Why Isn't AI Improving My Team's Productivity?

Alex: Welcome to the Scaling with AI podcast. I'm Alex Bacon and I'm on a journey to cut through the vendor hype and learn the real life use cases of how AI can help grow your business. Every episode I chat with scaling businesses just like yours who are leveraging AI to do more, go faster and grow bigger.

Let's dive in. This week we're looking at the importance of getting your processes and operations right before you can scale up with AI. I'm joined by Emily Hatton, who spent years working with marketing agencies on their operations, and now she's looking at how those processes and operations are fundamental.

For driving AI adoption and scaling your business in the new world. Okay, thanks Emily. Do you wanna start off by just telling us a little bit about yourself?

Emily: Of course. So I'm Emily Hatton. I'm a business operations consultant. That's kind of my main job, but what I've been really focused on over the past year is supporting agencies with their adoption of AI.

So I started a company called AI and Agencies, where I do a lot of workshops and webinars and resources around. Agencies to talk about how they're using AI and what's working well and try and get them to do more in terms of improving their use of it.

Alex: Brilliant, thank you. And obviously you've got a lot of background in operations, so what are you seeing as the most common operational challenges for marketing agencies?

Emily: So last year, 2025 in particular, I think was overall a tough year for agencies and a lot of margins were getting quite. Squeezed. I think that that was due to kind of clients being quite slow, so not as many leads as agencies would like. Leads not closing very quickly either. So it was much longer close rate for agencies last year and that led to a massive squeeze in terms of people's margins.

'cause obviously they were staff to generally handle more clients. But what it did allow, particularly some of the clients that I was working with do, was to look at. Where they could be more efficient in their processes. And that's really what I'm focused on, is helping them to get the efficiencies with the things that are within their control, in particularly around the operations and how they run their team.

And that's what I was trying to focus with clients on. And I think that other agencies were also focusing on trying to improve their margins with the resources they had.

Alex: And has the expectation from their clients changed? What does that conversation look like where they're sort of expecting people to use AI or maybe even they're using AI themselves to do some of the work that the agency previously did?

Emily: I think in terms of agency founders, things have changed over the last couple of years in that agency founders feel like they should be getting efficiencies from. Having AI in their agency. So from chucking a few tools over to the team and saying, use this is great. And I think that they feel like the team should be getting more efficient and should be able to, for example, handle more clients or create more output or be faster at the output that they're doing.

But this method of just chucking in tools that have been recommended by other agencies is not working. So obviously what happens is. The founder thinks it's a cool idea or something that someone else has seen that works well, but they haven't actually looked at the process they're trying to address by giving the team this tool and therefore nothing really changes.

The team half views it. Some of them might adopt some parts of it, some of them won't, and therefore the founder and the whole agency won't see any efficiencies. What they need to be doing is obviously not just chucking in new tools. They need to be looking at what processes do they need to be making more efficient.

So looking process first, rather than thinking, Hey, here's the core new tool. Like let's use that. You can keep that in in your pocket to review in terms of your tech stack at a later date, but you really need to be looking processed. First, so that you actually look at what goals you're trying to achieve.

So are you trying to reduce time per output? Are you trying to get more clients into each team member Through efficiencies. Okay. So what processes you gonna change that will allow you to do that?

Alex: Perfect. And what's the client sort of facing conversation around that look like?

Emily: So from agencies that I work with and what I see in terms of the wider conversation.

The problem at the moment is that agencies aren't very open about the way they're using AI and probably don't even know the way that the whole team is using it themselves. So therefore, if a client says, Hey, where are you using AI in your processes? An agency can't answer that properly, which then creates a bit of friction with the client and makes it more difficult to land them.

The agencies who are really confident and on the front foot with how they adopt AI and where they're using it are the ones that will win. Clients. Clients, they say, we've made the decision to use it here, and here because it's really efficient. We don't use it here because we wanna, for example, like retain the tone of voice.

Therefore, you know, we use copywriters for all the copy. So if the agency has made decisions on where to adopt AI and can confidently say to the client about that. Then clients don't have a problem with it. The clients want agencies to use AI. They don't want agencies to ignore the fact that AI exists.

They just wanna understand where it's being used and that the agency has done the right checks on the tools they're using, or thorough checks of the processes they're using are on that. It's the right tool and the right process to adopt it for them.

Alex: Yeah, I can, I can see that that transparency around how you're using AI is, is really important 'cause people know that you're gonna be using it.

