Supporting the Adoption of AI with Leadership and Governance with April Shields
Two teams can buy the same AI tool but can get completely different outcomes. One gets faster and sharper. Whereas the other ends up with more noise, more rework, and a pile of generic words that do not sound like them.
When I spoke with April Shields, Head of Submissions at Built, she made it clear why.
AI adoption in bid teams is not a software problem. It is a leadership and governance problem.
If you want AI to help, you have to set the rules, train the team, protect quality, and be clear on what problem you are actually trying to solve.
Start with the problem not the tool
April was told three years ago to find and implement an AI program. Her team was picked first because submissions looked like an easy place to start. When assessing the type of AI tool they might need, April did not simply begin by looking at all the features.
She began with Built’s real problem: they were trying to grow from $1 billion to $4 billion in revenue, and that meant shifting a team already flat out on high volume lower value bids into fewer bids that were far more complex and far higher impact.
She did not need more output. She needed her people to be more useful where it counted.
April also knew what she did not need. Built already had strong governance. A strong pipeline and an offshore team doing templates and production work.
So when tools came in trying to solve problems she did not have, she said no. Then she looked for the real time-waster in the submissions team. Her answer was content. People were always looking for content and sifting through the database took a very long time.
The tool April chose did one thing well. It safely linked to their libraries so the team could semantically search for relevant content, then aggregate the best bits into a usable first draft.
They trialled it as a team, they invested in it as a team and as a result it allowed them to produce higher value work and more time to understand the solution so they could bid better.
Garbage in, garbage out is still true
April is blunt about quality. If you ask AI to write from nothing, from no source content you do not get insight. You get polished sounding corporate fluff that could belong to anyone. Buzzwords. Absolute garbage.
The reason AI integration works for Built is not the tool on its own. It is the foundation behind it. Decades of strong submission content, well organised libraries, and someone who had been actively managing that content for years.
Even then, the draft is only the starting point. A bid still has to reflect your real risk position, your value, and the way you actually work. If that is missing, it will never feel credible to the client.
Governance is what makes it safe
Governance gives us clarity. It tells you what AI can do, what it cannot do and what the rules of engagement are. At Built, no one can use the tool until they are past probation. That gives the team time to train the juniors, show them what good looks like, and teach them the tone of voice and behaviours that matter.
Without that, junior staff will accept AI output as good because it sounds fine. Senior people will see it instantly.
That gap is where governance and training matter.
AI should pull people together not push them apart
One of the most interesting shifts April described is cultural.
During COVID, everyone proved they could work remotely and still deliver. But April's view is that if all you do is sit behind a computer, AI will eventually take your job.
So she is bringing people back together more. Flying people around more and using the time saved to spend time with each other, to understand the client problem and to bring strategic anchors into the bid.
AI does the dishes and humans do the thinking.
The long term question we cannot ignore
April raised one issue that the industry has not solved yet.
If AI can do what juniors used to do, how do we train the next generation? What are the skills they will need for the future?
You cannot build future bid leaders if no one gets the chance to practise the craft from the ground up. That is a leadership problem as much as it is a technology problem.
We have to remember that AI is not the strategy. It is a tool.
And the teams that win will be the ones who govern it well, use it to create time and reinvest that time into the human work that makes bids worth reading.
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Deb: [00:00:00] April Shields, welcome to Chasing the Win. You are the head of submissions for Built, uh, what a role. You've been in it a long time now. Been a
April: lot. 13 years now. I've seen a lot.
Deb: You have, I really wanna talk about the digital future of, of [00:01:00] bids, because I know that you've done some amazing stuff over the last few years.
Everyone's being told to digitise bidding. Yeah. Like faster, smarter, more ai. But it seems like in the real world, in the world we live in, um, the outcomes are, are wildly uneven. So I really wanna unpack why that is with you.
April: We've hit the nail on the head. That's what I was told three years ago. Go and get AI and it, my team was selected first because it seems like a really easy target to use, uh, ai.
