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AI's Impact on the Future of HR: Insights with Annie Johnson from Humaneer

• Anthony McMahon | Target State • Season 3 • Episode 8

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Discover the future of HR through the lens of AI innovation with Annie Johnson, co-founder and chief product officer of Humaneer. Annie takes us on her incredible journey from a traditional HR role to spearheading AI-driven solutions that are reshaping how organizations operate. She uncovers the concept of purpose-led design, aligning technology with company values to create ethical and effective AI systems. Annie doesn't shy away from the tough topics either—addressing fears around AI, job displacement, and transparency, while offering practical strategies to mitigate these concerns.

As we continue, the conversation highlights the complexity of media's role in shaping public perception, particularly through fear-based narratives and information overload. By comparing industry-specific insights to mainstream media's sensationalism, we explore the balance needed to stay informed. With a keen eye on governmental and regulatory challenges, we delve into the importance of clear guidelines for privacy and security in this digital era. Annie shares how startups like Humaneer make strides in fostering an AI ecosystem that prioritizes safety and productivity.

Our discussion also reflects on the broader implications of technological advancements on job evolution, emphasizing the need for a thoughtful integration of AI that augments rather than replaces human roles. By examining historical shifts in job markets, we advocate for a strategic approach that aligns with organizational goals and enhances the human element in work. Join us as we celebrate the innovative spirit of New Zealand, where Annie and her team are making remarkable progress in crafting AI solutions for the HR industry. This episode is packed with insights, strategies, and a hopeful outlook on the collaborative future of AI in the workplace.

Ant McMahon:

In this episode, I carry on the conversation on the world of AI and its transformative impact on the HR industry. My guest this month is Annie Johnson, co-founder and chief product at Humae. She shares her unique perspective on how AI is reshaping the future of work. We explore the rapid evolution of AI, especially since the mainstream surge in late 2022, and discuss the critical importance of ethical AI implementation in HR. Annie sheds light on common fears surrounding AI adoption, such as job displacement and lack of transparency, and provides some good strategies for mitigating these concerns. We delve into the concept of purpose-led design, a framework that empowers organizations to harness the power of AI while aligning with their core values and long-term goals. Annie explains how startups like Humane are at the forefront of AI innovation, offering flexible and customer-centric solutions to address the unique needs of the HR industry. Join us as we unpack the potential benefits and challenges of AI and discover how your organization can navigate this exciting and complex landscape. Hey, annie, welcome to the show. Thanks so much for coming on board.

Annie Johnson:

Awesome Thanks, Ant. It's so great to be here.

Ant McMahon:

Just before we get into some of your background and where you're going humaneer and purpose-led design, just for our listeners, give us a bit of an introduction about yourself.

Annie Johnson:

It's a big story. It's quite convoluted in a way. I've spent 20 years in the HR industry and listening to Melissa's podcast with you. I went the opposite way, so I studied psychology down here in Canterbury, went into the HR industry and ran a traditional career path, popped out into a commercial role and did a bit in the general management type space and started to get into a little bit of tech and enablement. So working with a business and ripping apart that ecosystem and rebuilding it to make sure that we were more efficient and that work was being done in the right way, that sort of gave me a healthy dose of passion around tech and human enablement. I popped out of that role and then started running my own consultancy when my daughter was born and so the honest human came from. You know I need to start paddling my own canoe and I really wanted to work with SMEs in the HR space, but a very commercial lens. I'd learned a lot from from being a general manager and and so bringing a different flavor to how you create people strategy and how you create the right environment and culture for your people to enable them became what the Honest Human was about.

Annie Johnson:

And then AI burst onto the scene in what was it? November 2022. And I was what you would call an early adopter. My first prompt in there was can you write me a position for a sales manager? And it just blew my mind and from there a light bulb went on. It became a good sort of two years of intensive curiosity around the technology. I could see where it could benefit so many industries and teams and roles, and so I started to think about you know, our industry in HR and and we were heading we suffer a lot of burnout. In our industry. We are heavily compliant driven. We deal with a lot of administration, so it became a bit of a side passion trying to look at how we can use AI in our roles as HR in a really ethical and safe way.

Annie Johnson:

And so this year I met the girls Humaneer him and Corrine who were building out a similar product in Australia whilst I was building here in New Zealand, and so we decided to join forces and it's a really awesome story of connecting randomly on LinkedIn. Over several months, we were having calls weekly, sometimes three times a week, and we realized we had a really aligned vision and a huge purpose around supporting our industry, hr and building one community that supports the industry, so that is the Humaneer Community App, where it's free to sign up for community members. That creates a really safe space for support and connection and development um, something that a lot of us don't often have. And the other side of it, which, which I lead as chief of product, is our hr ai productivity partner, and so that has been built around.

Annie Johnson:

A deep understanding of what we find in HR takes a lot of our time, which is not necessarily the awesome work or the work that contributes to helping an organization and grow. So a lot of what we're doing is really listening to the community to understand the fears around AI. What do they need in terms of a safe and secure product? What would they want to see in there in terms of how it helps them and augments their role so that they can go back to, you know, being the people, people. So we're on a really big journey and it's been super exciting. Kim and Corrine are just amazing co-founders, hugely inspiring women, and so coming together it's been such a dream. A lot of hard work, and we're really excited for 2025 and what we're going to deliver.