So I think it's about being confident. Demonstrate where it's being used, how it's being applied, and how that's helping enhancing output as well as just efficiencies. You spoke quite a lot around there, around processes, so just talk us through a little bit more kind of why that's so important to review and make sure the redesign of your processes are correct.

Emily: I think what's happening at the moment, and has happened in the past as well, not only with kind of more influx of AI is that. And founders tend to be quite reactive, so they tend to, rather than have a systematic approach to when things need fixing and how to always optimise their processes, they tend to do it either based on a client complaint and then they tend to like overhaul everything because a clients complained about one small thing because they don't have the confidence in there.

Processes to say, okay, that happened. Let's review and tweak that. They tend to have a very reactive approach, like, okay, so we need to change all of onboarding because the client wasn't happy about it. You need to have competence in your processes the same as with new AI tools coming in. So you need to not be reactive and say, Hey, this new tool's come in, let's use it.

You need to understand your process as well, and if you understand your process as well and you see a core new tool and say. This would be really useful for us because we currently use something else and it doesn't have the same capability as this tool. That's a good decision. But at the moment, people are saying, okay, that tool's great, but actually it might not be anything they need to use it for.

It might be a very small part of what they need to use it for. So if you have a really good understanding of your processes and address. Methodically, which processes need to be updated in order to optimise your service delivery, then you will consistently improve your margins, but also be really competitive versus other agencies.

So if you're always looking at the best way to optimise your delivery according to the tools that we have available now and how we can do it and just do it in a systematic way. Rather than reactive, like we had a complaint here, there's this tool here. You'll actually always be ahead of other agencies because you're doing it in a much more methodical way.

Alex: And obviously, as you said, you work with agencies, but I imagine the underlying issues are common for all businesses. What's your advice for organisations to help shift the conversation from tooling into processes?

Emily: Yes, of course it's across all businesses, but our main audience is agencies. So to get it from tooling to processes, it's great to have someone inside the organisation who.

Is responsible and owns this. So you should have someone in your agency, regardless of size, who's responsible for operations in some way. You might not need a full-time operations person, but you do need someone who's looking at how your agency runs and is thinking about how to make improvements on that.

All the time across all areas of your business. And then if you have an operations person who is good at what they do, they will lean more into the processes because they will work with the resident stakeholders in the business and they will get an understanding of where things are going well, where things aren't going well, what changes need to be made, and be able to look at that.

With a kind of more zoomed out lens rather than if you're a founder and you're not really involved in the day to day of what people are doing. Of course a new tool.

How it will help them or not, or probably hinder them because it probably just gives them a distraction from what they're actually doing. Whereas if you have someone who's operational minded and gets the fact that they need to look at processes first, which all operations people do think like that, then that's how you overcome that.

So you just need someone who is responsible for that area inside your business.

Alex: Perfect. And you have a sprint a five day sprint process that you run with agencies. Tell us about that and how that's structured and what that incorporates.

Emily: Yeah, so obviously agencies like to see impact quickly, so do I. So that's why I kind of designed it as a sprint.

So it's five days to learn how to put an AI operating system within your business. So really focused on. For ops. So it could be you as the founder of a small agency. It could be a ops person or an S lead, or it could be a delivery lead within your agency. So whoever is looking at this area and looking at how to make efficiencies and improve margins here is a great fit for them.

So the sprint covers the first date is an audit, so it's looking at. Weighing up your current business processes and where if you made changes and made improvements using AI would be your biggest gains. So which processes should you make changes to first in order to get the biggest gains from implementing AI more effectively.

Then days two, three, and four are, once you've identified those best cases, we then look at. Redesigning the workflows to incorporate AI more effectively within those processes. Across those three days, you have three updated workflows, and then the last day is looking at how to review when you make those improvements and how you can keep doing that.

So how we can keep using the operating system moving forward to compound on the gains that you get from AI. So the biggest problem that people get through making changes with.

I want to save X amount of time, or this should get me this amount extra output. They don't do that in the first place and therefore they dunno whether the change they've made has made any difference to their business and to their margins or not. And what's really important to me in a business. Mindset through the sprint is on the first in the audit.

We look at these reviewing your potential use cases and identifying the top ones, and it's done based on your financials. So it's done based on what will give you the biggest time saving for that individual, for that team, and therefore they can spend that time. Or doing something that is more valuable than the current admin process they're doing.

