makers may just never know that what the people are using isn't working. And you've at least put that middle call it an integration point but that middle layer in there that says here's what we're hearing from the people who are using this tool, but that middle layer in there that says here's what we're hearing from the people who are using this tool.
Speaker 2:Yeah, and also I think in anything you're doing, and particularly if you're starting to move into the AI space as well, that that frontline feedback loop is really critical. So making sure that their view is integrated into your design thinking and you're giving them tools and ways to provide that feedback also means you're going to get a better outcome, because the person who's on the phone talking to the people who are contacting your service knows so much more about what they need than someone who's sitting in the support centre. Regardless of how focused they are on a good outcome for that service user, it's the person who's dealing with them every day that knows what they need, but also knows the things in their flow of work that are causing them issues in terms of being able to deliver that amazing service. So you do have to listen to them.
Speaker 1:Yeah, definitely, and I think there's a really good point in there as someone who's used the health loan service before. As I mentioned, what I found really valuable with the service was the uh. The nurse that I ended up dealing with for our daughter had um an infection and we were ringing health line as a first point and she was able to. Because of the tool she was using, the way she was approaching it, she was able to focus more on the triage than on the technology and the questions she needed to ask, if you catch what I mean there yeah, and you know first.
Speaker 2:You know first of all, we have the most amazing team. We are so lucky with the clinical experts that we've got and they help so many people in exactly that situation, Right when you're really vulnerable in the middle of the night and you're really worried about your child. The work that they do is just phenomenal. Very, very proud to be associated with those awesome humans. If you've got your tech working right, you shouldn't notice the tech in the process. It should feel really human still, even if you've got really advanced tech working in there. I think the trick to making tech really successful is remembering that it's a human interaction that you're trying to create and the tech should support and enhance that and protect it. So your governance and your stance around privacy and your stance around ethics and how you make sure you keep everything safe is really important, but ultimately it's about enhancing that human connection and human experience 100%.
Speaker 1:Yeah, the example I remember. Remember. It was made the call. Obviously, a nurse can't see a child through a phone, and so she asked for a photograph. It was a. It was stagylitis on her arm.
Speaker 1:We we had a link that she she sent us a link that we were able to take a photo, upload the link and then within seconds, it was a straight, straight case of yep. That's what this is. You need to go to um after hours. Perfect again. Like I said, the focus was on the triage, not the system inertia that she needed to overcome to be able to do that correct.
Speaker 2:Yeah, and ultimately, when you're calling in, you're in distress and you want to know that you're getting really solid advice. That um one-way photo has been really phenomenal for our um service users. It means that, as you've just described, the nurses can see what is going on really quickly and provide the assurance of no, you're fine to stay home, or actually you do need to go in to see someone and you need to go quite quickly.
Speaker 1:Pretty quickly.
Speaker 2:yeah, and we were joking about our locations and living. For people like you that live out of the city, that's a big deal to have to in the middle of the night drive into an ED. So you want to know that you need to go right.
Speaker 1:Yeah, yeah, exactly, and you've been given that guidance that when you're standing in front of the registrar, I guess at the hospital or the ED or wherever someone's told you to be there.
Speaker 2:Yeah, that's right.
Speaker 1:Yeah, yeah.
Speaker 2:That's right yeah.
Speaker 1:That's right. We were armed with just that little bit more information that wouldn't have otherwise been there, and I think that's really good. As a service user, I think it was fantastic.
Speaker 2:That's so good to hear.
Speaker 1:That led me to a logical question, I think.
Speaker 2:You've been AI.
Speaker 1:I'm not going to ask where you see that fitting into the service model, because I think that's the wrong way of looking at it, but obviously there's benefits to it. And with the structure you've got, how are you able to approach assessing and prioritizing AI-based initiatives? And I'm using AI very broadly and I'm hesitant to do so, but in this context I'm sort of covering all the different bases generative AI, machine learning, predictive analytics, et cetera, et cetera. How are you approaching that in this structure?