Uh, and there are a lot of variances, I guess, in how the tools are adopted and how effective they are. But I think it's not always the tool for a start. And that's what we always think, what's wrong with the tool, uh, but to put it in, I guess, bid language, um, what's more important is the benefit, not the features.
Deb: Ah,
April: so quite often tools are just rolled out and you're just like, here it does this, this, this, this, and this. And, and that's kind of meaningless. So, [00:02:00] um, what we did instead was we tried to surface what the problem we were trying to solve was. And what that looked like for us was we were told the mission, we, our mission was to be Australia's number one contractor.
Deb: Okay.
April: One of the metrics for that was to grow the business from 1 billion to 4 billion revenue.
Deb: Yeah.
April: And how do I do that with the team that I have that are already doing a high volume of lower value bids?
Deb: Yeah.
April: So the problem that I needed to solve was how do I ensure my team is equipped to do a less volume of bids, but more complex high impact work.
The value of those bids is higher.
Deb: Yeah.
April: And whether or not we win or lose those bids means more.
Deb: Right.
April: So that was the problem we were trying to solve.
Deb: And this is three years ago when AI was just this, this concept flying around. It wasn't something anyone really
April: understood. It was just
Deb: a word. Right.
Understood. It was just, it was just an acronym.
April: Yeah.
Deb: Wasn't it?
April: So, yeah. So we just [00:03:00] decided that we didn't need to do more bids, but every AI company was, this is how you're gonna get more done with less. Whereas that wasn't my metric for success. Okay. I needed to make my people more useful with what we already had.
Deb: When organisations invest in, in new tools or new systems, how do teams then become more effective?
April: Well, again, instead more
Deb: chaotic.
April: Yeah, exactly. So again, we're trying to solve a problem that we had, that our team had. Right. And we were looking at tools that, you know, they shortcutted a governance process or they put things into templates for us.
But we already had strong governance. We already had a strong pipeline. Yeah. We already had an offshore team that was doing all the templates and stuff mm-hmm. For us. So every tool that came to us was like. They were trying to solve for something that I didn't actually need. And then I looked at my team and said, where do we actually waste time?
And it's always looking for content.
Deb: Looking for content.
April: Okay. Always looking for content. So the AI tool that we [00:04:00] ended up choosing, which we chose as a team, which we trialled as a team, which we invested in as a team. Mm-hmm. Um, simply did that for us. It safely linked to our libraries so that we could semantically search for content mm-hmm.
Appropriate to the bid that we were on. And it would aggregate those responses, right. Instead of just giving you 10 different responses, it would go, here's the best bits from 10 different ones, and here's an aggregated response.
Deb: Mm-hmm. We did it as a team. We did it as a team. Talk to me about that. How meaningful is that?
April: Well, again, 'cause we don't, we don't wanna just hand someone a tool and say, here's all the features, go and use it. My team of 15 people, including eight offshore, they're already very effective at what they did. They're already a high performing team. And actually the very first question I asked them said, the cost of this is equivalent to the cost of a whole new person.
Deb: Okay.
April: And we have to decide as a team if this is something we actually want and we're gonna [00:05:00] trial it and we're gonna test it. And you are gonna tell me. Would another person be able to help you do this more effectively? Or does this tool help you do your job more effectively?
Deb: Mm-hmm.
April: And we all trialled it for over a month.
Um, and universally, every single person in my team said, I actually don't need a new person. What this gives me is more autonomy over my role. What this gives me is more time to spend on higher value activities, which means I can spend more time with the team, I can spend more time with SMEs. I can understand our solution better so that I can bid better.
Deb: It enhanced the, the skills and expertise and professionalism of the team you already had. Yeah. And it didn't diminish your team did it. It didn't. No one lost a job over it.
April: No, absolutely not. No, absolutely not. And in fact, it's over the three years, it's only highlighted more that the level of competency of my team needed to execute.