And because you set that goal, you know what you should be saving or you know the change you should be making by the end of the week when you are reviewing it and you're implementing it long term, you can see whether it's successful or not, and then how you can build on it further. So for me the setting out.

Expectations for making the change and then reviewing whether it's successful or not is what this sprint really helps with and what hardly anyone does. Even experience. Lot people don't do this often enough,

Alex: And have you got a framework for that audit that people can sort of understand? What are the areas within the business that they should be looking at?

What should they be reviewing to get that benchmark?

Emily: So what is great about what I've designed is that, I mean, it's based on what you put in, so obviously it's you having a good understanding of where. You think the potential gains are? The baseline is usually, if something requires a lot of admin and a lot of crossover between multiple different tools.

There's usually an area for efficiency there. So if something is manually putting data, obviously between certain tools, there's a huge potential for using AI or using automation to improve that process. So. I give tips in the sprint about like, here are some areas you should look at. So it could be things like client onboarding.

There's often a lot of manual things there. Client comms, there's often a lot of manual intervention there with people using note takers, but still manually copying that actions into a project management platform. And imagine that across a team of. 30 to 50 people if everyone's doing that manually. If you had that automated and used AI to pull out the keynotes, get themes across the business, you would not only save a lot of time for client and account managers, for example, who could be using the time much better in liking the client in other ways rather than manual task.

But also you could pull out some great things with AI to provide the leadership team with. Level of insights than they have at the moment. Like what's going on across the whole business with all the clients, like they could see how many clients are at risk at any time because all the data is available in everything that the team is doing.

But often people aren't looking at that or aren't automating or using any.

Time saving and improvements to efficiencies within operations, but also to provide extra insights for other people in the team as well. So in every area of business, there's often room for improvement, like lead gen reporting, every area, and you just break it down into much smaller processes for, okay, so what can we optimise here?

Alex: And what are you seeing as the most common ones as you go into to different agencies? What are those workflows that are kind of consistently coming up?

Emily: Hardly anyone uses all Claude and share whatever they use projects across the team. So everyone's redoing like how they use prompts. Using different fonts and using the LM differently basically.

And of course, if they just had those things as saved in business models and shared across the team, they would have a lot of efficiencies because some people are playing about with and got really good ones for getting the app that they need and they haven't told the other people in the team. So other people are spending the same time on it.

And also getting. Potentially less good outputs. And that's like a really easy win to apply across the team. There's a few people that will probably be really good at prompting and say, Hey, can you share these prompts with the rest of the team, like within the platform so that everyone can get the same consistent outputs that you need.

And then other people, if they have an improvement, great, feed it in and this is how we do it. But that's a really common one that people are just. Keeping their use cases kind of isolated across really common tools that the whole team are using. And then everyone's doing the same thing again and again and again.

So that's a big waste of time across agencies.

Alex: And why do you think that is? Are they just not thinking about the fact that they could be sharing it? Or is it a little bit of IP that they wanna keep to themselves as individuals?

Emily: I don't think it's the fault of the individuals, actually. I think it's because.

Operations, how people are. Their workflows. So they're not thinking about this kind of new layer of how people actually get to the output, and they haven't changed their workflows to add that in. So it should be that, for example, there's someone that's responsible for, if someone's using Claude for example, there's someone who in the team who's responsible for.

Checking the problems, optimising them, you know, getting feedback from the team what they're using and storing that centrally for the whole team to use. But people just haven't got there. With using AI, it's kind of sneaked in under the radar and people aren't actually taking control of how people are using it in their agency.

A because. They might not have clearly defined who it sits with. Therefore, like no one really owns it, which is most likely the case. And C, because like even leaders, they're not the top users of it. It'll be the team. They're the top users of IT. Leaders will still be a bit behind with the use cases of it, so therefore they don't take charge of how it's being used.

There's kind of two problems that are causing this individuals great. I mean, they should be testing it. That's how we work now. But the problem is with leadership and the people running. The companies that they haven't thought about our workloads have really changed over the last couple of years. We need to redefine and train the team with how we're doing it.

Now,

Alex: And I think, I guess it also depends heavily on the tool and the licencing that they've got in place.

'cause obviously with ChatGPT, they can create and share their custom gpt and have that as a set. Benchmark for the team in Claude. I think it's a lot harder to to share those cowork plugins or the projects that you're, that you're working on with your, with your team is my understanding. Are you, are you sort of seeing that difference between what they're using and the outcomes that they're getting?