Ant McMahon:

Nice, thank you for that background and there's something in there I'm going to I was going to talk about purposely, but we'll come back to that because something you said I think is a really good point, and it's the fears around AI. To me, from looking at it from the tech lens back, there's been a lot of hype, particularly in the last two to three years, around what AI can do, what it might mean for us as humanity and how it might take our jobs and take us away. Do you feel that those fears are commonly held and do you feel that they're accurate from the conversations you've been picking up with the community?

Annie Johnson:

Yeah, that's a really good question and it's a big question. When I hear about fear that can be on so many different levels, there's a lot of fear around. You know the narrative that AI is going to take your job. You know people are wearing t-shirts and and it does nothing to support the good use of AI and and you know the ethical use of AI. So you know there is a lot of fear around people's roles disappearing and in the pace in which that might. There's a lot of fear around the transparency with AI. When you start to get into things like source credibility and you actually start to talk to people about where that information is going and what's coming back, you can sort of see a bit of a light bulb go on that.

Annie Johnson:

Perhaps I've never fully understood this technology and what it's doing. I think there's also a lot of fear around the pace in which this is iterating. It's created an incredibly intensive time for individuals and organizations and that pace when we don't have time to sit in that change and understand it and feel okay about it and we're almost forced to move with I talk to it can be a number of things that is creating that fear and so talking to our community, particularly in HR. We play a big role in this change and supporting employees and people to understand this tech and the risks and manage that process. This tech and the risks and manage that process. You know we are shepherding businesses and leaders and employees a lot of the time when we don't necessarily understand the technology ourselves. So that's a big ask.

Annie Johnson:

But also within our industry alone, within any industry, you are racing to try and understand what should I use? You know, how do I use it? What is the security? Is this? Right? You know it's a lot of sort of personal questions that come into it. So fear is a big one. Fear is a big one. And look, I think with the hype curve, it's not going to go away, because the way in which this is iterating that hype curve just seems to be ongoing. Right, there's the original stage of gen and AI and everything that starts to come over top of that in this race to AGI. You know, people just don't get a break from it, and so it is something that we need to manage really carefully and really understand it, sometimes at the individual level, which is quite hard when you're potentially an organisation of 500 people.

Ant McMahon:

Yeah, absolutely. And really good mention of the hype curve there, because traditionally the tech if we follow that technology goes through a point of what they call the trough of disillusionment. And I feel, looking at where we've gone with AI and particularly generative ai, is that it really jumped that trough pretty quickly. But what happened was not so much that people got disillusioned with it this is not why it jumped it. They didn't get disillusioned, they just realized it had limitations a lot quicker than what we've done with previous tech.

Ant McMahon:

So chat gpt hit the scene and everyone went. This is amazing, and then we realized it wasn't accurate. Yes, and to me, what most people have done, and certainly what I've done myself and see others doing as well, is we've moved away from using ChatGPT or Copilot or Google Gemini as a creation tool and we're now using it to curate so that prompts are becoming more specific and maybe more verbose, and we're trying to get it to just rewrite what we've already written to be in a way that's more consistent or in a slightly different tone, and I feel that's where it's jumped the hype curve pretty quickly for us, just the way we use it.

Annie Johnson:

Yeah, yeah, agree, and a lot of that, particularly what I have found when the Honest Human started to lean into more about AI education from a very human level, so not the tech speak. How do we talk about this on a level that people understand and in a language that doesn't sort of overwhelm people? And you know, part of that is around training people to use it. Well, that white box that you sit in front of and you sit there thinking what is that text that I need to put in there to get that prompt, that's come a long way. That's part of that jump is people are now understanding more about the technology and its limitations, but they're also picking up how that is driven by your human interaction. So you know the prompting space. You can very quickly overcomplicate that, but it's worth education and training because you're right, you know it can really 10x your outputs and it becomes a tool that you then understand and the outputs are more accurate and getting you 90% of the way instead of 60% of the way.

Ant McMahon:

Yep, exactly, and certainly I've found for myself. The prompts have changed from write an email that does this, this, this and this to here's an email I've drafted rewrite it for conciseness or rewrite it for clarity and therefore the content hasn't been generated, but it's been reformatted in a way that makes it clearer.

Annie Johnson:

Yes, yes, and you can get caught up in thinking that this, that prompting in these general models, is a science and look, it can sometimes be that if it's a more complex type task. I think the big thing that we need to also remember is prompting is one thing, and trying to get words into that query box in a way that it is clear and it's the right context and it's got the right guardrails it is an art, but once you get there, it does become a lot easier. The other thing to consider, which a lot of people don't realize, is also the type of model you're using, and as Chief of Product in an AI platform, I'm learning huge amounts around models and capability and use cases and for a lot of people just using it on a daily basis, chat GPT is general, so you're going to get some pretty verbose and general statements back, but as you get deeper into it, you start to understand that different models can have very different outcomes because they are purpose-built.