What we are doing now is tenfold what [00:06:00] we're doing three years ago. Like we are biding on Brisbane Stadium at the moment, as you know, everyone knows, which is massive for us. Where when I first started at built, the biggest job we had was a hundred million dollar job.
Deb: That's extraordinary. You've gone from hundreds of millions to billions in the space of three years.
And obviously there's, there's a lot surrounding that with the business and how extraordinary, um, that growth has been. The, the second thing I just wanna unpack in that is the quality of content. Like you had quality content to begin with, didn't you? That's it,
April: isn't it? Isn't that the important thing?
Garbage in, garbage out. Like if you just asked AI without any source whatsoever to generate a response to a bid question.
Deb: Yeah.
April: You've seen it. Yeah, I have. It's total garbage.
Deb: I've seen it. Yeah. Yeah.
April: It just comes up with buzzwords, right? Yeah. It just sounds like corporate fluff, but it doesn't have any real meaning behind it.
Yeah. But because we're able to link. Decades of submission libraries because I've been managing submission libraries for decades.
Deb: Mm-hmm.
April: The content that it [00:07:00] surfaces is of such higher quality that's relevant to our business. Mm-hmm. And that's the most important thing, is you can go and source a question or an answer from anywhere in the world that you think's relevant, but what your business needs to respond to is always gonna be different to someone else's.
Hmm. How my business respond is always gonna be different. My risk position is different. Mm-hmm. My value offering is different. My culture and behaviours are different and they present differently in bids. So just having a, I guess, coherent response that people want to hear isn't enough to win bits.
Deb: No.
How over time are you gonna maintain that quality? I guess there's a, there's a, a thought in my mind that people will, will become just dependent on the quality that's sitting within the system and they won't necessarily come back out of it in elevated further. How are you gonna, how are you gonna make sure that that doesn't happen?
That, that you elevate
April: Yeah. That you don't water that content
Deb: down, that you don't in effect water the quality of the content down over time. Yeah.
April: It's something, yeah. It's something that I've thought about a lot and I [00:08:00] think it goes back to some of the questions that we were gonna answer before. Well,
Deb: I will, I promise I'll come back to them.
April: It get judgement , governance, and clarity. Right. And, and, and the leadership behaviours around all of those things. Mm. So we are not relying on AI to give us just the answer. 'cause that's all it does. It gives us the answer we need to spend our time improving that for that specific output. So because we've got more time to do that, because our first draughts are of better quality, we are giving better, um, starting points for our SMEs.
I actually think the overall quality of our bids is improving. Yes. Um, they are more tailored, they are more client centric because of that extra time that we have to add in that the, the value doesn't actually diminish at all. So
Deb: you've got time to exercise your judgement .
April: Yes.
Deb: Wow.
April: And you have to empower people to exercise that.
Right.
Deb: You do.
April: So, you know, you have to make sure that you give the space for [00:09:00] that thinking. And it's very clear on those leadership behaviours. When I say to my team, we've got this AI tool, the expectation isn't that you are gonna just produce more.
Deb: No.
April: The expectation and the metrics of success have been very clear with my team from the start.
The expectation is you are able to get to first draughts very, very quickly. Mm-hmm. Um, but you need to spend the rest of the time that you would've saved improving the quality and having those gateways and judgement processes,
Deb: exercising
April: your judgement , asking interac
Deb: questions. Human Yeah. Human interaction.
Yes.
April: And so this is the thing that the, the most extraordinary thing that I've, like, I've just been thinking about this week, is our people during COVID d. All went offline, we all went, worked remotely, and we did it seamlessly. And we all decided it was entirely possible to work in our own little offices and we could do all of our jobs like that.
And that, that's still the case. That's still very much true.
Deb: Mm-hmm.
April: But I realise [00:10:00] now with ai, if that's all you are doing is sitting behind a computer, then AI will take your job.
Deb: Yes.
April: Because you are just doing computer work at that point.
Deb: Yes.