Emily: Yes, but you shouldn't really have everything in the platform because likelihood is, as everyone's been changing from ChatGPT to this year, you'll want to change the actual platform. So the same as with anything else your, so. Like how you do it should live somewhere else. And then you take that and people can use it with whatever tool they wanna.

That's kind of good SAP management and process management that all your processes live. Standalone and actually you can be flexible with the tools that you use it for. So for example, if there is a list of prompts, it's good that people test different platforms in some cases to see what the outcomes are.

So depends on your agency and how you want to lay it out. But you might have, for example, Gemini going on if you use Google Workspace. But because Claude gets such good reviews, might want some people to be testing Claude as well. So if it's all dependent on it being within the platform and shareable in there.

It. You need to pull that out as a habit somewhere else, like notion or some kind of workplace that you share across the team that's well organised. And then people can use different LLMs because people should be quite flexible if they can be, and agency should be flexible to test new tools when. They each overtake each other in terms of how much progress they're making

Alex: And how do you maintain that then, because they do have to live in the system ultimately to be able to sort of run them fairly autonomously, particularly thinking around Claude Cowork.

So if you've got. Your SOP saved centrally, as you say, notion or Google Drive, but then you're building out something in Cowork where you've got particular skills and connectors to run a task. There's a danger then that that gets tweaked and updated within the platform and actually what you've got stored outside the platform so it becomes out of date.

What's the the best way of kind of managing that?

Emily: To be honest, that's like normal process management. This happens all over the place. You know, even in say project management platform, you might have onboarding. Set up in ClickUp, for example, and then what will happen over time is that people will develop those and there'll be a complete different template and the SOP becomes a bit obsolete over time.

Someone usually the operations person or the head of that department who is responsible for keeping that documentation up upstate, has to do the same thing. With that. There needs to be a central place that everyone can access and you just decide the cadence. That gets reviewed and gets updated. We need to be a bit more flexible.

I don't believe in loads of recording of SOPs that just go stale, but there does need to be a central place of how you record, how your business does things, and someone usually a head of box. Doesn't necessarily do it all, but they have the coordination of how that is stored and how often it's updated.

And it might be in the case of LLMs, for example, because someone probably is more experimental than others and might test new things and stuff. They might work really closely with the. Say, you know, we need to review this more regularly because you know, this is always progressing and that's fine. That's great.

It's finding the right cadence for what needs to be documented in sap. Not every change, not every update, but this is how we use this l and m, like this is the processes we use it for. You don't have to record every update that testing, but just what cases you use it for and how roughly, and then of course it can evolve over time.

Alex: Yeah, and I guess it's a different level of detail as well. I'm, I'm working with a client at the moment who runs marketing agency actually, and she's, she's a delight to work with 'cause she's documented all her processes. And then what I'm effectively doing is saying, okay, well that's just under process.

This is what it would look like if you. Applied it in Claude and what you would need to build if you did it that way, versus if you did it in a different model. So the process kind of remains fairly consistent and then actually it's just the prompts, for example, or the skills that she's putting into Claude that are going to vary and develop and progress over time.

Emily: Yeah. And. The same as with all SOPs. I say if you need your team to do things in a certain way or like in a very specific format, you need to document that in your SOPs and give clearly step by step. This is what happens if actually you don't mind, which in some cases is the way you don't mind how they get to that outcome.

You just tell them the parts that they do need to do. How, and then you say, and this is what else we expect. So you can either have more broad kind of rules or like steps for how you do things, or very specific, if it's like this, you know, naming conventions, this needs to be named in this specific way because all of our ads are named in this way.

Great. You have to really clearly lay that out. If it's more that you don't mind how they get to their strategy, but you expect them to deliberate weekly in this kind of format, you tell 'em the parts that you're fixed on. They can then choose how to do it, which allows for experimentation within AI or other things as well.

The team should be allowed to make improvements on what's already there, and the main thing is to have someone who's interested and ask the team what they're doing or what they're trying, because then you'll know actually whether the problems are in your agency. If you know that everyone's trying to fix something, it means that there's a problem with it.

So it's something that you as Knox person or you as head of department. To think, okay, we need to make improvements on this, or we need to investigate a new tool for this because the whole team has been playing about and trying different prompts and doing this, so therefore it's something that they find a bit painful to do.