Ant McMahon:

Yeah, and it's a really good point about the type of model you're working with it's. It's something earlier um this year I caught up with both asa cox and then tim warren, who have been involved in ai startups as well, and one of the things that we talked about in those two podcasts with each of them is just that ai is a pretty blankage term for a lot of different technologies, and what we're talking about here and I won't try and pitch the whole humaneer umane r into any of these, but what we're talking with co-pilot and and chat gpt is that generative ai. That's very different to predictive ai or analytical ai, or. Some people will probably uh, write in and tell me I'm wrong on this one, but it's even completely different to the ai in your toaster which controls the timer, because that's artificial intelligence as well.

Annie Johnson:

Completely, completely, and it's a really overwhelming space for any Joe blogs to try and understand. I see a lot of people confusing types of AI as well, and in fact, it was a key question when I spoke at the HIRNZ conference recently, where, you know, asking the audience, do you actually know what AI is or what type of AI I'm talking about? And you know, pretty standard, not many hands went up. So so there is. There is a lot of context to understand in the background as well, which, coming back to your question around fear, the overwhelm of that information as well, you know, creates this fear that you're going to be left behind or I can't understand it, or it just goes over my head.

Annie Johnson:

It's too complex, and so you know, we we Hare are trying to find a really great way of explaining the use of AI. It's not always going to be gen AI. We definitely constrain all types of AI because bringing that together gives you a broader scope. So, yeah, it's a lot for people to take in. Even my learning curve this year has been incredible and if I say just one year, I could put it into dog years in terms of the Synapse connections. Yeah, yeah, it's just an incredible space to learn about.

Ant McMahon:

Yeah, and within that, you talked about the headlines that are driving some of this fear as well, and I think that there's a point that we've reached where the way we consume not so much consume, but where we get our information from has evolved quite rapidly as well. The headlines we see mainly in mainstream media are written to generate clicks and get people reading the article and drive revenue, so they are going to be tailored more towards that fear, and I'm not going to say it's yellow journalism or the old.

Ant McMahon:

if it bleeds, it leads kind of mentality, but it's certainly we'll put this out there, we'll get people commenting and we'll get people debating, but sometimes, actually, that information that the media are portraying isn't the right place to be consuming it, and that's where, like your blogs or Asa with Intela, they have that they're blogging as well. There's companies that are driving AI that are blogging, and maybe that information is more relevant to be consuming than the fear-based headline that's just there to drive revenue.

Annie Johnson:

Exactly, and you know we saw it recently with airlines and turbulence. You know, one example of a bit of a wobble, or big wobble you can see how it just grows legs, doesn't it? And with a fear of flying. That didn't do any good for my travel plans. But you're right, you know the media plays a big role in this and and sometimes it's not responsible reporting.

Annie Johnson:

Uh, I also think that there's a lot of people out there at the moment wanting more structure and guidance from our government. Um, you know, we've been waiting to see what New Zealand will put in place around policy. It's been pretty fluid to date. I think 2025 there's more of a strategy coming out, so there's a lot of people sort of wanting to lean on. What is the guidance? What are the guardrails for us?

Annie Johnson:

And you know, one of those areas is around privacy. We see a lot of horrible media and stories coming out about privacy and security, and it's a very important consideration for organizations. Some would argue that it's largely controllable if you're doing the right thing. However, there's a lot of businesses you know really afraid of, you know, crust around privacy and security. Is it smoke and mirrors? Is it actually doing what I'm asking it to do? Do we have data access in place?

Annie Johnson:

And so you start to look at the guidance around the Privacy Act, and what sort of guardrails do we need to lean on to make sure we're doing the right thing? Do we need to lean on to make sure we're doing the right thing? So it is a very complex way to digest information on something that's so new and moving so fast. People can feel genuinely incredibly overwhelmed and, as humans, our natural tendency when that's happening is that it'll make us feel incredibly uncomfortable. We're creatures of habit and we like to know that things are, you know, routine and safe, and so there's a lot to consume. You're right, it's. It's just making sure that you do go to another source of truth, something that's going to give you more accurate answers, not not saying the media is the wrong source of truth, but I think there's that balance there.

Ant McMahon:

I like you're. Media's the wrong source of truth, but I think there's that's balance there. I, like you're forming another source of truth. Let's find that balance. Read as much as you can about ai and then form their opinions, rather than read a single article from someone and form an opinion of that, the government piece you touched on. I think there's a really good point in there because, arguably, governments haven't or have struggled to keep up with tech regulations anyway. We've brought out all various jurisdictions have brought out their privacy laws, and that talks more to the impact of a privacy breach rather than the guardrails at the start. So do you do you feel in your experience that the regulators are still struggling to catch up, even with just general tech guidelines and tech regulations, rather than and not just specifically to AI?

Annie Johnson:

yeah, I do, I do and, and you know what you've touched on there is is a lot of. What we're dealing with is the lag indicators. You know if, if you're facing a privacy breach, it's too late. Right, I absolutely see a need for us to move faster, but I also appreciate how hard it is to keep up with this. And you know, even looking at the states and how models or your broader organizations, like an open AI or a anthropic, are designing these models and testing these models, there's no proper guard.