April: And then where, where does our value come in? Human, the human interaction.
So I'm bringing people more into the office. I'm flying people around more than I used to because the time that we have freed up now is time to spend with each other to understand what the benefit is to the client, what the problem is we're trying to solve, and really bring those strategic anchors into the, into the bid.
Whereas before we didn't have time. We just kind of just, it was a puppy meal. Right.
Deb: Yeah. It's such a different mindset though. And you're actually changing the narrative. You're actually flipping the narrative on, on, on a, on AI and on its application to a, what does it do for us to enhance human connectivity, to enhance human interaction, to, to actually be able to bounce those ideas that enhance what we're creating.
April: An example. Yes, please. [00:11:00] Um, we used to write meeting notes all the time and quite often, um, as women in a male dominated workplace, I was often tasked with that job.
Deb: Were you and getting some water?
April: Get us some, get us some water. And can you take the notes? Yes. And I would spend more time taking the notes than interacting or contributing to those meetings.
Deb: Yes.
April: And now I insist on AI notes because they take better notes than I did anyway, and I can ask it questions that I forgot to ask at the time.
Deb: Yes.
April: Which frees me up to contribute meaningfully in a meeting now. And that's just a small example that gets amplified across like multiple opportunities where AI can do what you worried about before so that you can worry about the, what you're doing as a human.
Deb: But that's even changing a, a cultural dynamic. I know that your company has always respected your capability as, as a professional, but I'd never imagined that AI could actually be a tool for feminism. But it is, and you know what an advocate I am for, for tendering as an art [00:12:00] form, but also for women in the profession in so
April: many ways.
Like just expands beyond taking meeting notes, like the thing that we get told so often in submissions. Can you make it look pretty?
Deb: Yep. Yep.
April: And to an extent that's, that's still, we still need to do that. Right. And AI isn't quite at the point where it's doing a very good job of that. Mm. It will though a hundred percent
Deb: and we still need to advocate against that language.
But it can free you up to be more creative.
April: Yes.
Deb: It can free you up to take the time to actually look at the way in which you have actually professionally presented documents in the past and, and, and really enhanced that, really elevate
April: that you sat up on a computer where no one's ever spoken to you and you've just done the hard work that no one notices.
Deb: Yes.
April: And now all of a sudden you can just set that aside while you go and talk to someone.
Deb: Yeah.
April: It'll reinvest that time in talking to people.
Deb: Amazing. So what would you say before introducing any form of digital tool or AI in a, in a bid environment, what do you think needs to be already in place? What elements do you have to in order first?
Governance. Governance. Okay. Governance. [00:13:00] Define that for me. Talk me through that.
April: It governance can sound, it can sound clunky, it can count sound slow, and it can sound disempowering to some people. It takes, um, authority away from you because there's a structure in place that means you don't get to make decisions.
Mm. But if you have governance in place around ai, what it can do, what it can't do, what are the rules of engagement? So for example, with our tool, I won't let anyone use it until they're past their probation period. That gives us enough time to train them. That gives enough time for them to understand what good looks like to us and to, and our behaviours and our culture around how we use it.
Yeah. It's only after that that they're allowed to use it. Um, so those things need to be in place, which makes, makes people very comfortable with where they sit.
Deb: Okay.
April: If you don't have the governance in place and you just go here, have AI and they don't know where it starts, they don't know where it finishes you, you end up with a lot more of that AI slot we talk about.
Deb: Okay.
April: So maybe an example was early days when [00:14:00] we're testing it, we had a, as someone that was more junior in the role, didn't understand, built our tone of voice and the language propositions that we put forward. And they did some introductions on cbs.
Deb: Okay.
April: AI. Looks perfect to that person. Sounds like good pros sound like
Deb: reasonably written.
Yes. You're
April: like, yeah, okay. That sounds like something someone would write. But
Deb: yeah,
April: to the more senior people in the business we go, we wouldn't write like that.
Deb: Yes.