Alex: Yeah. And I guess within that you're also capturing where's the human in the loop and where are you gonna use and how are you gonna use AI within that standard process? And, and that. Again, we'll will evolve over time. We said we kind of wouldn't talk too much about tooling, but inevitably agencies have already got a a stack of tools.

Where are you seeing that? Actually there is already AI built into the tools that they've got, but they just don't know or they're just not using them? What are the common errors there?

Emily: Always project management platforms have a load of. AI potential that agencies don't use. So because they're developing so quickly, I think, and people don't really keep an eye on the updates.

If you've taken on the tool from you'd probably be aware. But if you've had the tool in place for a long time and they just consistently make updates, you tend to ignore them. So. It's good again, to have someone who's responsible for owning that so that they're responsible for keeping eye on the updates and choosing which ones are relevant for the team and kind of rolling it out with the team.

It's important to roll out updates because the team will continue to do things inefficiently that potentially there's like way easier ways of doing. ClickUp has loads of AI as do Asana Monday, all of them in terms of. How to get a load of information out more quickly. Like a good example is that I've implemented with a client recently is they have problems with designers and like feedback the time to go from getting the design the brief done, and then the design completed and we could get a really good layer of information using AI saying like, tell me.

All the times between each of the tickets tell me like, what's going wrong? Like, what's the questions back and forth and stuff. And AI will give you, AI within ClickUp will give you a really good level of insight that we wouldn't have had before. We wouldn't be able to question. Click up in that way. So you might be able to get reports and dashboards, but you wouldn't be able to question it in that way and then dig into, oh, okay, so 50% of the tickets didn't have the right folder on.

Can you tell me who the main person was who was like not giving that information so you can really dig into what the problems are really quickly. Basically, if you have someone with that mindset. To give AI the right prompts. You can get really good level of information on that platform alone.

Alex: Brilliant.

And I suspect that's probably the case across a lot of tools that they're seeing as well. You mentioned in your process around measurement, and that's obviously a core part of your engagement, but also anyone who's looking at implementing AI, just talk us through a little bit more about that. What are those core measures that people should have in place?

Emily: So AI, but it's process based. So it's thinking, what am I trying to achieve by changing this process with AI or not? But usually at the moment, changes should be incorporating how you could use AI, because the tools normally have a really quick way of doing things better using AI. So you should set yourself a goal for what's the outcome that you expect.

So whether it's like money, time, what's the point of making the change to that process? On a cadence. So weekly, monthly, depending on how intensive you're going with making changes. Are you getting the changes? Do you expect, and if not, why? So is it that you haven't trained the team? Is it that the tool isn't doing what you need it to?

Is it that the process that you design isn't working? It's fine that things. Don't. But if you don't set a goal and you don't measure it, you never know. So that's where process changes happen. But then people aren't actually seeing, does it make any difference? And that's the only way you're gonna stay, is that actually having an impact on our margins and how, so I'm trying to introduce it into a sprint, into a manageable way, which is like looking at individual processes and how we can improve them, but longer term.

People really need to be looking at like redesigning the whole agency because capabilities of the tools and what people can do is very different now to how it was two years ago. So roles and structure shouldn't remain the same because there's lots of different ways of doing things. So yes, you can look at the process individually and make efficiencies, but actually you look across your whole model about how to really utilise people that.

Are excellent at using AI and can really drive your business forward by doing X, and how you actually embed it into each role that people have this continuous improvement mindset, which needs to be now more than ever about. I need to learn how I can question what I'm doing and find a better way of doing it, because there's always gonna be a better way of doing it now, and people need to understand where their role is important.

So where. Their personal intervention really matters versus. Things that should be automated or using AI like that needs to be clarified and most agencies are nowhere near addressing that.

Alex: And I like how you look at what you're measuring and the outcome of that to understand why and question, well why has that or hasn't that that been succeeded?

How do organisations then take those? Lessons that they're learning both positive and negative into the rest of the business. So if a particular workflow has or hasn't gone well and they're looking and understanding it's to do with adoption or to do with data or to do with the tooling or the process.

And do they take that further?

Emily: So if it's gone well, which in lots of cases it will go well, then it's how you can adopt that further or how your learnings from that you can get that wide across the organisation. So of course, if you are changing your process, you shouldn't. Change it across the whole organisation straight away.