Annie Johnson:

That again feeds into this fear of well, if nobody's got control over this thing, once it's out, it's out. So I can see how governments are really struggling to keep up and, unfortunately, we're going to need to wait for some of those test cases. There's going to be that first business who is held to account for a privacy breach because of AI, and in HR, we've learned to deal with that because we're always looking at case law, so someone will be that person. But I do hope 2025 is going to bring more clarity from our government and I believe that's on the cards.

Ant McMahon:

Yeah, yeah, hopefully, hopefully, fingers crossed. And within it, I think and this comes back to the point about alternative sources of information is, I think that there's a big role for the startups like Humane Air and like Contented, which is also another New Zealand startup coming through and leading this conversation. And we've got Microsoft and AWS and Google at the top leading the conversation, but their conversation tends to be more product-driven. If you use this product, if you use our product, this is the outcomes you'll get and these are the skills you need, but I think it's the startups that are coming through that can help really shape the conversation of no, no. Here's where AI will play its role and here's how the guardrails and here's the lessons we've learned by tinkering and by being intensively curious to your point. These are the lessons we've learned and this is what we're going to share, rather than that big Microsoft. Trust us, we've got this nailed kind of mentality.

Annie Johnson:

Yeah, and you know, when you think of a Microsoft it's just a beast right. I think the way startups think in this space genuinely we want to understand that problem statement. You know we're not with Humaneer, we're not building a product on assumptions. We have 60 years collective experience across us three co-founders. We've got a global community that we lean into to ask the questions and test our assumptions. And when you're building from the ground up, you start to solve a lot of those fears and trust factors because you are so close to your customer.

Annie Johnson:

Microsoft doesn't want to really go in right now and understand HR at a deep level. And when you look at Microsoft Copilot, that's going to be an incredible product in two years' time. But when you look at the large organizations, hr is often at the bottom of the barrel in terms of getting some proper tech expertise or your IT teams are overwhelmed so they don't have time to you know map co-pilot properly. And then there's your data concerns and so, yeah, I think startups are a great space to be in and it's super exciting because you can be nimble, so close to your customer that feedback feeds directly into your dev plan.

Ant McMahon:

Yeah, definitely, and you also. There's something in that. Where you talk about HR being at the bottom of the barrel is with the AI. There's also an element of the technology department can only do so much with AI tools, and particularly the Microsoft and the co-pilots is, yes, we can turn them on, yes, we can secure them, but we don't necessarily know the business problems that they'll solve. So to introduce the let's call them, the top-shelf tools co-pilot, paid GPT, paid Gemini to introduce those into the business is a collaborative effort that everyone needs to be in the HR department, the security team, the tech team, the finance team because it might be finance problems that have been solved the customer service, whatever. But with the startups, they're bringing that whole package together and saying, well, here's the problem we solve, this is the problem we solve, and the CIO might be sitting to the side going, cool, we can fit that into our tool stack here. But if the problem you're solving is for the HR department, then that's the people you should be talking to as well.

Annie Johnson:

Completely, and I call it your AI control tower. You know, bringing those bringing that expertise together at the table to understand your holistic position and how each of your functions in your business will use it. It is a big job, right? If you even consider the analysis that goes with understanding and ripping apart workflows and that needs analysis is huge, and not every business comes with amazing teams of BAs, and so, yeah, it is.

Annie Johnson:

I think that understanding the problem statements at the core, but also understanding the true statements around how you use it and why you use it in that function, there's a very careful approach with human error and HR in particular, because we are an industry that deals with some pretty hefty jobs, you know, and so we've got to be incredibly careful with our use of AI. And a lot of HR's fear is that when you go into a chat GPT, it's such a general model, unless you're skilled enough to lock that down in your settings and you prompt well, or you can build GPTs. Nobody's got time for that, you know. When I speak to HR, it's we want to be using AI, annie. We see the opportunity for us, we're excited by it, but tell us what to do. Don't make me go in and build agents. Don't make me learn how to be a prompt engineer. You know it's all of that, and I think that's where the space of startups are really leaning into. It's handing that solution straight to them.

Ant McMahon:

Perfect.

Ant McMahon:

And as you were talking as well.

Ant McMahon:

The idea that I had springing into mind was performance reviews and a tool to do the performance review.

Ant McMahon:

So on the one hand there's ChatGPT, where a manager sits down at the end of the year and says, oh, I've got a little performance review on Annie and just types in all the stuff and says, right, I'm in my performance review, annie. And just types in all the stuff and says, write me my performance review and they get an outcome. And let's not dwell too long on what the outcome is going to be, because it's going to be less than ideal for everyone versus a tool that's tailor-made for performance reviews, where through the year that manager is writing notes about Annie and is maybe being prompted with those notes, and at the end of the year they get a generate performance statement and the statement that comes out is a lot more curated and factual because it's built itself up over I don't know 52 weeks of prompts or 26 weeks or whatever. However long it is, it's just built itself off that. So there's a history behind it that becomes more valuable, doesn't it?

Annie Johnson:

a hundred percent and and a lot of what we face in hr are old, traditional processes. You know, like your performance review process, we are constantly pushing leaders to. You know you need to have your conversations, you need to do your reviews and and we get the pushback going. I don't have time. Your templates are hard, it's clunky.