Speaker 2:We we've been doing a lot of work with AI. We think that it has huge potential in the health and social service sectors, used well. Our starting points have been, first of all, thinking really carefully around what are our ethical non-negotiables and what are our principles of application? So for us, it's things like choice. We innovate responsibly. You know we're focused on the mahi that matters most, so enabling our clinicians to continue to provide excellent clinical advice, that we're transparent, so people will always know if they're dealing with a generative AI. So we are very proactively using AI in a very safe and carefully governed way. We make sure that our frontline voices are included in our thinking about AI, are included in our thinking about AI and, like I said earlier, our intention is that the AI fades into the background and lets the human shine. So we are using it in a number of different areas. So we have an innovation lab, we have an internal innovation lab and we also have innovation lab partnerships with some of our strategic allied partners and we've developed some in-house tools which are just going live now actually. So one is our CoopSpot, which is ring-fenced around policies, protocol, finding information for people in the organisation Now obviously really carefully ring-fenced and ragged appropriately, and that is to facilitate people getting information in the organisation. We have a bot that sources all our HR data and information to help people there, and those fall under our banner of the Mara Kowhānau, which our virtual team member really, really that's there to support us and you know, those are iterative design processes where we get feedback from our frontline feedback from people in terms of the digital innovations that they'd like to see, and then we build things to support them.
Speaker 2:We're also using note summarisation in some of our calls and that's been really helpful for some of our people that aren't the fastest typists, so it means that they can really focus their attention on the call they're in, not on the notes, but they still maintain complete control over the note before it's submitted so they can check and change it and make sure that it says exactly what they wanted to say, but again, just downplaying some of that mental load that they have, that they can focus in on the person who's on the call that they're serving and not have to multitask as much.
Speaker 2:So trying to unlock their capacity really and provide them with support. And then we are working with some really cool partners at the moment and working in the space of how do we help people when they contact us in that delay point before they get to one of our specialists, but they still really need help. So how do we hold them with empathy in a really, really safe way but also be the interaction when they get to a person as well, because we've captured some of the key stuff that's going on for them?
Speaker 1:Yeah.
Speaker 2:So you know we.
Speaker 1:It's used on multiple levels across our organization. Yep now, and you've got a very interesting problem but one of the better word here with ai and with data in particular, and that you've got. You've got employee data, you've got company data that's one silo there. Then you've got company data that's one silo there. Then you've got service user health data because they're ringing through with medical problems and there's health data in there. And then you've got individual data around service users, particularly that are coming through the Māori health sector and know that Māori treat view data in a different way to Western norms and treat it as a taonga. So you've got these three different elements of data that are all useful, but you're going to have to treat them in a different way. Have you had to go through a process where you are either segmenting or siloing those data sets so that you're not just tripping over yourself as you try and implement some of the AI initiatives?
Speaker 2:So we are treating really carefully from a data perspective. Privacy is our number one priority, so we prioritize privacy. We don't train our AI on any of our service user data. If we did do something like that in the future, it would be fully with permission and we would be extremely careful about that process. We are completely transparent when we're using any form of AI in the organisation and we're giving a really good thought to Māori sovereignty, particularly in relation to data, and our approach is really nothing about us without us. So for us, we're seeking input, we're seeking guidance and we're being really careful about where our data is stored, having assurances about what any providers do with our data, having assurances about what any providers do with our data.
Speaker 2:You know, we recently partnered with Microsoft and we were one of the anchor tenants that moved into the Microsoft North Asia environment, which means that data is in New Zealand and stored here and in the cloud, and we know where that is and we know that that is ring-fenced and very carefully managed. You know, we know that that is ring-fenced and very carefully managed For us. We work really hard to be very respectful and to embed tikanga Māori into our services and we take the same approach with our data and recognising that actually, you know, for Māori, actually for any indigenous group of people globally, it's really important to keep that ownership of their data, and AI has the potential to be really significant in terms of revitalizing some of the language and creativity and art for Indigenous groups. It also comes with a great risk and great responsibility around making sure that there is huge work to protect that data as well and make sure that it's used in a way that is absolutely aligned to the way that the people who own entries of that data want it to be used.
Speaker 1:Yeah, definitely, because, at the end of the day, every organisation goes down the path of who owns the data. But I kind of hold a view that the individual who gave you the data always owns that data as long as it's about them, and I like the point that you made about how did you say it? It was, if it's with us, includes us. What was it?
Speaker 2:yeah, nothing about us without us that's it, yeah yeah, and so you know we that's a different way of phrasing one of the principles that we applied right at the start of our ai journey, which was that, um, you know, no one owns the best ideas. Everyone, everyone is learning on this journey together. We have to go into it with really clear boundaries of what we will and won't do ethically and then govern it really well to make sure that we continue to stick to those principles. Yeah, and you know, protecting our service users is such a priority for Whakarongaro and it should be for any organisation.
Speaker 1:Absolutely. You need to take those things very seriously and that principles first approach. I really really like organisations when they're doing that as well, because they've at least got something they can draw back to as a first principle. And if privacy is the one, is this decision going to breach that principle of privacy? Yes, we're not doing it. It's very simple.