You should test in a kind of small pot, see how it goes, and then if that works, well roll it out wider. So often teams within agencies work quite a lot in isolation, so the more that you can encourage the learnings to be shared. It gives other people ideas. It might not be exactly the same tool, it might not be exactly the same process, but if you share what's gone really well, it can impact them because they get inspiration about what they could do or what they could change.

And then that can be rolled out as well. And with the flip of that, so with the negative where it hasn't gone well, so for example, if it's the still the team have no idea what to do, you've got a problem with. Change management or training rollout, which it gives you an opportunity to review that as an organisation because agencies really have to be good at.

Making changes. Making changes. And if you're not, it's something you have to address. So you have to address how are we gonna get the team to take on new things, to adopt new tools, to adopt new processes? Because an agency that's still doing the same thing as it were two years ago isn't gonna be around in two years.

Alex: And how are you seeing the attitude towards that adoption as you go in? Are the majority of people on board and keen, or are you, are you meeting some resistance from some of the stuff?

Emily: So the attitude is generally positive and I think much more so than a year ago. I think it depends how leadership frames it in terms of like that's the main issue.

Obviously some people are quite nervous in any profession, but particularly in like some areas of marketing, for example, like. Creative or reporting or things like that obviously if you're suggesting things that will reduce the time they need to spend on their role, of course they could see it as a threat to their role.

So it's important how leadership frames it, that what they want to do is to remove kind of the boring admin manual things that people are doing. Time. Client relationship or on innovation or on how to do things much better using technology. There's so much opportunity for agencies not to cut team members, but they need to reframe how they're doing their job.

People, I think they want to be doing like manual. Tasks and things that should be automated or things that we can get AI to do, but they do like people get stuck because they feel like that's part of what they own. Whereas if we can reframe the jobs in terms of what people should be aiming for, is it should be much more for.

Account managers about like relationship building, coming up with ideas for like what we can do next. Then that's where people feel less nervous if they understand what it means for them and if they understand what their agency's attention is with using AI. What's the point and what are they aiming for?

Alex: Excellent. I'm gonna move to the quickfire questions now. What's the most unexpected way that AI has helped you?

Emily: That's a good question. The most unexpected way I think is, it just always surprises me I think. Like, so as soon as I think that's boring or like, I don't wanna do that, I just can find a way of doing it more easily, I think, really does lean into.

Stuff that I find interesting, AI can't do as well as me, but the stuff that I find boring and I don't wanna be doing, AI can generally do a pretty good job of getting 80% of the way. So I think that's where it surprises me is it does tend to lean into where you are an expert in and it doesn't overtake that part.

I can still. Most of my time, like with clients on how I do strategies and how I actually get agency to adopt AI more effectively. But I can use it for providing like ideas, insights, backgrounds, where I've used it with other clients, which is stuff that I find boring. Pulling all that together so it leans into where I want to be spending my time.

It really helps me do that.

Alex: Brilliant. And what would you be doing if it wasn't for your job?

Emily: I think I've said this quite a lot, but I would be a florist probably, which is like totally the opposite. Anything that I do now, but unfortunately it's not. Maybe when I'm older, maybe I'll be able to do it, but yeah, Floris is my dream job.

Alex: You're the second person in a row that's, that's given that answer. Really. Yeah.

Emily: So it must be, it must

Alex: Must be something about it. Maybe you're spending so much time in AI and computers that it's, it's looking for something that's, that's the complete opposite.

Emily: Yes, exactly.

Alex: And what's one thing that you do regularly to help protect your mental health?

Emily: I wake up early, so I'm not one of those people. I think that people hate because they wake up early. I wake up early because it's very practical for me. So I wake up early every day at like 5 30, and I exercise first every day. And because I have a small kid, so she's six. And so if I wake up early and do my work before she finishes school at two.

I feel like I have a really good work life balance because I get my work in before that time, I've already exercise. I do my work, and then I get to spend time with her after two o'clock. Sometimes do some work, but generally. No, I get to spend time with her and it protects that. I don't feel so much under pressure that I feel so torn in different directions.

Alex: Nice. I like that. And we should probably tell people that you live in Malta and that's why. Why your child finish the school at two and why you get to enjoy the sun in the afternoon. Yes,

Emily: Exactly.

Alex: Brilliant. Thank you very much, Emily. That's been a fantastic conversation. So thank you for coming on.

Emily: Thank you very much for having me.