Annie Johnson:

So there is amazing opportunity to capture data on the go, but we also have to be cautious with that approach, because there's a lot of conversation out there at the moment, particularly when it comes to employee data or employee interaction with these types of tools, where it can be incredibly invasive. So if you you're using a tool that you know there's tools out there at the moment that claims to capture your performance data across emails and Slack and you know it's trying to bring in this ecosystem of all of this data and create a view for employees, that's quite invasive. And if that feels invasive, is that going to change how we interact in iRespond? And so with any process using AI or automation, you have to understand the human interaction first and what is going to build trust human to human, and how AI can underpin that and augment it, but not control it. So there's a little bit of a role to play there in unpacking how it's used.

Ant McMahon:

Correct and it ties back to something you talked about in that intro right at the start, as well as around using AI in an ethical and safe way. Using AI in the way we've just described for performance reviews may be ethical and there may have been a lot of thought gone into it, but it's that safe way, because safe is quite broad, isn't it of? We're now assessing everything and we're evaluating you based on how many emails you send and receive. It may not be safe.

Annie Johnson:

Yes, and we used to have an old saying in HR what gets measured gets done, which was quite an archaic way to view the world.

Annie Johnson:

But yeah, if you're an employee sitting there and I don't know, there's been some technology recently that claimed to measure how many times you smile as a supermarket checkout operator and there was a big article about that, because people are sitting there like forcing their smiles to kind of jimmy the system a bit.

Annie Johnson:

So you, you do, you do have to be a bit careful, and and that invasiveness also comes down to consent, which is a big question coming out for HR at the moment employee data in the next few years and how it's used will change and so therefore, what is the change we manage with that? But also what is the consent required? And I've already had organizations approach me and say, annie, I've got a lot of pushback from employees not wanting their data used with AI because they're fearful. You know that pushback is because they've heard about hallucinations and are worried it's going to be biased, which are very real concerns. But because there's a fear there, they've really pushed back. So that's going to challenge a lot of organisations to be really transparent, build the trust and manage that change in consent well.

Ant McMahon:

Yes, and that consent piece is key. I think there's something within there about what we're doing with the tool and what problems we're solving and avoiding the use of AI when you talk about it. When I say the use of AI, I'm not meaning avoid using AI, but avoid talking about it as AI. It's almost more valuable to build that trust by actually talking about the problem that you're solving or the solution that's coming through, or the outcome, rather than just saying, oh, we're going to use AI to measure how many times you smile. It's more about I don't even know what the problem you're trying to solve with that one, because it's so vague. Let's go back to performance reviews. Instead of saying we're using AI to run your performance reviews, now it's more about hey look, we know that performance reviews take a lot of time, so we've now got tools that help speed up the process throughout the year, so that the final performance review is a lot cleaner and measured. And sure, it's powered by AI, but you don't need to mention that to people.

Annie Johnson:

Absolutely, and that all comes down to how we should be managing change with this beast of technology right, and I think this is an area that we've underestimated the level of change we need to manage, and it's an area I think we need to really double down on our investment.

Annie Johnson:

And I'm of the view, with all of this around consent and how we're using your data, or how we use AI, as all part of ensuring that we we create a really trustworthy, transparent narrative around AI and it's making sure that we don't put the full stop just after setting policy. You know like there's a lot of organisations that will go like got our policy in place, oh, we're safe, everybody knows what they're doing. Off we go and then they don't recognise that full stop happens much further down the line. So once you've got your policy, that's great, that's standards. Now we need to start looking at how we crane our staff, how we educate our staff, and the change management of that alone needs huge consideration, huge consideration for communication, the why. You know the impact, and so businesses have forgotten that. That takes time and it takes investment.

Ant McMahon:

I mean change management is probably one of the biggest things that's evolved alongside technology, and the 20 years I've been working in my industry probably the same year was that the more we've brought tech into it, into the way people do their jobs, the more important change has become, and to how we run that process with them, the more important change has become and to how we run that process with them.

Annie Johnson:

I agree. You know, I think, that the big thing around change, you know, when I've implemented big systems like HubSpot, there was always a really in-depth change program. You know, melissa touched on a really great point in her chat with you that this is technology that sits in the hands of employees. And so with that, I think there's this dynamic that we forget because it sits in the hands of employees. We still need to run change, we still need to communicate. It might not be a big hub spot or a big payroll system. It still requires a level of change management and we've got to support our leaders to understand that and the exec team. It's a big skill set to understand and learn and do so. It's just an added thing to the pile when it comes to AI.

Ant McMahon:

Exactly and within there and I can't remember if I talked to Melissa about this, but certainly a few episodes ago now, when I caught up with Christy Law and talked about change we talked about that element of what's not changing as a result of this is just as important as it might seem easy to us looking back and going oh well, the job's not changing, so we don't need to tell them that. Actually we do, because the absence of any information drives the uncertainty and if we tell them their job's not changing, that's a piece of information that removes uncertainty.

Annie Johnson:

Yes, 100%, and you've hit the nail on the head around that transparency. And there's a big parliamentary inquiry that's just come out in Australia that has looked at the use and adoption of AI and one of their core recommendations is that the change management side of AI requires much more employee consultation, and that's on so many different levels of if it's going to change people's roles and how they interact, there should be a level of consultation with employees so that they've got that opportunity to feed into the process. And that's particularly important when it comes to that more invasive technology. You know where you've got some kind of AI running your engagement survey, looking at emails and Slack and messages. You know that's going to require change management. That's incredibly invasive for employees and if you don't run that change again, you're going to change the interaction and that's not why we want to adopt AI. You know that's not the opportunity that sits in front of us.