April: That's doesn't reflect us. That's how, that's not how I would talk about Deb.
Deb: Yeah.
April: And that doesn't present any value to the client. Yes. All it is is describing someone Deb's got a black jacket on.
It's not useful for anyone. Yes. But it's right though, isn't it? So you can't, you can't say, no, I'm sorry you're wrong. But we would talk about someone that's linked to the project attributes, for example.
Deb: Yes.
April: And they didn't use prompts in that way. So once we realised a few of those things that were surfacing early in that testing period, we put some sort of gateways in place.
I
Deb: love that. Because they still [00:15:00] have to learn the skills. They still have to know what it is to be a tenderer. They still have to know what it is to create great content. And then the tone of voice and the framing and the client centricity that goes into it.
April: Why are you doing this?
Deb: Yes.
April: And that's the question that just so few people ask the next why.
Yes. They ask one why. Mm-hmm. But they never get to the next one or the next one. There's an an endless series of But why, but why, but why, but why
Deb: So what? So what? So
April: what? So what? So what? So what?
Deb: Yeah,
April: exactly. And then it's, it's the more senior people in the business that are better at recognising that.
Okay. But that's also where the problem lies.
Deb: Well, I was gonna, I was just about to go there. So let's explore that. How have you had to position the use of these digital tools and AI and systems with them so that they understand it is not just an efficient, it's not just a more efficient puppy mill.
April: Exactly. So you have to like, you have to make it clear what it's there to do and what it's not to do, what the metrics of success are, and again, what is the problem we're [00:16:00] solving, the, the benefit to them and the benefit to us. What I'm still trying to work out is how, you know, I'm obviously very into elevating people and bringing people up through the chain.
How do you then bring on juniors that have no idea what they're doing, and how do you bring new people in the industry when at the moment AI is doing what they could do better than a junior? This is something, this is, this is something that I'm with. Well think that's what we're all grappl long term thing, right?
Grappl,
Deb: yeah. I think many organisations are grappling with that, you know, graduate level positions are, are, are theoretically being replaced by ai, but you can't replace learning. You, you can't, you still have to train people to do the jobs that we now sit here and do.
April: And is, is the answer that these people need to be better at AI than we are not better at tendering.
They bring a skill set that you don't have. Like my, my senior team has a vast skillset over many, many [00:17:00] years of experience. Graduates come in and they don't know those things, but you kind of can't be bothered to teach them because I could just ask AI to do that.
Deb: But then how do they learn to be that in the future?
How do they learn to be the professionals that you are Now
April: that I haven't solved that question yet.
Deb: No, I'm
April: still working on
Deb: that. I'm asking. I'm asking it theoretically.
April: Theoretically. So that's something that, that does worry me because. There is, there is a future where there won't be new people coming into this industry if we don't nurture it.
Deb: I'm not sure that's a question we're gonna be able to answer in, in our podcast, but I'm gonna keep contemplating it. And I, and I think it's a conversation worth having with our industry.
April: I think. So I think it's just something just to put out there as something to consider for the long-term future of our profession.
Deb: Yeah, absolutely. In high pressure bid situations. 'cause we know we are always under pressure. I must say I'm tired. Um, right now, um, what role does Clarity play in how teams make decisions and [00:18:00] prioritise their work now, having brought in a tool to allow that space and time for judgement ? Yeah. Allow that space and time for strategy, human engagement.
SME engagement.
April: Well, we all know that when people don't have clarity, like simple things like who do I ask for X?
Deb: Mm-hmm.
April: Who do I get to review x? Who has decisional authority over this thing that I'm doing?
Deb: Mm.
April: I see people waste hours just trying to figure that out. Mm. And having those things set early, that's, that's what clarity means to me.
So that you don't spin your wheels all the time trying to figure out where my effort goes.
Deb: Yes.
April: So if you have clarity through good leadership mechanics, uh, then you're able to get to the problem solving quicker. You're able to look at the strategy, execute the strategy, look at, look at how you improve the actual submission for your client rather than [00:19:00] going, but what decision gets made here.