Speaker 2:Yeah, and that's how we make our decisions. So we do. We check ourselves against our principles all the way through. And back to your question around how can you? I can't even remember the question now, but I think it links back to that where you have those principles as one of the very first steps that you need to take when it comes to AI, to that where you have those principles as one of the very first steps that you need to take when it comes to AI. And once you're clear on those, it actually makes the rest of it easier, because the technology is evolving so fast and we're all trying to learn and keep up with that technology. But the principles really ground you. And what are you here to do? What are the things that are important to your organization? Who do you need to protect in that process? And so then, when you're doing the work, it just removes that cognitive. Then when you're doing the work, it just removes that cognitive load when you're trying to make decisions with ambiguous information.
Speaker 1:Absolutely, absolutely and definitely with. The principles also tie into the broader conversation that I often have with clients around teeth of what's the problem we're trying to solve? Can we do it with this tool? Can we do it with this tool? Should we do it with this tool?
Speaker 2:Correct.
Speaker 1:And if we do it with this tool, what principles are we struggling to achieve by doing so? Or, I guess, are we going to break any of our principles. And if you can answer all four of those questions, what problems are we trying to solve? Can we do it this way, should we do it this way, and what principles are at risk because of that? You actually get a very clear decision.
Speaker 2:Yeah, that's right, that's right.
Speaker 1:Yeah, what's your advice to anyone who hasn't got those principles in place yet? Where would you suggest they start? How should they go about that?
Speaker 2:Oh, look, use AI to help you find them. We're happy to share our thinking with other organizations as well, because we've put a lot of work into our governance frameworks. Um, but really, um, it's about centering in on what are the ethics that you were going to apply to this, what are your strategic principles, and then being really, really staunch about them. How are you going to measure and hold yourself to account to them? Um, and then the rest of it becomes quite clear.
Speaker 2:We have governance meetings, we have measurement. We hold ourselves accountable for delivering the results that we said we were going to deliver. We also stop things really quickly when we know that they're off track or they're not performing, and that's totally safe in our environment, and so I would encourage you to think of somewhere between three to 10 principles that you are going to follow, and then just follow them. Microsoft has great guides about using AI. Lots of the big players out there have got really good information out there that you can use, and they share that to help you on your journey. And, like I said, happy to share some of our thinking about principles as well.
Speaker 1:Definitely and this is the enterprise architect in me coming out I've done too much work, yeah, yeah, I've been down that pathway plenty of times with clients and organizations as well. It's an interesting journey, particularly if you can get into not so much a disagreement I don't think it's disagreement but a different viewpoint on what one principle may or may not mean, as you're creating it as well.
Speaker 2:Yeah, and I think if you really think about not just AI but technology in the realm, people often forget that the impact is an emotional impact that it's having on people. So they think about the tools or they think about change management, but they forget that all of it is an emotional impact. But they forget that all of it is an emotional impact, and so you're dealing with that raw part of being human, and so, ultimately, everything you do will build or detract from trust. So your principles need to be around. How do you ensure that you're maintaining trust and building it in an environment where people are taking on new things and for some people, they're really excited about AI. Other people feel really nervous about that, and you've got to be able to maintain trust right through that process.
Speaker 2:So that's why I hold true to the principles being really important, because those principles catch you and stop you from doing things that are going to erode trust along the way, and your job as a leader really is to be able to frame up the future. So if you do it in a way that builds trust rather than erode it, then your team feels really heard through that process. Your customer ends up feeling really their needs are anticipated and they feel appreciated, and you're removing noise so people can show up at their best, instead of worrying about the technology and that's a really important part of a leader's job is, you know, creating that vision and then um helping people regardless of where they're at. I had great advice from someone once that I hated at the time, but I it often is meet people where they're at.
Speaker 1:Yeah, you should meet people. I was just talking about that in another group this morning. Exactly that when it comes to AI Meet people where they're at, work with them where they're at. And I liken it back to some advice I once had years ago from Carly Orr, who's a change and people leader as well, but a change very, very experienced change manager, and she was walking us through the seven steps of change and she said one of the first things you need to be doing for people is reminding them or not even reminding them, but telling them very clearly what's not changing as much as sorry, fully interrupted you, but yeah, I couldn't agree more right, and so much doesn't change.
Speaker 2:So much doesn't change and we forget to talk about that. And I get frustrated with change models that you know. It's like create a burning bridge. It's like, yes, there is a need to change and this is the problem we're going after solving, but actually all this is the stuff that you just don't need to worry about because that is still the same no, exactly that's even.