Ant McMahon:

Absolutely, and there's some metrics that go with this that may seem only important to management but very important to be sharing as well. Usually with the clients I talk to about AI strategies. Talk to them of, well, what are you trying to be? Are you trying to be a consumer of ai, where all you do is use someone else's tool? Are you trying to be a creator, where you have created a tool and this is human assets and the creator side you've created a tool that drives revenue for your business. Or are you somewhere in the middle where you're going to create some tools that will enable revenue, but they're not the revenue generators on their own?

Ant McMahon:

And whichever one of those you sit, there's going to be some metrics that you're going to track to see have we been successful and should we continue to invest in this. And some of those metrics are things you want to show the employees as well, where, in ways that they will understand, it's not just a oh, it's too complex and they're not going to understand these five KPIs, we won't share them. It's more like, actually, by bringing this in. These are the things we expect to see in the business and we're going to share with you if that's happening or not, so that the employees can understand that. Ok, so they want to see improved customer outcomes or faster customer handling or whatever, and they can see that that's been enabled by that 100 percent.

Annie Johnson:

And you can imagine the knock on effect when you're implementing AI and there's this scaremongering, this narrative that it's going to take your job. It should be about building that human AI symphony and part of being open and transparent around what's being measured and that return on investment absolutely should be how you design that you were showing your people that there are no smoke and mirrors here. It's doing what it intended to do. We are getting a return on investment and that's only going to build more trust for greater innovation. I think if we ignore this part of the hype curve and the change management required, our innovation in the future with AI will suffer because we will have lost the ability to build that trust and if we break it now, we don't do it well, it's just going to become harder.

Ant McMahon:

We'll get more people sitting in that category of being highly sceptical and when you're wanting to adopt this really quickly so you don't get left behind, you need those adopters understanding your why and your purpose Correct, correct and the why and the purpose are huge, and it brings me back to what I was originally going to start the conversation on and we've gone a long way around to get to here and that's purpose-led, which you recently posted on LinkedIn about and you touched on some really good points in there. But I just want to explore a bit more what you mean by purpose-led and how it differs from the traditional human-centric or other methods of design.

Annie Johnson:

Yeah, for me, I'm a non-tech person, right, and so I love talking about this type of technology with everyday people leaders, employees, business owners and it's really interesting to get really curious on the level they understand this TikTok and a lot of it has become this human-centric design in the bunny years, and so I just happened to ask someone the other day. They came to me saying, annie, we're ready to go out and build some proprietary technology. Can you help us find someone to do that? And we want to make sure it's human-centric. And I said to them what does that mean to you? You know, is that just a term that you've picked up on, or or is there something in that that's really important to you? And essentially, uh, it's, it boiled down to, it's just become that buzzword.

Annie Johnson:

And and saying human centric for them, uh, gave their staff a sense of security that it wasn't robots, and so it led me to a bigger conversation with Kim and Karine around our approach to design. We actually don't use the term human-centric. I understand why it's there, but we lean into purpose-led design because it gives you a much broader approach to how you choose your technology, how you design it, how you implement it, why it's there, and so, if you can take a broader approach, it helps you to make the right decisions for your business and your people. Purpose Lead is all about understanding how any piece of technology, any change in your business, any goal is actually designed for a very specific reason, and so, for us, it's about using that so that you can build that transparency, trust. It has a core purpose in your business and it goes back to your evaluation of it.

Ant McMahon:

And that's something that I see as hugely valuable as well, coming from my enterprise architecture background, where I've seen projects. I've seen vanity projects, which I've touched on in the past, but I've also seen projects that haven't really had a clear purpose beyond. Do something, anything but the projects where that there has, within enterprises particularly, but for any business, when someone's taking the time to sit down at start and talk about that purpose, what are we trying to achieve by this and why? What are the problems we're trying to solve? And that's been articulated throughout the project is more likely to be successful. I'm not saying it will be 100% guaranteed, but it's more likely to be because as scope starts to creep or as things start to try and derail the project, you can always bring it back to what's the purpose. Why are we doing this?

Annie Johnson:

Absolutely. You know I'm a huge believer in those big why statements. You know it anchors you back to what you were doing in the first place, and you're right. Scope creep is one of those horrible monsters that are inevitable in tech implementation, as I've found. But it's also about making sure you stay true to your why as an organization.

Annie Johnson:

Because of that hype curve we've spoken about, a lot of organizations have run out. They've gone, we're going to get left behind. So just throw an AI into our business without any real consideration, and so it is hard to measure the effectiveness of that. How do you measure the return on investment when you've just kind of plonked it into some workflow or you've just gone with a general model? It's really important to understand why you're using it, why it's here. If you're going to have a big statement on your reception wall that one of your values is being human and then you make hundreds of applicants interview via an AI chatbot, you start to get cognitive incongruency there where people what are we so so? That's the whole thing around purposely designed for us, is implemented in a way that it's you and it and it supports you in your business to continue your why yeah, yeah, absolutely.