Deb: Yeah.
April: And by who and who do I talk to, particularly with SMEs as well. Like if you, if you are given time to do a first draught on behalf of an SME, you're more inclined to then have a better value conversation with them about what the next level looks like.
Deb: I love that because one of the things that we always come up against is, you know, I have a day job.
April: Yes.
Deb: Yeah. I mean, that's a constant refrain from subject matter experts and operational people is, you know, I have a day job. So if, if you working with the tool can bring a front end draught to them that is more considered, more strategic, has more judgement , then you're going to use their time far more effectively.
Yeah.
April: And that's what we've seen, right? Like even the most basic things. I reckon maybe three years ago, most people came to me with, Hey apes, when was the last time we wrote [00:20:00] about, uh, cost management? Drive me up the wall yesterday, literally every day. Which part? How long is a piece of string? Yeah. Right.
Whereas instead, I never get those questions anymore.
Deb: Okay.
April: Because of it's already been drafted for them.
Deb: Yeah.
April: And they're the most basic things in my mind, but then when they see it in front of them, they go, okay, cool. So cost management in this case needs to look different.
Deb: Yes.
April: And for this client where they have a cashflow in, in like issue potentially where you have to front end all of the work before a certain financial year.
Deb: Yep.
April: You can talk to that. You can talk instead of just a process. Yes. Not like cashflow looks like this.
Deb: A, B, C, D,
April: congratulations. You know how cash flow works.
Deb: Yes.
April: Whereas this person goes, all of a sudden I'm freed up to tell them exactly what this means
Deb: for them and I'm freed up to get in front of the cost planner.
April: Yeah.
Deb: And to say, here's the draught. We understand from the client that they want a front end, A, B, and C. Yeah. Can you tell me [00:21:00] how we can make this contextual and bespoke within the process for that client? A
April: hundred percent. That's it.
Deb: So you don't need to have the expertise, you don't need to know the answer.
No. But you at least have the context, have the time, have the space to get a far more bespoke answer on your second draught.
April: And we've spoken about this before. When you ask someone to create something from scratch, they just freak out.
Deb: They freak out. They freak out,
April: they lose, lose a plot. Possibly. I couldn't possibly, possibly page, I can't
Deb: blank
April: blank page.
And I, I go, well we, this is your topic of expertise. Surely all we wanna do is tell everyone about this thing that you know so much about. About, but they always, always freak out. Whereas if you tell them what you think,
Deb: yeah.
April: Nine times outta 10 they go,
Deb: ah, yeah,
April: that's rubbish.
Deb: Cross it out.
April: Yeah. Don't they?
Deb: Yeah.
April: And then all of a sudden you get to a better outcome. Yeah. That's better for your client and has improved outcomes in your bids. Well,
Deb: so we've been doing that physically for years. I mean the, the, the joy of the square brackets, um, you know, my [00:22:00] team and I and you no doubt. It's like you put something in square brackets, you know, is actually probably not even wrong.
Correct. And you, you manipulate the person into looking at it and going, you are so wrong. It's like, I want to be wrong here 'cause I need you to bring your expertise to the table. You're actually now able to go with a really solid square, bracketed, almost accurate response and say, I need you now to make this bespoke.
Yeah.
April: And what we see now in the comments after the first draughts is. Too broad contextualise it.
Deb: Fabulous.
April: Whereas before we used to say things like, is this true?
Deb: Okay. Okay. Do
April: you know? So you know it's fact. So we know. So now it's true.
Deb: Yes.
April: But it is, it has not been narrowed enough for that purpose.
Deb: I love that.
I actually love that. I'm feeling, I'm feeling really buoyant, but about this. So what have you seen happen to team behaviour when leadership is consistent and predictable as opposed to when it isn't?
April: One of the scariest things that happens in [00:23:00] bids, and I'm sure you agree with this, is when things go quiet, when things go quiet, nothing good is happening.