Speaker 1:She even used um, a building move as an example in there. She said you know, I don't offer the move happening all the time and you can take for granted that people are going to be fine with an office move. But part of your change messaging needs to be that on Friday you'll leave and on Monday you'll come into the new office. You'll come in through the lift, you'll walk out of that lift, you'll find your. You'll come into the new office. You'll come in through the lift, you'll walk out of that lift, you'll find your desk. You'll sit down at your desk. Your computer will be there, you'll turn your computer on, you'll log into your computer and your work will arrive and start being done. None of that's changing. What's changing is this is the new key card you'll use to access that. Toilets are over there instead of over there, and I'm pointing left and right here, and the kitchen is around the corner and the coffee machine is there. Um, that's the stuff that's changing that you need to know about, but the rest of it it's not changing.
Speaker 2:You still need to know that yeah, I think what's interesting at the moment for people is generative ai does feel like it's at a pace of change, yeah, and I would just really encourage people to do the work to understand what generative ai is, what its capabilities are because there's amazing opportunities but also what it can't do and its limitations. And so the more you know about it and the more you understand how it works, the less afraid people will feel about it. Because, while I think you know the work isn't going to go away how we do the work and you know the work isn't going to go away, how we do the work and the you know the work as we know it might change, but the people who are going to emerge well through this and the companies who will come out well through this change aren't the ones that just think about re-skilling. They're the ones who think about re-imagining how things can work, and you know, that takes leadership, courage and it takes curiosity and it takes all those soft skills that humans have.
Speaker 1:Yeah, and it's a really good point is that generative AI seems like it can do so much, particularly when you're watching videos of Bigfoot finding an energy drink and walking through and catching his fish. They're great video, they're good for humor, but they don't have that human factor in them and all they are doing is just showing you this is what you could use AI for. They're not showing you the human side of what's gone into that process to get there in the first place.
Speaker 2:And I think if people really think about ai as an opportunity to, I guess, digitize and streamline a whole lot of the stuff that's annoying at work and, um, really emphasize the stuff that is intellectually stimulating and, um, that human to human contact you know that's quite a nice way to frame it so by by all means automate all that stuff there, that a cognitive load and takes time, and then think about what is the space it gives me then to deliver in the organization and how can I go about my work differently and what can I create as a result of that.
Speaker 1:Absolutely, absolutely. It's been great chatting with you and I'd just like to start to draw us to a close here. Is there any final thoughts you've got on organizations that are either looking to people we'll call it people, not organizations, because it's a human decision people that are considering how they might bring certain functions people and tech, or people and marketing, or tech and marketing closer together, and then any final thoughts on what AI could mean for them as well?
Speaker 2:Oh, that's such a big question, isn't it? Yes, yes, so you know, I would say go for it if you want to bring those things together, whether you do that structurally or intellectually, because to be successful you need to think about that enterprise view, but also the customer, the employee journey, and solve the problems for them. Either do it structurally or do it by having good conversations and asking good questions and understanding the linkages outside of departments, so that you can get a better outcome for everyone. But it's working really well for us having that team that is specifically focused on delivering capacity into the organisation and better experiences for our customers and our kaumahi. So I encourage you to think about, whether you do that through structure or not, how you can do that.
Speaker 1:Then I've forgotten the second part of your question, which was Our second part of the question was for just where the future of AI, or the future of work in general, might be taking us as well.
Speaker 2:Oh, I think, on quite an adventure. So you know there's just wonderful opportunities. When I think about some of the big challenges, particularly in the wellbeing space, you know there's significant mental health issues, loneliness issues. People are trying to do more with less across every sector, every industry, so frame the AI as an opportunity. I do think it comes with a huge responsibility for leaders in the organization, though, to really think about what is their job in this, and do they want to shape how AI is used and is it used for good, or do they want it to shape them so?
Speaker 2:you know, get ahead, understand and then deploy all the really human skills around courage, curiosity and care consistently across your thinking, because, ultimately, the decisions that we make right now are going to have an impact on the next generation, so we really want to get that. So I think leadership is always a responsibility. Right now, ai has to be approached. It's a strategic capability that you need to have as a leader. You need to understand it. So your job is to understand, take calculated risks, be courageous and then translate for the organisation why it's important and how people still matter.
Speaker 1:So thank you so much, and, anna, thank you very much for your time. Where's the best place to find you if anyone wants to follow up questions, particularly around the principle and some of the other stuff we talked on?
Speaker 2:Oh, good question. So they can reach me at Whakarongaro or they can contact me via LinkedIn if they want as well.
Speaker 1:Excellent, perfect. Thank you very much, anna.
Speaker 2:Great talk, thank you.