Ant McMahon:

And and you also start to lose the human connection from the process the more technology you put around it as well. Um, yeah, so yes, there are processes where technology will take a hundred percent of the job and will do it faster and more efficient than people, but those processes are very rare within an organisation and there are going to be. Most processes that particularly AI can solve for people are going to be more augmentive. The AI is going to come in with recommendations or with insights or something that will make the person better at the job they're doing. It's not necessarily going to take the job away from them.

Annie Johnson:

I agree, and you've touched on a point there and that goes back to that, that fear that I hear about and that's out there in the media, where a lot of this has been. It could take your job. You know it's going to replace jobs and look it has. In some industries it has disrupted it hugely, right. You only need to look at content design for that. I am 100% all about it.

Annie Johnson:

For renting our roles, there is a real opportunity to look at how we value our work. Where did this 40-hour work week come from? Why is it eight, nine hours a day, you know? But with that also comes it comes back to this trust model as well with AI. So how much efficiency somebody is gaining day by day and how transparent they are with you about that is entirely dependent on your response. So if it's going to augment your role and I'm going to win back an hour, two hours a day, are you going to be an organization that just tips more work in that bucket or are you going to be one of the thought leaders that start to challenge how do we value our work? Are we going to do what we said we would do and get more of our humanness back, rather than allowing AI to dehumanise us in a way.

Ant McMahon:

Absolutely, and let's just touch on the job loss there for a moment, because you talked about AI taking over content creation. I did a presentation on this a few years ago and this is before generative AI really became up. But it was about the job loss that's happened through technology, and one of the stats that I pulled up and I've just brought it up now is that technology has taken 90% of all jobs ever in history up to date, and this was by 2019 I think it was pre-COVID when I did the presentation. So 90%, but when you start looking back, a lot of those jobs not only were they taken by technology, but they were created by technology in the first place and necessitated by technology, and two examples that sprung to mind were telephone operator and the checkout operator at a supermarket.

Ant McMahon:

So, yes, technology took those jobs, but the telephone operator didn't exist before the middle of the 19th century. The checkout operator didn't really exist before the middle of the 20th century either. Yes, we had store clerks. Yes, we had people behind the counter doing work, but it was at a different layer. So technology sort of came in and bought all these jobs with it and then it took them away at the same time, and there's probably an element there where you could see the tasks that technology is taking away are probably tasks that technology put there in the first place.

Annie Johnson:

Yeah, that is such a great point and I've never actually thought about it that way. And you know, one of the industries that I often reflected on is banking. You know, I used to watch my mum run payroll for my dad and it was on a carbon copy, big green bit of paper. Every Thursday she would sit there handwriting it out. You know we would traipse down to the bank. I would go with her because Westpac at the time had a big jar of jelly beans. Why they took those away is a story for another day. But you know there was a bank teller and and that bank teller processed it and and handed her copy back and we left.

Annie Johnson:

And you look at banking now and and that automation, and you know the self-service that comes with banking. Now I walked in the other day needing to do some complex payment and I needed a human, and so I panicked, um, but but you're right, you know technology, the disruption with technology has been here for a long time. It feels intensive. It feels like we're we're ripping the guts out of industry at the moment because of how fast ai is moving.

Ant McMahon:

It has just been a wave of iteration and that that we have never seen in our lifetime, so that is what is making it feel hugely intense and disruptive Absolutely, and the element within there and I'm just trying to bring up the stat and in fact I'll talk about this one because this was one that fascinated me in the presentation and the research that we'll go back and we're talking broad technology here, everything technological, but if you go back to the the start of the 19th century, there were 11,000 handsome cabs in London. Now that's 11,000 horse-drawn carriages plus the horse-drawn buses, which have 12 horses each. They estimated this was 100 years on, obviously, but they estimated that there were 50,000 horses transporting people every day through London. What was then broken down in those stats is that an average horse produces between 15 and 35 pounds of manure and two pints of urine per day.

Annie Johnson:

Wow.

Ant McMahon:

So that was going onto the streets and London had some pretty bad diseases. 150 years ago, horses had an average life expectancy of three years and because of all this, because of all the disease and everything that was going on, it was predicted that that most modern cities, london, new York there's similar stats for New York. It's quite interesting to see them as well but they felt that most of those cities would be overwhelmed and unlivable within 20 years. So by 1920 and it went away.

Ant McMahon:

so not only did technology take jobs you know, taxi drivers weren't there, the stable hands that looked after the horses, everyone that dealt with supporting horses wasn't there as a job but London became.

Ant McMahon:

Now this is a very subjective as to what liv is, but London became a livable city again as a result of technology, and we can fast forward that 100 years. And okay, horse manure was not the same problem it once was, but there's similar problems that have disappeared because technology started to bring better efficiencies. I remember there was a Microsoft TechEd conference where one of the keynote speakers was talking about the use of drones and machine learning and predictive analytics to identify areas where mosquitoes were breeding, and I think it might have been Haiti, one of the Caribbean islands. Mosquitoes obviously bring disease, and what they were using the drones for was to then drop insect traps into those zones that were normally unreachable by humans, thereby controlling the mosquito population and thereby controlling disease as well. So we can talk about all the bad things that technology might do, but we can also focus on the things that we were never able to do before as a result, absolutely and there's always the group of well, it does need consideration.