No. That means that again, decisions are unclear. So someone's off doing something that they're not sure is right and they're afraid to speak up. Well
Deb: they've gone off on a tangent, gone
April: off on a
Deb: tangent and they're not sure if it's the right one.
April: Yeah. And then risks aren't getting surfaced. Yep. And decisions aren't being made.
Aren't being made.
Deb: Yep.
April: And everyone just goes off and does their own thing. And it's not until the last moment that you realise that you've been on the wrong page. Yeah. For an extended period of time. And then you have to come back and rework everything when leadership is very clear with what the expectations are, what good looks like, where you are allowed to use your own judgement
Yes. With a risk scenario. Really
Deb: empowering. Yeah.
April: It empowers them to make good decisions. Yeah. And then where they're not sure, they're very free to raise it
Deb: empowers them to ask the question. So are you finding, in the last three years, would you say that the rework on bids has diminished over time?
April: Very [00:24:00] much so.
Because the first pass is better because the quality of the conversations that we're having is better. And like it sounds like this is magic. Right? It didn't happen overnight. It's
Deb: not. No, no,
April: it's not at all like, it's not at all magic. Not a
Deb: pany at all.
April: And there's a whole massive learning curve with prompting and all of this.
Yeah. It's not like the tool arrived and all of a sudden we will. Brilliant.
Deb: But you also came with a strong culture, a strong team, a strong quality, a strong work ethic. So we wanna say that you came with all the best foundations to be able to apply this tool.
April: That's a really important point to make as well, is that we knew what was good about what we did, not just what we needed to solve.
Deb: Yes. Yes.
April: So instead of just going, here's a problem we need to solve, let's focus on that, we also made sure we articulated what was already working. Yes. What we didn't need to solve for. Don't bother doing those things 'cause it's already fantastic.
Deb: We've already got that in
April: hand. And if you can, if you can solve this problem so that you can elevate those elements
Deb: Yes.
April: Then that improves everything. It's an employee value proposition as well. [00:25:00] Yes. Like I've, I've got a very high performing team that I'm very proud of and quite often I would think to myself, how lucky is it that I have a team like this? And then I'd sat myself on the wrist and goes, it's nothing to do with luck.
It's actually, it's
Deb: absolutely
April: right. It's actually building it through leadership capability, right?
Deb: Yes.
April: And then now that I've got such a high performing, amazing functional team, how do I maintain that? And that comes back to that question of what do you want in your role? Yes. Making sure that, making sure that the people in my team know that I value their contribution and that if they want another person and not ai, because it's, that's gonna elevate them.
They were free to give me that feedback.
Deb: But they didn't.
April: But they didn't.
Deb: Yeah.
April: Because they realised that their jobs meant more because they were taking the lower value
Deb: tasks. They're playing, they're playing more meaningful roles in actually winning bids.
April: Yeah. I don't get the complaints like I used to of such and such.
Can't see what I do. They just think I changed the font colour. [00:26:00]
Deb: Yes.
April: Or they don't know that I can help.
Deb: They think I'm a glorified proofreader.
April: Yeah. Or they treat me like an administrator and I'm just really good at booking meetings.
Deb: Yeah. Yeah.
April: But now we are actually, and I don't, I don't know if the rest of the business realises how they see us, how that has changed.
'cause it has been incremental. It's just been moving little chess pieces slowly. It wasn't just an overnight thing.
Deb: No.
April: It wasn't this transformation that everyone just wakes up the next day and goes all of a sudden.
Deb: And AI only played a very small part in that.
April: Yeah, exactly.
Deb: That is leadership. That is culture change.
That is, that is advocating for tendering and bid management and proposal management as an art form.
April: Yeah.
Deb: And that advocacy has to be there. If organisations don't have that foundation to begin with and they just throw AI in there as the panacea at at all ills, I don't think they're gonna see the results that they want.
They have to have it