Annie Johnson:

We are such massive change. You need to try and anticipate the unintended consequences of that Absolutely, and that's one of the big things also around this purposely design is the sustainability aspect of AI, and that should be consideration. If that's important to your business and you have values around that, then make sure that you are building your solution in line with that. And there's some really amazing voices out there now starting to challenge us on that, and I think it's a good conversation to have. It's an important conversation to have because individually, I might be saving time and it's good for me, but the impact of that on a wider scale sometimes we forget, so it's that's going to be a big conversation.

Ant McMahon:

I don't have the answers and I'm really interested to see more about that, because the stats and the numbers are pretty mind-blowing yeah, they are, and I're right individually we don't have the answers, but collectively, when we start to build on the conversations and look for those alternative points of view, as we talked about early on, that's when we can start to see the answers coming through and what they might look like. And it's been part of a societal conversation on what does AI mean for us, what does trust mean and how do we build trust in the tools and how do we put humans at the centre, people at the centre, rather than technology at the centre of all of this? I think that only comes about when we actually start connecting and talking as well.

Annie Johnson:

Yeah, I agree, and this inquiry from Australia has raised some really important points where AI will disrupt industries. Industries, it'll remove types of roles, how we do work, and there is concern that you know we're always saying, for every job that's lost, ai will create a job. We just have to be careful around the pace of that and whether it's balanced. Um, so you know there's a lot of that fear mongering around losing your job. I'm not seeing that at the pace that people are fearful of, but we do need to be cognizant of it.

Annie Johnson:

Right, you've got to think medium to long-term and that's another thing around AI for businesses is don't get short-sighted. Don't be short-sighted. You know there's a lot of quick wins that you can. It will help you, uh. But you've got to make sure that you've got that medium to long-term plan in place, because you can go sink a huge amount of money in ai development today and in six, twelve months time it will be out of date. So you've got to be really careful about that and I think that's that's a lot of pressure on businesses to to stay ahead. And, as we talked about earlier, it's the right knowledge around what's happening. What's coming down the line. It's in beta. What's what's coming out, what's good, what's bad, you know it's.

Ant McMahon:

It's all of that consideration as well yeah, and and and within that as well as do we need to build it ourselves or is there someone out there doing this? And maybe as a counsellor, if we think we need to build it ourselves, has someone already tried? Because there's possibly data out there from other organisations who have tried to solve the same problem in the same way and decided it just wasn't worth it and therefore, if you can find that you might save yourself a bit of time and pain along the way, Absolutely, and we find that, particularly in the HR industry and we are HR tech it can be a really frustrating space to navigate.

Annie Johnson:

We are, you know, system to system there might be the slight differences, but nobody's really taking a step back and going. Why do we keep building systems that we've got to keep vaulting together and are we listening to the right problem statement? You know it's yeah, there's lots of lessons out there and I wish people were more transparent around. It failed for us or it didn't work, or you know, because I agree, you've got to do your homework and to understand those earlier learnings. There'll be nuggets of epicness in that right. Absolutely Might help us.

Ant McMahon:

Absolutely, and that's where experimentation is key. Through this, as well as as call it a proof of concept, call it a proof of value, doesn't matter what you call it, but just experiment with some of the stuff before you go and sink that large amount of money in it. You know that an ai project can be six months or more of of time that's been distracted from from doing anything else, but you might be able to run an experiment in two weeks or even in two months that will tell you this has legs or this doesn't have legs.

Annie Johnson:

Completely, and that is some of the best advice I received when sourcing devs was build a really tiny concept. Think about workflows, the problem statement. He's to give it to a few mates to to play with and break, and that's one of the best things I ever did was take that advice and and play with it first and understand is is this solving the problem I intended it to solve, or you know? So, yeah, you're right, it's. It's definitely worth understanding that and and getting the right expertise around the table to help you with that.

Ant McMahon:

But the needs analysis is really important yeah, definitely, definitely, and I think it's been a great conversation. It's probably a good time to to stop on that note of getting people to reflect on what. What is the need, what are they trying to solve and and making sure they don't spend more time, money, blood, sweat, tears than is necessary.

Annie Johnson:

Yes, completely. It becomes very complex very quickly and it is expensive. Devs are ooh. It's something I've learned.

Ant McMahon:

The benefits might be there, but developers don't come cheap.

Annie Johnson:

They don't, but they are very, very smart people and every day being deep in the dev space is cheap of product Gosh. I'm just. I'm floored at how smart people are and actually a good nod to New Zealand that we've got so many smart people here in New Zealand that I have been amazed by in this journey. We are incredibly lucky and I think we should, you know, really back that innovation space. You know there's a lot of great things happening to help explore that and raise it and celebrate it.

Ant McMahon:

Absolutely, Annie. Thanks for your time and thank you so much for coming on as a guest.

Annie Johnson:

Absolute pleasure, Ian. Thank you so much. No problem.

Ant McMahon:

I look forward to catching up again soon.

Annie Johnson:

Yeah, absolutely. Thanks so much.

Ant McMahon:

See you.